Professionals across supply chain are urged to move into AI roles. The promises are compelling: substantially higher income, greater job security, strategic influence.

But which roles?

Supply chain roles like Supply Chain Agent Manager, AI Compliance Officer, and Robot Manager are emerging with real budgets as AI transforms supply chain work. Yet the path forward remains unclear.

Four emerging roles will define supply chain leadership in the agentic AI revolution.

Managing agents requires both business acumen and technical fluency. In 2026, three forces will converge: capability maturity with agents actively performing tasks like supplier evaluation and risk monitoring, strategic pressure from leaders embedding Agentic AI across the procurement lifecycle, and operating model evolution with digital platforms moving toward extreme automation and deep integration.

These roles won’t appear overnight. They will evolve from existing procurement, operations, and logistics roles. The common thread across all of them is ownership: ownership of agent outcomes, accountability for system behavior, and continuous optimization as business conditions shift.

Role 1: AI Supply Chain Leader

AI supply chain leaders turn agentic AI from technical capability into business value. They oversee the application of AI across the entire supply chain function. They define and execute strategy for deploying agent use cases. They combine technical understanding with operational ownership.

This role doesn’t have a defined career path. It attracts change agents focused on transformation. They report directly to CSCOs and translate procurement goals into agent objectives.

Required skills:

• Deep supply chain domain knowledge (procurement, logistics, demand planning)

• Strategic thinking about how agents reshape workflows

• Ability to articulate AI business value in financial terms

• Cross-functional influence across procurement, IT, and operations

This person sits between the CSCO and the technical team. They ask the strategic question: “What supplier or procurement challenge becomes solvable when we deploy agentic AI?”

Role 2: Agent Operations Manager

Agent operations managers are the human supervisors of agentic workflows. They monitor execution, intervene when needed, and ensure accuracy, compliance, and business continuity.

These roles typically emerge from procurement operations or supply planning. They bring deep understanding of the workflows being automated and the outcomes those workflows must deliver.

When an AI agent evaluates suppliers, the agent operations manager confirms the logic is sound and aligns with business priorities. When an agent processes RFQs, they ensure compliance requirements are embedded in the agent’s decision logic.

Required skills:

• Deep operational knowledge of the workflow being automated

• Ability to read and interpret AI recommendations

• Understanding how AI agents work, what data they need, and how to interpret structured and unstructured data output

• Compliance awareness and audit readiness

• Comfort with continuous monitoring and rapid exception handling

This is not a new role requiring new hiring. It’s an evolution of existing procurement coordinator and operations roles.

Role 3: No-Code Procurement Designer

No-code procurement designers design, test, and deploy AI agents using no-code platforms. They evolve from business analysts, process owners, and automation leads who already understand how work should flow.

An agentic procurement engineer acts as the bridge between human judgment and autonomous systems, designing and orchestrating intelligent agent workflows that automate sourcing, negotiation, compliance, and spend management.

With no-code AI platforms, they move beyond documenting requirements. They actively shape agent goals, constraints, and behaviors. They test agent logic against real procurement scenarios.

Required skills:

• Process design and continuous improvement mindset

• Understanding how to write clear prompts and communicate requirements so AI systems understand procurement nuance, like how “ASAP” from one customer means 48 hours while from another means 2 weeks

• Ability to work iteratively with agents and refine outputs

• Patience for testing and learning by doing

• No formal data science training required—learning by doing and asking questions is how you build skill and confidence

Role 4: Supply Chain Workflow Architect

Workflow architects take a holistic view of how humans and agents work together to accomplish supply chain goals. These architects design workflows where humans and AI agents complement each other, ensuring AI enhances rather than replaces human expertise in complex logistics decisions.

At the core is deep understanding of the business function and workflows. Strong business analysis is essential to redesign work for an agentic model, not simply automate existing manual processes.

Agentic AI succeeds when embedded directly into integrated business planning workflows used by supply chain teams, paired with decision memory that allows AI to learn from outcomes, and paired with digital twins of the physical supply chain to ensure AI recommendations respect real-world constraints.

Required skills:

• Supply chain strategy and operations knowledge

• System thinking about how procurement, demand planning, and logistics interconnect

• Ability to identify where agents add value vs. where human judgment remains critical

• Change management and organizational design

• Understanding of data architecture and integration challenges

The common thread: ownership

All four roles share one critical element: ownership. Ownership of agent outcomes. Accountability for system behavior. Continuous optimization as business conditions change.

While some manual tasks will inevitably be automated, organizations view this as an opportunity to elevate procurement teams. Rather than spending hours on data entry or invoice matching, procurement professionals can shift focus to higher-value activities like strategic sourcing and supplier relationship management. New positions like AI data trainers and ethical oversight leads are expected to emerge, offering exciting growth opportunities.

What this means for your career

If you work in procurement or supply chain operations, 2026 is when you decide whether you lead the agentic revolution or manage around it.

You don’t need to wait for a formal role to emerge. Start now. Ask your CSCO if you can pilot an AI agent for your highest-friction process. Volunteer to be the agent operations manager. Learn the no-code platform your company is evaluating. Help design how humans and agents will work together.

The person who figures this out inside your organization will be the one leaders turn to when they ask “What should we do about agentic AI?”

Explore emerging supply chain AI tools at Chaine.AI (www.chaine.ai)—our directory covers agentic platforms, no-code tools, and orchestration solutions shaping 2026 procurement.

Which role matches your supply chain future?

Are you drawn to strategic leadership? Operations management? No-code platform design? Workflow architecture? Which emerging role do you see yourself evolving into? What skills are you developing now to lead the agentic revolution? Share your thoughts in the comments.

Join the Chain.NET community for strategic discussions on AI-driven procurement roles, agentic workflow design, and supply chain leadership transformation. We run regular panels where CSCOs and procurement leaders share their emerging role strategies and hiring plans. Connect with peers building their AI capabilities now.

Visit www.chain.net to join the conversation, and check our events calendar at www.chain.net/c/events for upcoming masterclasses on agentic AI roles and procurement leadership.

The automation is coming. Anyone denying it is delusional.

If the industry managed to build human-free warehouses, then what stops it from building human-light forwarding companies? The answer is nothing. The technology exists. The economics make sense. The only question is whether companies will implement it intelligently or turn it into another cost-cutting disaster.

Anthony Miller at Wiser Logtech recently discussed this online and his conclusion was blunt. Anyone who thinks this is not coming is in for a shock.

The right approach should be replacing outsourcing, enhancing in-house teams, automating everything possible, and having people work from exceptions. What the industry will likely see instead is immediate cost cutting, big decisions made without proper planning, higher risk, and apologies when it does not work out.

The pattern is predictable. The consequences will be severe.

The Warehouse Precedent

Brian Newman, who works in supply chain transformation, stated the obvious. “It’s coming. If you can automate a warehouse you can automate the chain.”

Miller agreed. “You can automate any process that is highly repetitive and data driven, whether the data is deterministic or not.”

The warehouse automation wave proved the concept. Facilities now operate with minimal human intervention. Robots pick, pack, and move inventory. Systems route orders and manage exceptions. Humans handle edge cases and maintenance.

Freight forwarding involves similar work patterns. Repetitive data processing. Document verification. Status updates. Exception management. Rate quotes. Booking confirmations. Most of this work follows predictable patterns that AI can handle.

The technology is ready. The question is how companies will deploy it.

The Big Tech Model

Miller noted what has happened to big tech companies and their headcount. It feels like just a matter of time before sizeable forwarders start doing the same.

The parallel is direct. Tech companies overhired during growth periods. When efficiency became the priority, they cut deeply. Meta eliminated thousands of positions. Amazon reduced headcount. Google streamlined operations. Microsoft trimmed teams.

These companies had strong technology foundations. They still cut aggressively. Freight forwarders with weaker technology will face more pressure to reduce costs through automation.

Paul Claydon at a supply chain technology firm agreed with the assessment. Miller responded with what everyone is thinking. “I’m just waiting to see how the big 3PLs justify huge headcount cuts.”

The justification will be simple. Automation enables efficiency. Market conditions require cost reduction. Shareholders demand profitability. The cuts will come.

The Human-Light Reality

Mark Woolnough at a freight operations and recruitment firm made an important distinction. “Human free and human light are very different. Also human light is probably the accurate terminology.”

He pointed to Notion’s new agent updates as an eye opener. “Obviously not industry specific but if used by someone internally with the right mindset...”

The future is not human-free. The future is human-light. Small teams managing automated systems. People handling exceptions rather than routine work. Expertise concentrated in complex problem-solving rather than distributed across transactional tasks.

Peter Creeden, a global supply chain executive, emphasized that the shift is not just about automation but redesigning the forwarding business model around people and technology, not just cutting headcount.

He challenged the sector to rethink resilience. “It’s not just risk management but building capability, connectivity, and accountability. Human-light shouldn’t hollow out the workforce but empower skilled people to work with smarter systems and AI, improving exception handling, compliance, and trust, not cutting costs.”

Miller agreed but added a dose of realism. “But we both already know how this is going to play out. Hard lessons will be learned.”

The Implementation Problem

Stewart B. at Ziegler Group referenced a post about using AI to remove problems in supply chain as opposed to using it to figure out how to do workarounds quicker. “Both need deep planning, a progressive and adaptable strategy and excellent execution rooted in change management, which relies heavily on experience of the business. There’s lots of AI stuff flooding the industry, lots looks a bit clunky and gimmicky, but in the mid or long term, someone is going to start getting this stuff right.”

Miller’s response captured the industry’s frustration. “How to do the workarounds quicker. I swear, the amount of times I heard workarounds from forwarders using CargoWise. Hate it.”

He continued: “This comment needs to be turned into a standalone post. It is 100% true. But making the AI work in the right way will be hard. We’ve seen RTTVP fail. We’ve seen Blockchain fail. We’ve seen digital freight forwarding fail. I believe that we cannot afford to see AI fail, so it will succeed. I just hope that it will succeed in the right way, and not become another round of workarounds.”

The history of technology implementation in logistics is littered with failures. Real-time transit visibility promised transformation but delivered marginal value. Blockchain was supposed to revolutionize supply chain transparency but became a solution searching for a problem. Digital freight forwarding disrupted nothing.

AI cannot afford to follow the same path. The industry needs it to work.

The Foundation Problem

Francine Nielander at Lean Six Sigma consulting identified the critical prerequisite. “If you have your processes and data structured and you can automate or even optimize using AI, great. But those are not the companies that are in trouble and are likely to go for a quick AI fix. It’s not going to help you if you don’t have your ducks in a row. It will make processes even less transparent. Why was this order placed? I don’t know, the AI did it. Good luck in making sense of that.”

Miller agreed. “There is no quick fix in our industry and anyone suggesting otherwise needs to go do something else.”

Samil Shah raised the question directly. “Traditionally, getting value out of software required a good data foundation which in turn relied on good, consistent processes. With Agentic AI, can businesses skip the foundational work and jump straight to value?”

Miller’s answer was one word. “No.”

This is the trap waiting for companies desperate for cost savings. AI built on bad processes and dirty data will amplify problems, not solve them. Companies without solid foundations will implement AI and create expensive chaos.

Jennifer Morris at Ship Happens warned about the all-or-nothing approach. “I think the issue is many companies are just diving in head first and making it all or nothing. I have a feeling some of these legacy companies that were kind of flailing already and have turned to AI so they can make major cuts, not mentioning any names at all, are going to have problems. I think a more strategic approach and implementation will be what truly works. Not slap on AI, they barely understand, and hope for the best.”

Miller identified specific companies to watch. “I’m looking forward to seeing what DSV and Maersk do. I’m concerned about the likes of K+N and Ceva/Bolloré. Also quietly excited about some smaller players like Geodis. We’ll see how it plays out, but yes, those who are diving in head first are in trouble. No point getting first mover advantage as an LSP. It’s about long term vision.”

The Human Element

Nacho Gil de Sagredo, who specializes in digital and sustainable supply chains, raised an important constraint. “I think this would work with human-free BCOs. While clients have people in procurement there’ll be people in sales and operations on the LSP side. I think this is why digital forwarding has not exploded yet. Humans like humans when there’s risk involved.”

The observation points to a fundamental limitation. As long as customers have human procurement teams, they will want human contact on the supplier side. Automation can handle routine transactions, but relationship management still requires people.

This creates the human-light model rather than human-free. Small teams managing customer relationships while AI handles operational execution.

John Vonk at Seeburger Benelux agreed. “Totally agree that human-light logistics is on the horizon. The challenge isn’t if we can do it, but how we do it responsibly. The companies that win will be those who blend automation with human judgment rather than swinging too hard on cost cutting.”

The Execution Details

Luca Conner at Pack’N provided practical guidance. “The sweet spot is automation for the routine and people for the weird stuff. The mistake is cutting seats before you can measure exceptions and promise kept. What’s worked for us is simple flows, clear owners, and tracking exception rate and cycle time before we pull labor out.”

He asked where the cleanest early wins are appearing: quotes, status pings, document checks, or invoice matching?

Miller responded that document checks is a tale as old as time with OCR solutions. It should improve greatly and remove the need for armies of people in low cost of labor countries doing manual validation. He identified customs and compliance as the biggest area to change. “It is a major drag on global supply chains.”

This practical approach, measuring exception rates and cycle times before removing headcount, represents responsible implementation. Most companies will skip this step.

Kenneth West identified the strategic shift. “Legacy tech stacks are hitting their ceiling. The shift from human-heavy to human-light isn’t just about cost, it’s about control. Agentic AI flips the model: instead of outsourcing complexity, companies can internalize intelligence. The ones who build exception-based workflows now will lead the next wave of operational resilience.”

Miller called out the buzzword density but acknowledged the underlying point. Companies that get this right will have operational advantages competitors cannot match.

The Reality Check

Ian Aguilar offered necessary skepticism. “I am a big fan of the current gen AI systems. Very useful, far more so than Google was historically. They do get things wrong frequently, though. Like, on the daily, and can be wrong in any given topic, even if you call them out on it multiple times. I’ve had both ChatGPT and Grok be wrong on simple addition, subtraction, multiplication even.”

His conclusion: “So far they are a nice to have tool, yet very far from a necessity. I absolutely could not trust business activities or decisions to it. Very interested to see where we are in 3-5 years though.”

Miller acknowledged the skepticism is healthy. But he also pointed to the rapid pace of improvement. What seems unreliable today may be dependable in months, not years.

Vlad Nikalayeu at Skypace identified the accountability problem. “You know what’s the main problem? It’s still people who’ll be eventually taking responsibility for what AI does.”

He imagined a future where LinkedIn profiles include AI performance metrics. Companies will want proof that candidates can work effectively with AI systems. The HR function transforms into validating human-AI collaboration capabilities.

The Nearshoring Alternative

Troels Daugaard noted that sizeable forwarders are using nearshoring instead to cut costs. Miller questioned why asset-light companies would want to nearshore.

The observation reveals competing cost-reduction strategies. Nearshoring moves work to lower-cost locations but maintains human headcount. AI reduces headcount but requires technology investment and change management.

Companies will pursue both. Nearshore operations will implement AI. The combination will drive costs down faster than either approach alone.

The Warning

If legacy ERP and SaaS players in logistics and supply chain are not using AI or planning AI functionalities, they are already late. The technology is moving faster than incumbent software providers can adapt.

If you are an LSP or BCO doing your own orchestration and you are already doing diligence or trialing solutions, you are ahead of the curve.

The gap between leaders and laggards will widen quickly. Companies that move now have time to learn and iterate. Companies that wait will face crisis implementations when competitive pressure becomes unbearable.

The human-light forwarding company is not a future possibility. It is a current reality being built by early movers. The question is not whether your company will follow. The question is whether you will move strategically or desperately.

Hard lessons are coming. Some companies will learn them in controlled experiments. Others will learn them through layoffs, customer losses, and operational failures.

The automation is here. The execution will separate winners from casualties.

Join the conversation on AI implementation in logistics, workforce transformation, and operational automation at Chain.NET, where supply chain professionals share real-world AI deployment experiences, debate implementation strategies, and connect at events focused on responsible automation. The future is being built now.

The global manufacturing landscape is shifting beneath companies’ feet. Tariffs, industrial policy, and geopolitical tensions are forcing supply chain leaders to rethink decades of assumptions about where to make products. Yet most companies lack the basic visibility needed to respond.

A January 2026 report from McKinsey & Company, titled “Decoding disruption to reshape manufacturing footprints,” surveyed 100 global supply chain leaders and analyzed 188 KPIs across industries. The findings paint a troubling picture. While 95% of companies report visibility into their tier-one suppliers, only 42% can see into tier-two suppliers or deeper. Worse, that visibility has actually declined since 2022, even as trade tensions escalate.

The Visibility Gap Is Getting Worse

Companies seemed to have learned important lessons during the pandemic. Supply shortages forced executives to map their supplier networks and identify concentration risks. But those efforts have faded.

Read more

The question isn’t whether AI will reshape supply chain work. It’s which jobs disappear, which ones transform, and how fast it happens.

A procurement manager spends two hours daily matching purchase orders to invoices. An AI agent does it in seconds. A demand planner builds forecasts from historical data and manual adjustments. An agentic system learns from thousands of patterns and recalibrates continuously. A logistics coordinator tracks shipments across multiple systems and creates status reports. An AI agent monitors, flags exceptions, and escalates automatically.

These tasks are vanishing. The question is whether the people performing them disappear with them.

Which Supply Chain Roles Face Real Risk

The jobs most vulnerable to AI share one characteristic: they are transactional, repetitive, and rule-based.

Procurement Clerks and Logistics Transaction Processors. These roles are already shrinking. Procurement Clerk roles face a 95% estimated chance of being reduced by AI, with clerical duties like creating purchase orders, verifying records, and data entry being highly automatable by AI-powered procurement systems. This isn’t speculation. It’s already happening across both procurement and logistics operations.

Purchasing Agents (routine sourcing). Purchasing Agents face a 70% estimated chance of being reduced by AI, as digital procurement platforms can automatically solicit quotes, compare suppliers, and even negotiate routine purchases. The agent does what humans once did—source, compare, recommend. The difference is it does it at scale, instantly, without fatigue or bias.

Inventory and Logistics Analysts (reactive management). Traditional inventory and logistics roles focus on managing spreadsheets, responding to stockouts, and manually adjusting thresholds. AI systems now predict demand better than humans, optimize safety stock mathematically, trigger reorders before problems occur, and route shipments more efficiently. Reactive management is becoming obsolete.

Logistics Coordinators and Order Processors (routine tracking and reporting). Tracking shipments across multiple systems, creating status reports, coordinating routine handoffs, and managing basic logistics tasks—these are perfect AI tasks. The role will not disappear, but the number of coordinators per operation will drop dramatically.

These roles share a pattern: they involve processing data, applying known rules, and executing routine decisions. That’s exactly what AI does best.

Which Roles Will Actually Grow

Not all supply chain jobs are equally at risk. Some are becoming more important.

Supply Chain Strategy and Risk Leaders. As AI handles routine decisions, human judgment becomes valuable for complex trade-offs. A CSCO who can design strategy around AI capabilities—using agents to execute while preserving human oversight of critical decisions—will be in high demand. The CPO role is unlikely to be replaced by AI; instead, it will be profoundly reshaped, transitioning from traditional cost control and sourcing oversight to a more strategic, digitally-enabled leadership role, with 90% of procurement leaders already exploring or using AI agents.

Supplier and Carrier Relationship Managers. Negotiation, trust-building, and strategic partnership development cannot be automated. An AI agent can handle transactional supplier and logistics provider interactions, but it cannot navigate complex business relationships. Professionals who excel at partnership strategy will become more valuable.

Supply Chain Data Stewards. Supply chain data stewards will employ data science using AI to analyze supplier networks, onboard data governance strategies, predict disruptions, and track product movements, proposing cost savings on a weekly basis. The demand for people who understand data, can govern AI outputs, and ensure quality will grow as AI adoption accelerates across procurement and logistics.

AI Enablement Specialists. AI enablement engineers source or help develop appropriate agents to deploy, mapping workflows and ensuring data is cleansed enough to support proper decision-making. Supply chains will need professionals who understand both operations and AI—people who can bridge business requirements and technology capabilities in procurement and logistics environments.

The pattern here is opposite to risk roles: these positions involve judgment, strategy, relationships, and oversight. That’s where human value concentrates as AI scales.

The Timeline Question Nobody Can Answer Honestly

The main debate centers on speed. Some experts warns of massive job displacement in five years. Other argue adoption will be slow and the economy will adapt.

For supply chain, the honest answer is: it depends on your organization.

A Fortune 500 manufacturer with mature supply chain technology and executive commitment to AI transformation could eliminate 30% of transactional procurement and logistics roles within 24 months. A mid-market company still managing supply chain operations through spreadsheets might take five years just to implement basic automation.

What’s certain is this: the change is accelerating. Over 90% of CPOs are planning or assessing GenAI, yet fewer than four in ten have moved beyond pilots, underscoring a gap between intent and operational impact. The intent is clear. The execution lag is real. But that lag is narrowing.

Within three years, any supply chain professional whose entire value proposition is processing transactions will be vulnerable. Within five years, that vulnerability becomes acute.

What Procurement and Logistics Professionals Should Do Now

If you’re a procurement specialist, logistics coordinator, demand planner, or transportation analyst whose job centers on transaction processing, you have a choice window that’s closing.

Skill up toward strategy, judgment, and relationship work. Learn how your organization’s supply chain works holistically, not just your slice of it. Understand how AI agents are reshaping procurement and logistics processes. Develop the ability to oversee and refine AI outputs rather than just executing them.

Specialize in areas AI struggles with. Supplier and carrier negotiation. Contract strategy. Risk assessment under uncertainty. Supply chain network design. Logistics optimization under complex constraints. These require judgment and stakeholder management. They don’t automate easily.

Become fluent in AI. Not as a coder. As an intelligent user. Understand what AI agents can do, what they can’t, and what they’re missing. Become the person who asks “what’s the AI not seeing?” That skill is increasingly valuable in procurement and logistics.

Move toward oversight roles. As organizations deploy more AI agents, they need people to govern them. Audit them. Ensure they’re behaving correctly and making sound decisions. That’s a growth area across procurement and logistics functions.

The Uncomfortable Truth

Saying “the supply chain economy will adapt and create new jobs” is technically accurate but personally unhelpful if your job is the one being eliminated.

Yes, new roles will emerge. Yes, the economy adapts. But adaptation takes time. The person whose job gets automated in 2027 doesn’t benefit from a new role being created in 2030.

That’s why the time to move is now—before the market becomes crowded with procurement and logistics professionals realizing the same thing.

Organizations that are ahead in AI adoption are already recruiting for strategy and governance roles. They’re already struggling to find people who can bridge operations and AI. That’s your window to reposition yourself.

Close it and you’re competing with thousands of other procurement and logistics professionals for the remaining transactional roles—which will pay less than they do today because, well, AI can almost do them.

Is your supply chain job at risk?

What role do you play in your supply chain? Does your job focus on transactions and routine decisions, or strategy and judgment? What skills are you developing now to adapt to AI-driven operations? Are you in procurement, logistics, or another supply chain function?

Share your perspective in the comments. Your honest assessment matters—especially if it helps other professionals see their situation clearly.

Join the Chain.NET community for strategic discussions on AI adoption, reskilling, and the future of supply chain careers. We host regular forums where procurement and logistics professionals share experiences navigating AI transformation, discuss which roles are evolving, and explore career strategies for the AI era. Connect with peers proactively reshaping their careers.

Visit www.chain.net and check our events calendar at www.chain.net/c/events for upcoming sessions on AI adoption, skill development, and supply chain career strategy.

Nike just redrew the corporate power map. The sportswear giant eliminated two cornerstone C-suite positions and handed their responsibilities to a newly empowered Chief Operating Officer. The move has executives across industries debating whether this signals a broader shift in how companies should organize leadership.

The restructuring, part of CEO Elliott Hill’s “Win Now” strategy, removed the Chief Technology Officer role held by Muge Dogan and the Chief Commercial Officer position occupied by Craig Williams. Both executives are leaving the company.

In their place, long-time supply chain leader Venkatesh Alagirisamy, known as “Venky,” steps into an expanded COO role starting December 8. He now oversees supply chain, planning, operations, manufacturing, sustainability, and technology.

The changes don’t stop there. Regional heads for Greater China, EMEA, North America, and Asia Pacific/Latin America now report directly to Hill. Global Sales and Nike Direct (e-commerce and retail stores) now report to CFO Matt Friend.

The reaction from operations and supply chain executives has been swift and divided.

The Case for Consolidation

Dr. Francois Gourd, a strategy and executive management consultant, welcomed the return to simpler structures. “In the ‘old times’ there were only CEO, COO and CFO and it was working very well. The inflation of CXOs that came afterwards created silos, unnecessary structure, inefficiency, additional costs and confusion. The most efficient organizations are the simplest ones.”

His comment drew strong agreement, with nearly 80 reactions from executives who have watched C-suite proliferation complicate decision-making.

Dirk Fischer, COO at Huf Group, appreciated the validation of his role but raised a practical question. “Being a COO, this is of course nice to hear. But reading what you said, for what you need then a CEO? But one thing is also clear. It is the person that qualifies for these roles, not the title.”

Michael Stanier, a managing partner and brand builder, questioned why Nike ever diluted the COO role. “The surprising thing here is why Nike ever diluted the role of COO in the first place. It is the obvious C-Level operational integration role to enable fast decision-making and to deliver accountability.”

Technology Moves from Silo to Operations

The decision to fold technology under operations drew particular attention. Frederic Gomer, who analyzed the restructuring, framed the shift clearly: “Tech is no longer ‘IT’s job.’ It’s ops work. If tech touches service, lead time, inventory, delivery, allocation, store flow, forecast… it belongs with the people who run the system.”

Habeeb Rahman, a Group Deputy CTO, endorsed the logic. “Right move. Technology is the core driver of business. If COO does not understand technology, it becomes difficult to compete in the market.”

Nico Bac, founder of Digital Procurement Now and formerly at P&G, saw the move as part of a broader trend. “Technology is a real game changer and needs to be better embedded into every part of the business. There is still some way to go here for most big businesses.”

Marcela Escobar-Alava, a CIO and CDO, shared her perspective on integration. “I’ve always seen my role much more integrated into operations than a standalone tech silo. I love the less aligning part. Personalities and fiefdoms always get in the way of alignment and progress.”

The Skeptics Raise Valid Concerns

Not everyone sees the consolidation as wise. Ghassan Kabbara, a fractional CIO, warned of role overload. “This feels like the Peter Principle in action. Leaders are being loaded with responsibilities far beyond their core strengths. A strong COO now owns tech, sustainability, planning, supply chain and integration. That’s not operations anymore. That’s five professions in one.”

He extended the concern to the CFO’s expanded remit. “Same with the CFO: finance plus sales, customer experience and growth execution. This isn’t promotion. It’s sideways overload. Role saturation.”

Davide Petruzzi, founder of OrygoAI, shared similar reservations. “That looks risky. Too much stuff under one person. Plus tech is very fast moving and most COOs don’t have technical backgrounds. Let’s see if it works out well for them.”

Josep Ragull, a supply chain and ESG executive, questioned whether fewer voices improve decisions. “Not sure though how reducing the number of voices in the management team can help run the business better. Less debate, less opinions, faster decisions indeed, but better ones?”

He added a pointed concern about the commercial reporting line. “Putting Sales and Marketing under Finance is the best way to kill any creativity, innovation and disruption, which is what made Nike great.”

George Saives, a consulting executive, was more blunt about sales reporting to the CFO. “Sales reporting to the CFO! YIKES! CHIEF PREVENTION OFFICER.”

Integration as the Scarce Capability

Michael Allen, a global operations and supply chain executive, offered perhaps the most nuanced analysis. “This is less about org design and more about accountability. What Nike is signaling is that integration has become the scarce capability. When demand, supply, capital, technology, and sustainability are decoupled, performance degrades quietly until it breaks loudly.”

He continued, “Placing technology under operations isn’t a demotion of tech. It’s an admission that value is created where systems meet execution. Code doesn’t move product. Operating models do.”

Stefano Bianchetti, a senior supply chain lead, reinforced this view. “The point is not that the COO role is getting ‘bigger.’ The point is that someone has to own the real trade-offs when demand, capacity, technology and capital collide. When that ownership is missing, organizations fill up with functionally correct roles that are systemically irresponsible.”

Context Matters

Several executives cautioned against treating Nike’s move as a universal template.

Patrik Paňko, a commercial and omnichannel strategy specialist, emphasized timing. “This feels less like a universal org blueprint and more like a phase-specific decision. When scale, inventory risk and capital efficiency dominate, integration under a strong COO makes sense. In a growth or disruption phase, separating Commercial, Tech and Ops often creates more speed and tension, in a good way.”

Puneet Dua, an FMCG specialist, agreed. “If this OM is what Nike needs to turnaround, great for them. Others don’t copy paste. Find your own OM. Context is important.”

Bruno Pontinha, a senior client partner, noted the model doesn’t fit all industries. “This logic is not totally true for Telco. The CTO remains a key role in this industry as CSPs still deeply rely on the mobile and fixed network tech infrastructure that enables their services.”

The Execution Question

Sotiris Karababas, a senior business leader and interim supply chain executive, raised a critical implementation concern. “IT moves under the COO, and the press release promises ‘faster decision-making’ and ‘operational synergy.’ But let’s be realistic: A change at the top doesn’t guarantee a more efficient company.”

He continued, “The real impact depends entirely on the structure one layer below. If you install an IT Director between the technical teams and the COO, you haven’t shortened the loop. You’ve likely lengthened it.”

Ingo Winterhoff, a former Adidas executive, emphasized that execution requires more than restructuring. “Customer centricity, product obsession and proper inventory levels are key ingredients to lasting success. Executing this or any operating model successfully requires team play at the highest level.”

What This Means for Operations Leaders

Maria S. George, a global supply chain strategy executive, posed the question many are asking. “The faster now and more complex cycles ‘idea to market’ call for streamlined decisions and end-to-end ownership to best serve ever demanding customers. The BIG QUESTION is: do companies have ‘ready now’ COOs to take on the larger scope?”

Gabriele Tagliavia, a global COO, suggested the evolution continues. “Running the operating model is clearly the future and I would push it even more: running the operating model by making a clear separation between what is still human-led vs AI.”

The debate over Nike’s restructuring reveals a profession in transition. The COO role is expanding from operational execution to enterprise integration. Whether that expansion creates clarity or chaos depends entirely on the leaders who fill these seats.

As Colin Emberson, who scales complex multi-market businesses, summarized: “Running ops is table stakes. Owning the operating model is the job now.”

Continue the discussion with operations and supply chain leaders on Chain.NET.

Here’s a question worth asking honestly.

Where do the most useful insights actually come from when you’re running a supply chain today?

Not industry reports. Not consultant frameworks. Not conference keynotes.

From other practitioners.

The leaders who consistently outperform their peers share one trait: they’re plugged into networks where real knowledge flows. Where someone who faced the same challenge last quarter shares what actually worked—and what didn’t.

This isn’t a soft skill. It’s a strategic advantage.

Static knowledge can’t keep pace with dynamic reality

Supply chains are moving too fast for traditional learning models.

AI adoption. Tariff volatility. Regulatory pressure. Geopolitical disruption. Talent shortages. Sustainability mandates. Most of what defines supply chain leadership today wasn’t in textbooks five years ago. By the time something gets formalized into a framework or published in a report, it’s already outdated.

The half-life of supply chain knowledge is shrinking. What worked in 2023 may be irrelevant in 2025. The strategy that succeeded in one region may fail in another. The technology that transformed one organization may create chaos in yours.

This reality demands a different approach to learning.

Peer learning keeps pace because it’s grounded in live experience. It’s not theory filtered through consultants or academics. It’s practitioners sharing what they’re seeing right now, in real operations, with real constraints.

The pattern is consistent

The strongest supply chain leaders don’t figure things out alone anymore. They can’t. The complexity is too high. The pace is too fast. The variables are too interconnected.

Instead, they build networks where knowledge flows continuously.

They compare notes with peers facing similar challenges. They challenge assumptions before committing to strategies. They test ideas in real time with people who understand the trade-offs. They learn from failures that never make it into case studies.

This isn’t about collecting contacts or attending events for visibility. It’s about building genuine relationships with practitioners who will share unfiltered truth.

The executive who can call a peer and ask “how did you actually handle this” has an advantage that no amount of research can replicate.

Why peer learning outperforms traditional sources

Reports and frameworks have their place. But they come with limitations that peer learning doesn’t.

Timeliness

By the time research is conducted, analyzed, written, and published, the situation has often changed. Peer conversations happen in real time. Someone facing a tariff change today can learn from someone who navigated it last month.

Context

Published insights are necessarily generalized. They have to apply broadly to justify their existence. Peer conversations can be specific. You can ask follow-up questions. You can explore the nuances that matter for your situation.

Honesty

Public-facing content tends toward success stories. Nobody publishes case studies about their failures. But failures often teach more than successes. In trusted peer relationships, people share what went wrong—and those lessons are invaluable.

Relevance

Not every insight applies to every organization. Peer networks let you find people in similar contexts: same industry, same scale, same challenges. Their experience translates more directly to your situation.

The information advantage has disappeared

Twenty years ago, access to information was a competitive advantage. The leaders who knew more could do more.

That era is over.

Everyone has access to the same reports. The same news. The same analyst perspectives. The same technology assessments. Information abundance has replaced information scarcity.

The new advantage isn’t having more information. It’s processing information faster. Learning faster. Adapting faster.

And the fastest learning happens through peer networks.

When you’re connected to practitioners who are testing ideas in real operations, you learn from their experiments without running them yourself. You see results before committing resources. You avoid mistakes others have already made.

This learning velocity compounds over time. Leaders who learn faster make better decisions. Better decisions create better outcomes. Better outcomes create more learning opportunities.

Building the network that matters

Effective peer learning doesn’t happen by accident. It requires intentional investment.

Engage actively, not passively

Showing up isn’t enough. The value comes from participation. Asking questions. Sharing experiences. Challenging ideas. The more you contribute, the more you receive.

Seek diverse perspectives

Networks limited to people exactly like you create echo chambers. The most valuable insights often come from practitioners in different industries, different regions, different functional backgrounds who face similar challenges from different angles.

Build trust through reciprocity

People share openly with those who share openly with them. If you only take from your network without contributing, relationships stay superficial. Genuine exchange requires genuine giving.

Prioritize quality over quantity

A small network of trusted peers who will tell you the truth beats a large network of acquaintances who share only polished stories. Depth matters more than breadth.

The community that accelerates learning

This is exactly what we’re building at Chain.NET.

An industry-led community where supply chain, procurement, and logistics leaders gather every week—online and offline—to share what’s actually working. To challenge assumptions. To compare notes. To learn faster, together.

Through executive forums, roundtables, masterclasses, open AMAs, and benchmark surveys, members don’t just consume content. They participate in conversations that sharpen their thinking and accelerate their learning.

The pattern we see consistently: the leaders who engage most actively are the ones who adapt fastest to changing conditions. They’re not smarter. They’re better connected.

As 2026 unfolds, the advantage won’t come from having more information. Everyone has that.

It will come from learning faster, together, with people who understand the reality of the job.

Where do you learn best? Are you plugged into peer networks that accelerate your development? What’s the most valuable insight you’ve gained from a fellow practitioner?

Share your experience in the comments—and if you’re ready to engage with a community built for peer learning, join us at Chain.NET.

The best supply chain leaders know they can’t figure it out alone.

Supply chain salaries are rising. The market is finally rewarding scarcity.

But this is not when supply chain excellence becomes automatic.

This is when it becomes expensive.

You can feel it already. The CEO wants resilience. The board wants visibility. The numbers look stable enough to relax. And the market is rewarding companies with strong supply chain leadership.

That’s exactly why 2026 is dangerous for CSCOs.

Misallocation becomes easy. When confidence rises, companies spend faster. They greenlight too many resilience initiatives. They fund every AI tool vendor pitches. They approve transformations that should demand proof. They mistake activity for supply chain performance because the mood improves.

Most CSCOs will enter 2026 thinking the job is to optimize harder.

The job is not to optimize harder. The job is to build a supply chain operating system where the organization can reallocate resources without chaos.

Read more

Nanda Kishore is a senior operations and supply chain leader with global experience across aerospace, marine, clean-tech, mining, and heavy industrial manufacturing. Having worked across Europe and Asia, he has led large-scale transformations spanning supplier development, manufacturing excellence, logistics, and customer delivery. Known for operating effectively in complex, high-pressure environments, Nanda focuses on building resilient operations, scalable supply chains, and leadership teams capable of delivering results through constant change.

How did you move into your current role? A short overview of your background and career.

I began my career in India within a Mitsubishi joint venture, where I built a strong foundation in manufacturing and operations. I then moved to Europe, working with an innovation-led technology group at TCS across the Nordics, leading large-scale transformation initiatives. That journey took me to Rolls-Royce Marine, where I built and led supplier quality and development, drove cost-excellence programs, and supported contract execution through to customer delivery. Most recently, I moved into marine electrification, helping to build sustainable supplier ecosystems and global logistics capabilities for emerging technologies.

What is your current role and your main responsibilities?

I currently work in a senior operations and supply chain leadership capacity, supporting complex industrial and technology-driven environments. My focus is on stabilizing delivery, developing resilient supplier ecosystems, strengthening execution across manufacturing and logistics, and supporting scale-up and transformation initiatives. A key part of my role is bridging strategy and execution, working closely with engineering, quality, and commercial teams to ensure decisions translate into real-world performance. I also spend significant time mentoring leaders and building capability so operational discipline keeps pace with innovation.

What does a typical workday look like for you? Any morning routine you follow?

I start most days with stretching and yoga to reset both physically and mentally. Beyond that, there is rarely a typical day. My work spans multiple time zones, so meetings can happen early in the morning or late in the evening. The focus shifts daily between problem-solving, decision-making, and aligning teams across functions. One constant is learning. I make time every day to read, reflect, and stay current on industry, technology, and leadership topics.

What lessons did you take from the pandemic? What positive changes came out of it?

The pandemic was one of the most demanding periods of my career. I was leading manufacturing programs at Rolls-Royce Bergen Engines while navigating shifting health regulations, uneven global impacts, and very different stakeholder expectations across regions. Decisions often had to be made with incomplete information. On a personal level, I also experienced loss, which brought perspective and humility. Professionally, the period accelerated digital adoption, remote collaboration, and outcome-focused leadership. It reinforced that trust, clarity, and adaptability matter far more than control.

What are the biggest challenges in your current role? How do you address them?

One of the biggest challenges is managing volatility between demand commitments and supply reality. Markets move fast, while forecasts rarely align with actual timing. My role is to balance demand, supply planning, and supplier economics so trust and pricing are preserved. Global logistics is another critical area. I addressed this by implementing multimodal logistics partners supported by live dashboards, enabling transparency and proactive communication. In parallel, I focus on tight cross-functional alignment, especially with engineering, so technology, operations, and supply decisions move together rather than in silos.

Which tools or technologies are you most excited about right now?

I am particularly excited about the rapid maturation of AI in operational and supply chain environments. I have tested AI for logistics optimization and am currently involved with a startup applying AI to day-to-day procurement execution, automating purchase-order follow-ups, prioritization, and exception handling. What is powerful is the ability to connect data across planning, sourcing, logistics, and operations in near real time. When technology improves speed, transparency, and decision quality, it fundamentally changes how teams operate and scale.

How do you integrate sustainability or ethical practices into your operations?

For me, ethics and sustainability are not separate checklists. They are embedded in how operations actually run, from supplier selection and onboarding to performance management and workplace design. Culture drives behavior across the value chain. Suppliers and partners tend to mirror the standards and pressure they experience from the organization. Transparency, fairness, and clarity under pressure matter. When internal teams and external partners are treated as true extensions of the business, resilience, trust, and long-term performance follow naturally.

How do you stay informed about new trends and technologies in supply chain?

I stay current through a mix of structured learning and real-world exposure. I read daily to track technology, supply chain, and geopolitical developments. I participate in webinars and expert discussions, not just to listen, but to challenge my own thinking. Beyond content, I value conversations with operators, founders, and peers. These discussions help distinguish what is truly changing from what is simply being talked about.

Which skills matter most for supply chain leaders today? How do you develop them?

The most critical skill is collaboration supported by clear, honest communication. In complex organizations, influence is built less through authority and more through alignment and trust. Effective collaboration requires meaningful delegation so teams feel ownership, not instruction. Empathy plays an important role here. When people feel heard and trusted, execution improves naturally.

Which trends will most impact the profession in the coming years?

The most important capability for professionals today is the ability to continuously learn and unlearn. Technology, operating models, and expectations are evolving faster each year. Approaches that worked well in the past can quickly become constraints. Adaptability is no longer optional, it is a leadership requirement.

What advice would you share with someone starting a career in supply chain?

Supply chain, and life, are rarely linear. There is no single formula for success. You have to find your own way through complexity, uncertainty, and pressure. There will be moments when decisions are questioned and outcomes are unclear. What matters is passion for the work, curiosity to keep learning, and perseverance to stay the course. Success is not about perfection. It is about resilience and commitment over time.

Nanda Kishore, Senior Operations & Supply Chain Leader
LinkedIn: https://www.linkedin.com/in/nandakishore5750/
Chain.NET profile: https://www.chain.net/u/981f30db

Nanda, along with many other supply chain leaders, actively participates in the regular events and discussions organized by GSCC. Explore upcoming sessions on the events calendar: www.chain.net/c/events

Join our global community on Chain.NET and become a GSCC member to access expert-led events, reports, replays, and professional groups: www.chain.net

Last December, Triumph, the German lingerie brand, closed its China operations after 31 years. The company entered in 1994 as one of the first Western brands to establish a foothold. For generations of Chinese women aged 40 to 60, Triumph became iconic. Now it joins a growing list of Western brands retreating from the market.

The easy explanation blames trade wars and geopolitical tensions. Executives on the ground tell a different story.

“Trade wars are not the cause,” wrote Emmanuel Hemmerlé, co-founder and managing partner at EH and a long-time China business advisor. “Business dynamics are: declining market share, falling sales, weak profitability, and investment demands HQs can no longer support.”

His assessment triggered a wave of responses from executives, consultants, and China market veterans. The consensus: most Western brand failures in China are self-inflicted.

The Internal Constraints That Kill Western Brands

Hemmerlé identified five internal factors that undermine foreign companies in China:

Unfounded alarmism around “China risk.” Misconceptions about political and geopolitical risk mislead boardrooms. Boards make flawed strategic decisions based on fear rather than on-the-ground intelligence.

Read more

The supply chain leaders who will thrive in 2026 aren’t those with the best AI strategy or the most optimized operations.

They’re the ones who know how to genuinely connect with people.

This sounds soft. It isn’t. In a world where every competitor has access to the same technology, the same market data, and the same optimization tools, your professional network becomes your unfair advantage.

Let me show you why this matters more now than ever before.

The shift no one saw coming

Throughout supply chain history, competitive advantage has taken different forms.

In the efficiency era, success went to leaders who could produce more, faster, and cheaper. Cost optimization was king.

In the information era, data became the differentiator. Success went to those who could gather intelligence and use it strategically.

Both still matter. But something fundamental is changing.

We’re entering the connection economy.

Here’s the reality: we’re drowning in information. Every supply chain professional can access the same market reports, benchmark data, and technology assessments. AI tools are commoditizing analysis that once required expensive consultants.

When everyone has the same information, the same tools, and similar capabilities, what’s left to make you stand out?

The answer is deceptively simple: human connection.

The executives who succeed aren’t just those who know the most. They’re those who know the right people. Who can pick up the phone during a crisis and get answers. Who have built trust with peers who will share what’s actually working, not just what looks good in a case study.

What connection actually means for supply chain leaders

Connection in supply chain isn’t networking theater. It isn’t collecting LinkedIn contacts or attending conferences to be seen.

It’s intentional relationship building that creates tangible value.

Access to unfiltered intelligence

The most valuable insights never appear in industry reports. They circulate in private conversations between practitioners who trust each other. The real story behind a technology implementation. The supplier everyone should avoid. The strategy that actually worked versus the one that got presented at the conference.

This intelligence flows through relationships, not subscriptions.

Faster problem-solving under pressure

When disruption hits, connected leaders have options. They can reach peers who faced similar challenges and learn what worked. They can tap supplier relationships built on trust rather than just contracts. They can mobilize resources through networks that respond because of relationship equity, not just commercial obligation.

Isolated leaders face every crisis alone.

Career resilience and opportunity

The supply chain talent market is competitive. The leaders who advance aren’t always those with the best credentials. They’re often those with the strongest reputations within professional communities. People who are known, trusted, and recommended when opportunities arise.

Your network is your career insurance.

Why 2026 changes everything

Three shifts are accelerating the importance of connection for supply chain leaders.

The talent challenge is intensifying

Organizations everywhere struggle to attract and retain supply chain talent. The leaders who succeed connect with their teams as humans, not just resources. They create environments where people feel valued and part of something meaningful.

But they also connect externally. They know where talent exists. They have relationships that make recruiting conversations warm rather than cold. They’ve built reputations that attract candidates who want to work with them specifically.

AI is commoditizing individual expertise

When AI can analyze data, generate reports, and recommend actions, individual knowledge becomes less differentiating. What AI cannot replicate is the trust network that gives you access to information and opportunities others don’t have.

Your relationships become more valuable as your analytical tasks become more automated.

Uncertainty demands trusted advisors

We’re operating in volatile conditions. Tariffs shift. Regulations evolve. Disruptions cascade unpredictably. In this environment, leaders need peers they trust. People who will tell them the truth, share their own struggles honestly, and provide perspective that cuts through noise.

These relationships don’t form during crises. They’re built before you need them.

The questions that matter

As you look toward 2026, ask yourself honestly:

Do you have peers you can call when facing a challenge you’ve never seen before? People who will give you their real perspective, not polished advice?

Are you known in your industry? When opportunities circulate through professional networks, does your name come up?

Do you invest in relationships proactively? Or do you only reach out when you need something?

Have you built trust with people outside your immediate organization? Suppliers, customers, peers at other companies who see you as a genuine connection rather than a transactional contact?

Can you mobilize support quickly? When you need help, do people respond?

Building the network that matters

Yes, you still need operational excellence. Smart strategy. Quality execution. Competitive performance.

But in 2026, those are table stakes.

The supply chain leaders who will succeed are those who remember that business is ultimately about people connecting with people. They invest in relationships before they need them. They show up consistently for their professional community. They give as much as they take.

This is exactly what we’re building at Chain.NET: an industry-led community of supply chain, procurement, and logistics leaders who gather every week, both online and offline. Not for networking theater. For genuine connection with peers who face the same challenges, share real insights, and support each other’s success.

Because in the connection economy, isolated excellence isn’t enough. You need a network that amplifies your capabilities and creates opportunities you couldn’t access alone.

The question isn’t whether connection matters.

It’s whether you’re investing in it before you desperately need it.

We want to hear from you. How important has your professional network been to your supply chain career? What’s the most valuable connection you’ve made, and how did it change your trajectory? Are you investing enough in relationships, or do you find yourself too buried in operations to connect? Share your thoughts and experiences in the comments. The best communities are built by practitioners who engage honestly about what works.

For decades, supply chain was underpaid.

But 2026 will be a breakthrough year for supply chain professionals.

This is not a feel-good moment. It’s a structural reset in how companies value supply chain talent, especially the CSCO office. The most acute shortages sit in middle management and transformation leadership roles, where fewer ready successors are available as experienced leaders retire.

When companies struggle to fill director and CSCO positions - roles that directly impact business resilience—that’s not a staffing problem. That’s a leverage moment.

The real problem wasn’t pay. It was pipeline collapse.

Supply chain salaries are expected to climb as the need for logistics, procurement, and supply chain analysis experts grows. But this isn’t generosity. It’s desperation.

Supply chain roles have grown 22% year-over-year since 2020, with demand for supply chain talent continuing to outpace supply. Yet the talent pipeline has quietly collapsed.

Read more

A major automotive supplier deployed an AI agent to monitor supplier risk. The system worked. It flagged financial instability, quality issues, and geopolitical exposure across their vendor network. Stakeholders were satisfied. The deployment became a proof of concept.

Six months later, the same organization tried to extend that agent to procurement processes. They wanted it to influence supplier selection, contract terms, and sourcing decisions. The request seemed logical. One agent. One mission. Broader scope.

What they discovered was this: The agent that worked for risk monitoring couldn’t work for procurement without fundamental redesign. The logic was channel-specific. The integrations were locked to one workflow. The governance structure assumed a single, isolated use case.

Expanding the agent required rebuilding half the system.

This is the moment most supply chain leaders discover a costly truth: They didn’t fail to adopt AI. They failed to adopt it with an operating model in mind.

The Seductive Power of Single-Purpose Success

Supply chain teams are under pressure to prove AI value fast. So they start narrow. One problem. One team. One workflow. This approach is not naive. It’s pragmatic.

A procurement director might launch an agent to automate invoice matching. It cuts processing time from days to hours. It reduces errors. It delivers measurable ROI in 90 days. The project is labeled a success.

What rarely gets scrutinized is whether that agent was built to work beyond invoice matching.

When the same organization later wants to extend AI to purchase order generation, contract compliance checking, or supplier performance evaluation, the cracks appear. Each extension requires new integrations. Each new use case requires separate logic. Each channel requires its own governance structure.

Progress that seemed inevitable hits a wall.

Why Channel-First Thinking Fails Supply Chains

Supply chain workflows are deeply interconnected. A sourcing decision influences inventory levels. Inventory levels affect logistics planning. Logistics planning shapes supplier requirements. Supplier requirements flow back to sourcing.

Most organizations implement AI agents for isolated tasks within these workflows. An agent for demand forecasting. A separate agent for inventory optimization. Another for supplier evaluation. They are built independently, integrated loosely, if at all.

This fragmentation creates cascading problems.

When demand forecasting agents make predictions, inventory agents don’t automatically adjust. When supplier risk changes, sourcing agents don’t recalibrate. The organization ends up with multiple AI systems that don’t speak to each other, duplicating analysis and creating conflicts in decision-making.

The operational friction is invisible at first. It becomes obvious only when leaders expect these agents to coordinate across the supply chain. Then teams discover the agents were never designed to work together.

From Isolated Success to Fragmented Risk

The consequences compound in three ways.

First, governance becomes harder instead of easier. Different agents follow different approval rules. Risk thresholds differ. Escalation pathways conflict. A sourcing agent might recommend a supplier that the risk agent has flagged. The organization has no coherent system to resolve that conflict.

Second, visibility disappears. When agents operate in isolation, no single dashboard shows how AI is affecting supply chain decisions. A CSCO can’t easily answer the question: “Where is AI actively reshaping our operations and what trade-offs are we making?” That lack of visibility creates risk in regulated environments.

Third, scaling becomes exponentially expensive. Each new use case requires new integrations. Each new channel requires separate logic. What started as a one-agent deployment becomes a constellation of disconnected systems, each requiring its own maintenance, tuning, and governance.

The Omnichannel Architecture That Works

A different approach starts with architectural foundations, not channel coverage.

Instead of asking “Where is our biggest problem right now?” the question becomes “How do we build AI logic that can be reused across multiple supply chain workflows?”

In this model, the core agent—its workflows, decision logic, integrations, and guardrails—sits at the center. Individual use cases become applications of that shared intelligence. Sourcing agents, procurement agents, logistics agents, and inventory agents all draw from the same underlying logic about supplier performance, cost, risk, and compliance.

This doesn’t require launching everywhere at once. It requires choosing foundations that don’t limit future growth.

A procurement team can still start with invoice matching. But the system is built so that the invoice matching logic, supplier data integrations, and approval workflows can be extended to RFQ automation, contract evaluation, and supplier performance management without fundamental redesign.

What This Means for Procurement and Logistics Leaders

For CSCOs and procurement directors evaluating AI platforms in 2026, the distinction is critical. Ask vendors: Can your system support my first use case AND scale to cover my full procurement lifecycle?

More specifically:

• Is the core intelligence (workflows, business rules, integrations) reusable across channels, or is it locked to one use case?

• When I add a second procurement workflow, do I recreate logic or reuse it?

• How does governance scale? Can one policy framework cover multiple agents, or do I manage separate governance structures?

• What’s the actual cost of extending from one use case to three? From three to ten?

The vendors with the clearest answers are the ones thinking architecturally, not tactically.

The Real Cost of Ignoring Scale

Early AI wins are seductive because they obscure structural problems. A successful invoice-matching agent looks like progress. It is progress. But if that agent can’t evolve into a broader procurement intelligence system, you’ve optimized for short-term success at the cost of long-term agility.

Months later, when the business demands that AI influence supplier selection or logistics planning, your team faces a choice. Rebuild the system (expensive, time-consuming, high-risk). Or operate with fragmented agents (expensive, operationally complex, governance nightmare).

Neither option was inevitable. Both were the predictable result of early choices made for speed rather than scale.

Start Where You Must. Build for Where You’re Going.

The organizations that will win with supply chain AI are not the ones that deploy agents fastest. They’re the ones that deploy agents smart.

They solve their most pressing problem first. They prove value quickly. But they do it with architectural choices that don’t trap them later.

When expansion becomes necessary—and it almost always does—they can move quickly. They reuse logic. They extend workflows. They scale governance. Progress accelerates instead of decelerating.

That difference is entirely set by decisions made in week one of the project.

What’s your AI scaling challenge?

Are you scaling a successful agent and hitting unexpected friction? Have you deployed multiple agents that don’t talk to each other? What would change if you rebuilt your AI strategy with omnichannel architecture from the start?

Share your experience in the comments. Your story could help peers avoid the same costly path.

Join the Chain.NET community for strategic discussions on supply chain AI implementation, vendor evaluation, and scaling strategies. We host regular forums where CSCOs and procurement directors share real experiences scaling AI agents, navigating vendor platforms, and building architecture that grows with their business. Learn from peers solving these problems now. Visit www.chain.net and check our events calendar at www.chain.net/c/events for upcoming masterclasses on AI strategy and supply chain technology architecture.

A procurement manager spends three hours every Friday matching purchase orders to invoices, cross-checking against supplier contracts, and flagging compliance issues. A logistics coordinator manually tracks shipments across three systems, consolidates data into spreadsheets, and sends status reports.

These are perfect jobs for Claude Cowork.

I took Claude’s new desktop tool and configured it as a member of a supply chain team. I gave it a folder with supplier data, contract files, and procurement records. Then I asked it to run a complete procurement reconciliation.

It ingested new supplier contracts. Compared spend against terms. Flagged risk mismatches. Wrote a CSCO-ready briefing. And it stored everything it learned so next month’s run is faster and more accurate.

The entire setup took less than 15 minutes. No code. Just a folder and clear instructions.

Here’s exactly how to do it for your supply chain.

Read more

A recent benchmark survey reveals a widening divide between logistics leaders and laggards. The difference? Automation, AI adoption, and viewing transportation as a strategic weapon rather than a necessary cost.

Transportation management stands at a crossroads. On one side sit the 17% of companies that have fully automated their operations, embrace AI-driven insights, and view logistics as a competitive weapon. On the other side, 37% remain stuck in heavily manual processes, treating transportation as a necessary evil while watching competitors pull ahead.

The 9th Annual Global Transportation Management Benchmark Survey from Descartes, conducted with 616 transportation professionals across North America and Europe, reveals this stark divide. The research shows that companies treating transportation strategically aren’t just working smarter. They’re growing faster, investing more in technology, and positioning themselves for long-term success while others struggle to keep pace.

The Strategic Shift Nobody Saw Coming

Transportation’s evolution from back-office function to strategic driver accelerated dramatically in 2025. A record 81% of respondents now view transportation as either a customer service differentiator or competitive weapon. This represents an 11% jump from 2024, when only 70% held this view.

The shift matters because it correlates directly with financial performance. Among companies viewing transportation as a competitive weapon, 79% report industry-leading or better-than-average financial positioning. These same companies expect revenue growth of at least 5% at rates 10% higher than organizations treating transportation as basic service.

Business growth now drives transportation management system expansion more than cost reduction. Some 48% of respondents cite growth as their primary driver for TMS investment, up from third place in 2024. Improved customer service follows at 46%, with cost reduction pressure at 38%.

This represents a fundamental mindset change. Transportation leaders no longer ask how to cut costs. They ask how transportation can enable growth, improve customer experience, and create competitive advantage.

The Automation Divide

The survey exposes a troubling reality. Only 17% of organizations have achieved full automation with AI-driven insights. Another 46% remain mostly or partially automated but heavily reliant on manual intervention. The remaining 37% operate with minimal automation and mostly manual processes.

This automation gap correlates directly with financial performance. Among industry-leading financial performers, 51% report full automation. That figure drops to 8% for middle-of-the-pack companies and just 5% for below-average performers.

The pattern repeats across multiple dimensions. Companies with strong financial positioning invest more in technology, adopt AI faster, share data more broadly, and treat transportation strategically. Weaker performers cut costs, resist technology investment, keep data siloed, and view transportation as a necessary expense to minimize.

One global manufacturing executive captured the challenge. “We realized procurement had outgrown its traditional role. Today my team is directly involved in strategic planning, market forecasting, and revenue growth initiatives. We’re not reporting to the board. We’re sitting at the table with them.”

The question facing most organizations isn’t whether to automate. It’s how quickly they can close the gap before it becomes unbridgeable.

The AI Revolution Takes Hold

Generative AI adoption has reached near-universal levels. Some 96% of respondents now use AI in some capacity within their transportation operations. Only 4% report no AI usage, and these holdouts are significantly more likely to view transportation as a necessary evil and expect limited growth.

The top AI use cases reveal where organizations see immediate value. Data entry leads at 41%, followed by route and load optimization at 39%. AI-driven vehicle maintenance predictions, automated load matching, customer service chatbots, and dynamic pricing optimization round out the top applications.

Companies with industry-leading financial performance adopt AI across categories at double-digit higher rates than below-average performers. The one exception is driver safety, where adoption rates remain more consistent regardless of financial positioning.

Shippers show 46% adoption of AI for data entry compared to 37% for logistics service providers. This suggests shippers face greater administrative burdens from managing multiple carriers and modes.

The divide between AI adopters and non-adopters extends beyond technology. Non-adopters are more likely to view transportation management as a necessary evil rather than strategic function. They expect lower growth rates. They invest less in technology. They operate more manually.

AI adoption has become a proxy for strategic orientation. Organizations embracing AI signal they view transportation as a competitive weapon worthy of investment. Those resisting signal the opposite.

Fraud and Theft Move Center Stage

A new concern emerged in the 2025 survey. Carrier monitoring for insurance, safety, and fraud jumped into the top three most-needed TMS capabilities at 30% selection rate. Carrier vetting and identity validation, new categories this year, were selected by 25% of respondents.

The concern is more pronounced in North America, where 33% selected carrier monitoring compared to 23% in Europe. This 10-percentage-point gap reflects the greater prevalence of freight fraud and cargo theft in North American markets.

Carrier identity validation and fraud prevention capabilities that barely registered in previous years now command significant attention. The rise reflects increased sophistication of freight fraud schemes, growing cargo theft, and financial pressure forcing some carriers to cut corners on insurance and safety compliance.

Transportation professionals no longer assume carrier legitimacy. They verify insurance coverage, validate carrier identity, monitor safety scores, and implement fraud detection systems. The trust-but-verify approach of the past has given way to verify-then-trust.

Investment Patterns Tell the Story

Technology investment intentions reveal which companies are positioning for growth versus managing decline. Overall, 80% of respondents plan to increase transportation management IT spend over the next two years. Some 23% plan increases of 5% or more.

The distribution of investment varies dramatically by financial performance. Among industry-leading financial performers, 84% will increase TM IT spend. That figure drops to 45% for companies with below-average financial positioning.

This creates a reinforcing cycle. Strong performers invest in technology, which drives automation and AI adoption, which improves performance, which generates resources for further investment. Weak performers cut spending, fall further behind in automation, see performance deteriorate, and have fewer resources to invest.

The gap compounds over time. Organizations that invested in transportation technology five years ago now operate with significant advantages in efficiency, visibility, and customer service. Those that delayed investment face the daunting challenge of closing a widening gap while competing against better-equipped rivals.

The Visibility Imperative

For the eighth consecutive year, shipment visibility topped the list of most-needed TMS capabilities at 40% selection rate. Carrier monitoring debuted in second place at 30%, followed by performance management and business intelligence dashboards at 35%.

The methods companies use to achieve visibility reveal the maturity gap. Real-time GPS and ELD tracking leads at 60%, up 8% from 2024. Carrier and broker shipment status portals follow at 50%. Disturbingly, 43% still rely on spreadsheets and email updates after shipment delivery. Some still call carriers and brokers for status updates.

Companies viewing transportation as a competitive weapon use real-time GPS/ELD tracking at 68% rates compared to 52% for those viewing transportation as basic service or necessary evil. The visibility gap mirrors the strategic gap.

Less-than-truckload emerged as the mode needing the most visibility improvement at 38%, displacing truckload at 31%. Ocean freight trails distantly at 19%. North American shippers prioritize truckload visibility improvement at 43% compared to 32% for European shippers, reflecting different freight patterns and infrastructure maturity.

The Road Ahead

The survey reveals an industry transitioning from tactical cost management to strategic value creation. This transition shows up in how companies measure transportation value, where they share data, what drives TMS expansion, and how they prepare for industry changes.

Cost per shipment remains the top value measurement at 61%, but contribution to revenue growth follows closely at 51%. Service level targets, contribution to competitive differentiation, and contribution to ESG goals round out how leading organizations measure transportation value.

Companies viewing transportation as a competitive weapon measure contribution to revenue growth at 60% rates compared to just 38% for those viewing transportation as a necessary evil. The measurement framework reflects strategic orientation.

Transportation data sharing patterns reveal the shift toward connected ecosystems. Supply chain operations lead at 54% for where transportation information creates value, followed by carriers at 52% and warehousing and distribution operations at 49%. All categories showed increases year over year, indicating information sharing continues to expand.

The growing recognition that transportation data has value beyond the transportation department signals the function’s elevation. When sales teams use transportation data to promise delivery dates, when customer service uses it to respond to inquiries, and when supply chain operations use it for planning, transportation becomes integral to business operations rather than a supporting function.

Key Takeaways

Transportation management is experiencing a strategic elevation that correlates directly with business performance. Companies viewing transportation as a competitive weapon report better financial positioning, higher growth expectations, greater technology investment, and more advanced automation than those treating it as a cost to minimize.

The automation gap represents the defining challenge. Only 17% of organizations have achieved full automation, while 37% remain heavily manual. This gap widens between strong and weak financial performers, creating a reinforcing cycle where leaders pull further ahead while laggards fall further behind.

AI adoption has reached 96% of organizations, with data entry and route optimization leading use cases. Companies not using AI are significantly more likely to view transportation as a necessary evil, expect limited growth, and resist technology investment. AI adoption has become a strategic signal.

Fraud and theft prevention emerged as a new priority, with carrier monitoring and identity validation jumping into top TMS capability needs. North American companies show 7-10% higher concern than European counterparts, reflecting regional differences in fraud prevalence.

How automated is your transportation operation? Are you measuring transportation value through cost per shipment or contribution to revenue growth? What’s preventing your organization from treating transportation as a competitive weapon rather than a necessary cost? Share your perspective in the comments.

The global road transport market is entering 2026 under pressure from multiple directions. Capacity shortages in Europe have reached critical levels. Toll increases are rolling out across the continent. Extreme weather is disrupting networks with increasing frequency. And regulatory tightening in Asia and the Middle East is adding layers of complexity for cross-border operations.

DSV’s latest Road Transport Market Update provides a comprehensive view of these dynamics across four regions: Europe, the Americas, Asia-Pacific, and the Middle East and Africa. The report draws on data from sources including Eurostat, the European Central Bank, the IMF, and industry indices to paint a picture of a market where shippers face rising costs and shrinking options.

Europe: Capacity Crunch Intensifies

The numbers in Europe tell a stark story. The Transporeon Capacity Index dropped to 93.6 points in December 2025, marking a 5.5% decline year over year. By January 2026, it fell further to 90.4 points. This represents a severe capacity shortage that is forcing shippers to compete for available trucks.

Rates reflect this imbalance. The Spot Index rose to 146.1 points in December, up 4.3% from the previous year. Contract rates followed a similar trajectory, reaching 130.7 points with a 4.1% annual increase.

Economic conditions vary sharply across the region. Large Western economies including Germany, France, Italy, Spain, and the UK are expected to grow modestly, between 0% and 1%, with no real recovery from 2023-24 levels in sight. Eastern and Southeast Europe tells a different story. Poland, Bulgaria, the Baltics, and the Balkan states are expected to maintain growth above 2% through 2026-2027. Turkey projects growth exceeding 3.5%.

Labor costs continue rising. Wages grew by 3.3% in the Euro area and 3.7% across all EU countries when comparing Q3 2025 to Q3 2024. These increases, driven partly by inflation that reached higher levels in previous years, are now baked into transport pricing.

A wave of toll increases is compounding these cost pressures. Austria raised truck tolls in January 2026. Belgium increased Wallonia tolls by nearly 2% based on the index model. The Czech Republic implemented motorway toll increases of 0.7% to 1.5%, with Class I road tolls jumping 10.2% to 41.8%. France introduced network-dependent increases ranging from 0.82% to 0.95%. Poland added vehicle class-dependent increases of 4% to 6.6%.

More changes are coming. In March 2026, EU member states must introduce additional charges for air pollution caused by traffic. The Netherlands will launch distance-based truck tolling in June 2026, applying to highways and selected regional roads with rates varying by emission class.

Americas: Trade Uncertainty Clouds the Outlook

The U.S. economy remains sluggish but not recessive. GDP growth appeared solid in 2025, though the figures were distorted by volatile trade flows and tariff impacts.

Inflation held near 2.7% in December, still above the Federal Reserve’s target but not reaccelerating. Core inflation, excluding energy, food, alcohol, and tobacco, ran at approximately 2.7% year over year in the U.S., 2.5% in Canada, and 4.3% in Mexico.

Trade policy uncertainty has driven unusual swings in imports and exports, complicating historical comparisons and business planning. The labor market shows signs of stagnation. Unemployment dipped to 4.4%, but job growth slowed sharply, creating what analysts call a “low hire, low fire” environment.

Crude oil production is expected to remain close to 2025 averages on an annual basis in 2026 before falling by 340,000 barrels per day in 2027. Despite 13% fewer drilling rigs at the end of 2025 compared to the beginning of the year, productivity gains kept production at record highs. Over the next two years, sustained lower crude oil prices are expected as drilling and completion activity pulls back.

Consumer spending outperformed expectations during the holiday season, driving strong retail sales and rapid inventory drawdowns. The overall macro outlook tilts modestly optimistic, though policy uncertainty remains a key headwind.

Asia-Pacific: Regulations Tighten

GDP growth across Asia-Pacific is moderating, easing from approximately 4.5% in 2024-25 to around 4.1% in 2026. Growth remains uneven. India, Vietnam, and the Philippines are outperforming, while North Asia and Singapore see slower momentum.

Inflation has cooled but not normalized. Fuel, labor, compliance, and financing costs remain structurally higher than pre-2020 levels. This creates a baseline cost increase that is unlikely to reverse.

Malaysia has tightened enforcement on lorry overloading, introducing zero tolerance with nationwide inspections and stricter weight-limit checks. Penalties have increased significantly, including heavy fines, vehicle seizure, and license suspension for repeat offenders. Stricter load planning and documentation are now essential, with enforcement expected to remain sustained rather than temporary.

The Thailand-Cambodia border continues to experience policy-driven disruption, with geopolitical risk persisting. The November 2025 Thailand floods caused short-term localized disruption, though operations have normalized. Intra-Asia trucking shows stable lead times, but they remain lane-specific, and buffers are increasingly used as a hedge against uncertainty.

Middle East and Africa: Divergent Fortunes

Growth remains uneven across the region. GCC economies are outperforming South Africa despite a gradual recovery there. The UAE projects growth of 4% to 5%. Saudi Arabia expects 2.1% to 2.0%. South Africa forecasts approximately 1.7% in 2025, rising to 2% in 2026.

Regulatory changes are increasing operational complexity and cost pressures, particularly for cross-border road freight. Namibia will require a Trader Identification Number for all customs transactions starting April 2026, increasing administrative compliance burdens. Saudi Arabia has implemented market-linked diesel pricing and Saudization requirements, raising operating costs and creating labor constraints. South Africa has intensified permit and road compliance enforcement, adding security and operating costs for freight operators.

Demand remains strong in construction, retail, e-commerce, and healthcare distribution, particularly in Saudi Arabia. Specialized transport, including temperature-controlled freight, continues gaining traction across Middle East corridors. Security risks and infrastructure constraints in South Africa continue adding cost and operational complexity.

Fuel pricing across the region has largely shifted to market-linked models, resulting in ongoing cost volatility. Recent diesel price increases of approximately 8% in Saudi Arabia contrast with short-term fuel price relief announced in South Africa.

Weather Becomes a Planning Factor

Extreme weather is increasingly affecting road freight operations. Severe storms, snow, ice, and heavy rainfall in early 2026 disrupted transport flows across North America and Europe. Major hubs became harder to access. Regional networks slowed. Local deliveries and long-distance cross-border movements both experienced delays.

Climate patterns are shifting. Longer warm spells, heavier rainfall, and more frequent storms are putting extra pressure on infrastructure and increasing the risk of delays. Planning and forecasting must adapt quickly to these changing conditions. Supply chains may require more flexibility to keep goods moving when conditions change at short notice.

Key Takeaways

First, European road freight capacity has reached critically low levels. Shippers should expect continued rate pressure and should lock in contracts where possible. The combination of capacity shortage, toll increases, and labor cost growth creates a compounding effect on transport budgets.

Second, regulatory complexity is rising globally. From EU pollution charges to Malaysian overloading enforcement to Namibian customs requirements, compliance burdens are increasing. Companies operating cross-border routes need to invest in documentation, planning, and local expertise.

How is your organization adapting to these road freight market pressures? Are you seeing capacity constraints or rate increases in your key lanes? Share your experience in the comments.

Continue the discussion on Chain.NET (www.chain.net).

Arnel Gamboa serves as Vice President of Logistics at ACE Hardware Philippines, bringing more than 26 years of multi-industry experience across FMCG, retail, cold chain, agribusiness, and distribution. Known for leading nationwide networks, driving digital modernization, and building strong supply chain teams, he has become one of the region’s most respected logistics leaders. His career blends operational excellence, systems transformation, and a deep passion for elevating the Philippine supply chain.

How did you move into your current role?

I transitioned into my current role through a mix of operational experience, leadership exposure, and transformation achievements across several industries. My work in modernizing WMS platforms, leading nationwide distribution networks, and driving cost-efficient, customer-focused operations positioned me well for ACE Hardware’s needs. The company needed a leader capable of scaling operations, transitioning major DCs, and designing a long-term supply chain roadmap. The opportunity aligned with my passion for innovation, people development, and advancing Philippine supply chains.

A short overview of your background and career.

I have over 26 years of end-to-end supply chain experience across FMCG, retail, cold chain, agribusiness, 3PL/4PL, and distribution. My leadership roles in Swiftfoods, Benby Enterprises, National Book Store, and ACE Hardware allowed me to deliver major transformation projects and operational improvements. I am a Chartered Fellow of both CIPS and CILT, a Six Sigma Master Black Belt, and an active mentor in the ASEAN supply chain community. My background blends technical depth, organizational leadership, and advisory work.

What is your current role and your main responsibilities?

I oversee nationwide warehouse operations, distribution, inbound logistics, transport management, project management, returns management, and non-trade procurement. I lead the strategic planning and execution of ACE’s supply chain roadmap to ensure operational excellence, cost efficiency, and service reliability across hundreds of stores. My work spans inventory accuracy, WMS and digital capability improvements, supplier partnerships, regulatory compliance, and continuous process improvements to strengthen resilience and customer satisfaction.

What does a typical workday look like for you?

My day starts with reviewing dashboards such as DIFOT, replenishment lead times, DC performance, and order fulfillment. I connect with warehouse, transport, and planning teams to assess priorities, resolve bottlenecks, and manage service risks. The rest of the day includes strategic planning, supplier and 3PL meetings, system enhancement reviews, and cross-functional alignment. I also spend time mentoring leaders, strengthening governance routines, and monitoring transformation projects.

Any morning routine you follow?

My routine focuses on clarity and momentum. I begin by responding to emails, reviewing key operational metrics, and checking overnight service updates. I then set my top priorities before joining alignment huddles with the logistics leadership team. Personally, I take a few minutes for grounding, reflection, or a short walk to maintain calmness and energy for the day.

What lessons did you take from the pandemic?

The pandemic reinforced the importance of agility, resilience, and collaboration. It highlighted the need for real-time visibility, scenario planning, and diversified logistics networks. People leadership became critical ensuring empathy, safety, and support during high-pressure conditions. It proved that technology, digital tools, and strong supplier relationships are essential for continuity. Most importantly, it emphasized that empowered teams and adaptable systems drive long-term success.

What positive changes came out of it?

It accelerated digital transformation, improved cross-functional collaboration, and increased recognition for frontline logistics teams. It fast-tracked omnichannel readiness, strengthened WMS and inventory visibility, and encouraged organizations to redesign networks for resilience rather than cost alone. Remote coordination improved communication discipline and elevated partnerships with suppliers and 3PLs.

What are the biggest challenges in your current role?

Major challenges include balancing cost efficiency with rising service expectations, managing nationwide distribution complexity, and ensuring accurate replenishment for hundreds of stores. Unpredictable demand, capacity constraints, and the need for digital upgrades add pressure. Strengthening supplier collaboration, optimizing 3PL performance, and navigating regulatory requirements require continuous focus. Talent development and upskilling also remain essential in an increasingly digital logistics landscape.

How do you address them?

We address challenges through technology, process discipline, and strong partnerships. We leverage Blue Yonder JDA-WMS, KPI dashboards, and network modeling. We standardize processes, strengthen supplier scorecards, and reinforce governance routines across DCs and 3PLs. Capacity planning, regional hub development, and continuous improvement initiatives help resolve bottlenecks. I also invest heavily in talent development and problem-solving culture. These pillars help convert challenges into resilience and operational advantage.

Which tools or technologies excite you right now?

I’m excited about predictive analytics, advanced WMS optimization, robotic process automation, and data-driven dashboards. Our migration to JDA-WMS enables better automation and real-time visibility. We’re exploring enhanced mobility tools, upgraded scanning technologies, and potential TMS integrations. Analytics and scenario modeling strengthen forecasting, planning, and replenishment. With ACE’s growing omnichannel footprint, we are testing solutions for faster B2B, B2C, and e-commerce fulfillment.

How do you integrate sustainability or ethical practices?

We focus on route optimization, reducing empty miles, and improving load efficiency to cut fuel consumption. Regional hubs shorten delivery distances, and improved planning reduces wasteful movements. In warehouses, we pursue energy-efficient layouts, reduced scrap, and optimized handling. Supplier discussions include packaging improvement and compliance standards. Ethical practices are embedded through transparent procurement, fair supplier treatment, and strong governance frameworks.

How do you stay informed about new trends and technologies?

I stay informed through active involvement with CIPS, CILT, SCMAP, and other organizations. I participate in conferences, leadership programs, and research-driven forums. I also learn from technology partners, academic institutions, and consulting firms. Vendor discussions and industry networking help me stay ahead of emerging trends in automation, sustainability, and digital transformation.

Which skills matter most for supply chain leaders today?

Strategic thinking, analytical strength, leadership agility, and digital literacy are essential. Leaders must understand end-to-end supply chain dynamics and be able to drive transformation. Soft skills, including communication, collaboration, and people development, matter greatly. Resilience, adaptability, and integrity help leaders navigate volatile environments. Sustainability and ethical judgment are also becoming central skills.

How do you develop them?

I develop these skills through a mix of real-world challenges, continuous learning, and mentorship. Large-scale transformations and crisis situations sharpen execution and decision-making. Certifications and executive education deepen technical and strategic skills. Peer learning, councils, and cross-functional projects broaden perspective. Coaching teams strengthens communication and leadership capacity.

Which trends will most impact the profession in the coming years?

Digital transformation, predictive analytics, warehouse automation, sustainable logistics, and omnichannel fulfillment will dominate. Supply chains will become more integrated, data-driven, and visibility-focused. AI, robotics, and digital twins will enhance forecasting and scenario planning. Regulatory pressures will increase sustainability requirements. E-commerce growth will reshape distribution models, pushing networks to be faster, agile, and customer-centric.

What advice would you share with someone starting a career in supply chain?

Start by mastering the fundamentals inventory, forecasting, logistics flows, and procurement. Stay curious and embrace the complexity of supply chains. Build analytical and digital skills early. Seek mentors and join professional communities like CIPS, CILT, PISM, or SCMAP. Develop resilience, communication abilities, and a service mindset. Above all, stay adaptable. The industry evolves quickly, and those who grow with it will lead it.

Arnel Gamboa
Vice President – Logistics
LinkedIn: https://www.linkedin.com/in/arnel-gamboa-fcips-fcilt-faapm-dm-c-mphil-msc-cmc%C2%AE-mpm%C2%AE-mcips-cs-cssmbb%E2%84%A2-aprm%E2%84%A2-smac%E2%84%A2-45767316/
Chain.NET profile: https://www.chain.net/u/0f6d9aca

Arnel, along with many other supply chain leaders, participates in the regular events and discussions organized by GSCC. See the full event calendar at www.chain.net/c/events.

Join our global community on Chain.NET and become a GSCC member to access expert-led events, reports, replays, and professional groups: www.chain.net

McKinsey admitted what clients have suspected for decades. The traditional consulting model is broken.

Business Insider recently reported that 25% of McKinsey’s global fees now come from outcomes-based pricing, not billable hours. The firm is moving from advisory vendor to operating partner. Clients no longer pay for projects. They pay for results.

This shift represents more than a pricing adjustment. It signals the collapse of the time-and-materials playbook that Accenture, KPMG, PwC, Deloitte, Boston, Bain, EY and many others still rely on. For supply chain and procurement leaders facing pressure to deliver transformation results, the implications are clear.

Stop paying for advice. Start demanding accountability.

The McKinsey Model Breaks

Strategy work now represents less than 20% of McKinsey’s revenue. The rest comes from deep, multi-year AI and transformation execution. The firm gets paid only when it delivers measurable outcomes.

EY is openly considering a service-as-software model powered by AI agents. Multi-year, cross-functional transformations are pushing firms to behave more like long-term operating partners than advisory vendors.

The stakes are massive. Tens of billions in consulting revenue are tied to models that AI has made obsolete. Whoever adapts fastest wins the C-suite wallet.

Alex Richards framed the unanswered question. If outcomes drive fees, who owns the risk when AI underperforms or fails to scale?

Thomas Lund summarized the new reality. “Firms that master risk-sharing, AI-enabled delivery, and multi-year outcomes will capture the new C-suite wallet. The rest will sell PowerPoint decks.”

Why AI Changes Everything

AI exposes whether firms can actually deliver outcomes, not just decks. When execution becomes measurable, billable hours stop being the product.

Mark Anthony Brewer at Immortal Tek identified the fundamental shift. “The consulting model isn’t collapsing because of AI. It’s collapsing because AI finally exposes whether a firm can actually deliver outcomes, not just decks. When execution becomes measurable, billable hours stop being the product.”

He continued. “If firms are getting paid on results, they need AI systems that are auditable, governed, modular, and traceable, not black-box monoliths they can’t control. The real shift isn’t time versus outcomes. It’s advice versus accountability. Once AI performance is logged, versioned, and traceable, the firms that can prove their systems’ reliability win every long-term transformation deal.”

Richards agreed completely. “AI isn’t killing consulting, it’s just showing who can actually deliver. Once the work is trackable, you can’t hide behind a slide deck. It really is the shift you called out: advice to accountability. The firms that can prove their AI works in the real world are the ones that will win the long-term transformation deals.”

Dave Snowden at The Cynefin offered a different perspective. “There are two ways of looking at this. One is that AI changes the consultancy model, the other is that AI’s competence demonstrates that consultancy has, over the past few decades, impoverished itself by simply repurposing text based documents with no originality.”

The observation cuts deep. If AI can replicate most consulting deliverables, those deliverables never required human expertise in the first place.

What Supply Chain Leaders Should Demand

The shift to outcomes-based pricing creates opportunity for supply chain and procurement executives. Traditional consulting engagements deliver recommendations. Implementation responsibility falls on internal teams. When projects fail, consultants blame execution gaps. Clients absorb the cost of failure.

Outcomes-based pricing flips that dynamic. Consultants share risk. Success gets defined upfront. Payment depends on delivery.

Bryan Cassady summarized the change. “It is about time consultants are expected to deliver results instead of kilos of powerpoints.”

Gereon Hempel confirmed the pattern. “I couldn’t agree more. PowerPoint and chill times are over. I see it in my own consultancy where we’re providing solutions instead of creating a PowerPoint with tasks for our clients. All the way is the new name of the game.”

Diana Barber described what clients are rejecting. “The old Big 4 playbook, high rates, junior-heavy teams, and 1,000-slide decks, is no longer accepted by clients who need real outcomes.”

For supply chain transformation projects, this matters enormously. Warehouse automation implementations. Transportation management system deployments. Procurement technology integrations. These projects succeed or fail based on execution, not analysis.

Traditional consulting delivers analysis. Outcomes-based models deliver working systems.

The Risk Question

Veronika Bruce at Adobe partnerships raised the critical tension. “If the traditional consulting model is collapsing, it’s because outcomes-based pricing fundamentally rewrites where accountability sits. But here’s the real tension behind the trend: when fees depend on outcomes, who actually owns the outcome? Is it a failure of implementation? Internal readiness? Cross-functional adoption? Or the limitations of the tech stack itself? And even more importantly, who defines the framework that decides this? Without clear ownership across these layers, shared risk becomes a negotiation rather than a model.”

This question determines whether outcomes-based pricing creates value or creates conflict. Success requires rigorous definition upfront. What constitutes success? Over what timeline? What variables can the consultant control? What depends on client execution?

Stefano di Bartolo emphasized the challenge. “The shift to outcomes-based pricing requires contracts to rigidly define roles and risk during implementation’s unpredictable stages. As AI handles analysis, the consultant’s indispensable value concentrates on three human assets: contextual expertise spotting pitfalls via use case ownership, objective advice providing technology-agnostic solutions, and people leadership driving stakeholder adoption and coordination. Firms must now aggressively capitalize on these three assets and come up with different fee models.”

Richards agreed. “The moment you move to outcomes-based models, the contract becomes a living map of who owns what, especially when real-world variables like turnover or shifting priorities hit. AI can take over the analysis, but it can’t replace the judgment, neutrality, and people leadership needed to keep a transformation on track. Context, objective guidance, and stakeholder alignment are the three levers that actually determine whether an AI program succeeds. That’s where firms need to double down and rethink how they price.”

The Accountability Gap

Another insider identified what outcomes-based pricing actually means. “This shift feels less like the end of traditional consulting and more like an overdue reckoning with accountability. The billable hour model always insulated firms from delivery risk. Clients paid for effort, not impact. Outcomes-based pricing flips that, which is healthy, but it also raises questions about who defines success and over what timeline. Success can be both measurable and tangible. The measurable is easy, the other is less defined. Sometimes the value comes from just having a second opinion. The best models are going to be a hybrid that tie measurable outcomes with knowledge gain that inspires innovation and creative solutions.”

Matthew Waugh agreed. “If you’re brought in as a partner you should be accountable for an outcome, not just hours on a timesheet. Whether AI is part of the solution or not doesn’t change the basics. Simply telling a client what to do, or dropping in a team to deliver something, rarely stacks up in a real cost-to-value analysis. A genuine partner should accelerate the realization of value, uplift the internal team working beside them and leave sustainable capability behind once the engagement is done. That’s the model clients are demanding now and it’s great to see the C-suite shifting spend toward partners who deliver that kind of impact, AI or no AI.”

Peter Welling emphasized the core principle. “Change the model where management consultants share implementation risk and reward not just upstream concepts and models. Will sort out who can deliver real value. Don’t need AI to do that.”

What Works in Supply Chain

For supply chain and procurement transformations, several outcomes lend themselves to performance-based pricing.

Cost reduction from category optimization. Measurable. Time-bound. Directly attributable. Consultants can share upside through success fees tied to documented savings.

Inventory reduction from demand planning improvements. Measurable. Requires system implementation and process change. Success depends on both consultant execution and client adoption.

Service level improvements from network optimization. Measurable. Requires analytical work, technology deployment, and operational change management. Shared accountability works when baselines are clear.

Procurement cycle time reduction from process automation. Measurable. Requires technology selection, implementation, and user adoption. Success metrics are objective.

Theodore Krantz Jr. noted practical applications. “The contextual AI tools cover better market analysis for our space in supply chain risk than the traditional enterprise B2B analysts. There will always be a need for some strategic analysis and consultation but the AI tools do a fantastic job of fundamental industry analysis already. We use Grok for supplemental corporate development analysis.”

The technology enables new delivery models. Analysis that required weeks of consultant time now takes hours. That compression forces pricing changes. You cannot charge traditional rates for work AI completes in minutes.

The Implementation Challenge

Scott Alexander identified what changes. “The days of the multi-year, multi-million dollar transformations are a thing of the past. AI tools are taking the technical skills-for-hire out of the equation. Consulting will be more focused on the human and organizational side of client challenges.”

This creates opportunity for supply chain leaders. Traditional transformation projects included massive analysis components. Market assessments. Competitive benchmarking. Data modeling. Process mapping. AI handles most of this work now at fraction of cost and time.

What remains is the hard part. Change management. Stakeholder alignment. Cross-functional coordination. Technology integration. These human-centric challenges determine success or failure.

Consultants who master these skills create value. Those who rely on analysis become obsolete.

Ikum Kandola at TheAX.ai, who spent five years at PwC, identified the missing link. “The missing link for most consultancies is poorly managed data which is the risk for AI to underperform. Due to too much red tape, I left and created a platform for AI-productised consultancy. To offer outcome based pricing at scale consultancies need to be productising with repeatable delivery, clear benchmarking and faster time to value. By using a platform you can have your own IP and frameworks guide AI to assess, analyze and write reports along with all your data in system. McKinsey might do it in-house but boutique consultancies can’t afford the same luxuries.”

The Market Reality

Not everyone believes the shift is permanent. Rasmus Brix raised skeptical points. “I don’t believe performance based pricing will be the dominant revenue component for three simple reasons: one, it requires endless and detailed estimation of baseline what would have been the case without consulting team. Two, there’s tons of factors that a consulting team can’t control that significantly impacts value delivered. That’s a risk that has to be priced for, higher cost for client. Three, in many cases the value delivered by a consulting team is should be to upskill a team, function, or company and define an operating model that allow those skills to be deployed effectively to create value. Developing a pay for performance pricing model that measures that will take longer time than the project itself and still be wrong.”

His conclusion: “Claiming death of consulting due to AI is like claiming death of executive search because everyone is on LinkedIn so you can just go find them yourself.”

The parallel has limits. Executive search requires human judgment and relationship building that AI cannot replicate. Much of traditional consulting does not.

Ying Ying Shi at Accenture raised a practical concern. “Outcome-based pricing requires significant financial runway. Firms need the resources to wait years for results to materialize and absorb the risk of uncertain timelines. That creates an interesting challenge: if outcomes take 3 to 5 years to fully take shape, how do smaller consultancies structure deals that work for both sides? The firms that navigate this successfully will likely need to get more surgical about defining outcomes, focusing on shorter-term, measurable results they can directly influence rather than broad transformation goals that depend on countless variables.”

This creates advantage for large firms with balance sheets that can absorb multi-year payment delays. Smaller consultancies need milestone-based hybrid models that provide cash flow while maintaining outcome accountability.

What Supply Chain Leaders Should Do

Stop accepting traditional consulting engagements for transformation projects. The billable hour model creates wrong incentives. Consultants optimize for engagement duration, not delivery speed. Junior staff maximize utilization. Analysis expands to fill available time.

Demand outcome-based pricing for measurable results. Cost reduction targets. Inventory improvements. Service level increases. Cycle time reductions. These outcomes are objective and time-bound. Structure fees to reward delivery and penalize failure.

Require hybrid models for complex transformations. Blend fixed fees for defined deliverables with success fees for outcome achievement. This provides consultants with working capital while maintaining accountability for results.

Insist on capability transfer. Outcomes-based engagements should leave internal teams more capable, not more dependent. Build knowledge transfer into success criteria. Measure team capability at project end.

Define risk allocation explicitly. What can consultants control? What depends on client resources? What requires executive sponsorship? Clear contracts prevent disputes and enable genuine partnership.

Leverage AI to compress analysis phases. Do not pay traditional rates for work AI completes quickly. Redirect consultant effort to change management, stakeholder alignment, and implementation support where human expertise still matters.

The consulting industry is undergoing forced evolution. AI accelerates the exposure of firms that deliver PowerPoints instead of performance. Supply chain and procurement leaders have leverage to demand better models.

Use it. The firms that adapt will deliver more value at lower risk. The firms that cling to billable hours will price themselves into irrelevance.

The future of consulting is accountability. Supply chain transformations are too important and too expensive to fund on hope and hourly rates.

Join the conversation on consulting transformation, outcomes-based pricing, and supply chain innovation at Chain.NET, where supply chain professionals share experiences with consultant engagements, debate delivery models, and connect at events focused on holding partners accountable for results. Better consulting starts here.

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The supply chain technology market offers overwhelming choice. Infor. Kinaxis. Blue Yonder. SAP. Oracle. o9. Relex. OMP. Logility. Anaplan. Project44. Dozens more…

Every platform looks impressive. Every vendor promises transformation. Every demo showcases advanced capabilities that appear essential.

Most implementations fail anyway.

Alena Kavalchuk at MAIR Group recently outlined a practical framework for technology selection. Her approach challenges conventional wisdom. The best tool is not the one with the loudest marketing or the most advanced AI. The best tool is the one that fits your business reality.

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