AI for Supply Chain Is Much More than Picking the Right Technology Solution 

Kevin O'Marah

September 03, 2026 • 5 min read

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Anthropic co-founder Jack Clark has predicted that by the end of 2028 there is a 60% chance that some AI systems will create their own successors with zero human involvement. A provocative idea, yes, but practically speaking, what does it mean for go/no-go decisions right now on ERP upgrades, new tool selections, or SaaS renewals?  

Zero100 research is designed for chief supply chain and operations officers making these kinds of real-world technology decisions in the age of agentic AI. Our approach is to deconstruct AI in cross-functional workflows built for operational advantage (what we call PowerThreads) while ensuring a technology architecture that keeps your options open. 

Grounded in Risk, Reward, and Reality  

Early in 2026, we asked 100 CSCO/COOs what role they saw for their existing technology stack over the next 5–10 years. Unsurprisingly, nearly all said they plan to build on what’s already there. The same survey also revealed that 83% believe more than half of their CEO’s AI commitments to the board were not realistic within stated timelines. In other words, AI expectations are out of alignment with reality.  

Investors, boards, and CEOs who feel top-down pressure to move fast on AI are often more concerned about the risk of falling behind than making a bad choice. Operators who must deliver transformed workflows with big productivity gains see the potential, but also the pitfalls. The path forward today is more confusing, and the stakes are higher.

Technology Investment Choices Are Situation Specific – What Archetype Are You?  

Over the last five years, we’ve worked with hundreds of leaders across the Zero100 community and concluded that the right decision is always: it depends.  

Large global CPG businesses with solid ERP backbones are one archetype. Fast-growing fashion brands with patchwork supply chain systems are another. Industrials with engineering PDM foundations and aftermarket supply chains are different from regional retailers with merchandising-led systems. Capacity-constrained hyper-growth startups building from scratch are different from slow-growth, cost-driven businesses.  

Potentially even more important than these externally visible archetypes are internal cultural nuances. Company risk tolerance, change appetite, and the credibility and influence of the supply chain organization with the board and executive team are all less obvious – but often critical – considerations as leaders assess what to reinvent vs iterate.  

For large companies with a web of legacy systems, making technology choices in the agentic age starts with two things:  

• the work you are trying to change, and  
• the architecture you already have.  

So, there’s rarely one technology answer. An incumbent platform may be the right foundation in one architecture. An emerging AI provider might unlock a capability elsewhere. Building a solution in one market to prove the value and leveraging a partner to help you scale may be an early accelerator. And, where operational differentiation matters, building or partnering may make more sense than buying.   

Rather than choosing from a shortlist of solution providers, this logic asks which approach, including building your own in specific areas, is best for the flexibility, security, and cost of your future tech stack, while also getting quick proof points of value creation on the workflows that matter competitively to your business now.  

Questions We Answer  

Our research explores a specific set of questions facing CSCOs today, including:   

• What are the true agentic capabilities of the existing pool of leading supply chain SaaS vendors across planning, sourcing, manufacturing, and logistics?   
• Who are the disruptive, emerging AI players, and how much of what they promise is proven in pilots and, more importantly, at scale in operations?   
• What role will frontier model providers play, if any, in how supply chain leaders build out their tech stack?  
• Where are organizations building vs buying, and what tradeoffs inform those decisions?   
• How much of the technology stack should an enterprise own, and how does that influence architecture choices and the capabilities that can be reused across the enterprise?  

Bold, but Practical   

The Zero100 approach to technology investment recommendations starts with recognizing your archetype and finding situation-specific answers to determine what technologies create value in your operating context. Our method uses purpose-built data products and primary user experience to assess the strategic and architectural fit of the technology solution providers our members care about.   

We don’t start with the assumption that incumbent or disruptor, build or buy, open or closed is inherently better. We analyze real-time market and customer sentiment, test it against enterprise evidence and architectural constraints, and form a point of view from there. It’s a flywheel that enables the profession to learn together – at speed – in a rapidly changing landscape.   

Bold thinking, grounded in pragmatism, is the way forward for supply chain leaders looking to deliver on the potential of agentic AI.   

Let’s be real about AI for supply chain.