Turn a promising model into a dependable operating capability
Supply-chain AI pilots can produce credible forecasts, recommendations and alerts. That does not prove an organisation can use their output reliably, repeatedly and economically in live operations.
Why supply-chain AI pilots fail to deliver lasting value draws on a structured analysis of 43 interviews and 154 relevant transcript sections from the Resilient Supply Chain archive. It examines what separates a promising technical demonstration from a dependable operating capability, including counterexamples and successful deployments.
Inside the brief
- Four recurring barriers involving production data, execution, decision authority and work design
- Why model performance alone is an inadequate measure of production readiness
- Practical production and investment gates for deciding when to scale, revise or stop an initiative
Complete the form below to receive your complimentary copy. We’ll email the executive brief to the address you provide.
About the research
This executive brief draws on a structured review of the Resilient Supply Chain interview archive available on 31 August 2026. The evidence set comprised 43 eligible interviews and 154 relevant transcript sections, including counterexamples, successful deployments and contradictory evidence.
The archive reflects purposively selected practitioner and provider perspectives rather than a representative industry survey. The findings identify recurring mechanisms and evidence gaps without estimating their prevalence across the wider supply-chain sector. Reported outcomes are generally contributor accounts rather than independently audited benchmarks.