Stop Funding AI Pilots That Have No Path to Scale

A pilot should reduce uncertainty about a business decision. If it avoids real users, integrations, exceptions, support, and cost, it may prove technical possibility while proving nothing about operational value. This decision connects to Build an AI Strategy That Starts With Business Value and Turn Company Priorities Into an AI Opportunity Portfolio, which provide the strategic direction and portfolio context. Use this four-part leadership framework Scale hypothesis — State what must be true for the capability to work beyond the demonstration. Production conditions — Test representative data, real roles, integrations, exceptions, and fallback paths. Full economics — Include review, corrections, support, security, change, and exit—not only software fees. Decision gate — Choose stop, fix, repeat, or scale using thresholds written before launch. A practical decision example A service company tests an internal knowledge assistant with approved documents, ordinary users, missing-source cases, and an outage fallback. The pilot passes only if supported-answer quality, adoption, response time, operating cost, and restricted-data controls meet agreed thresholds. This is a hypothetical example; use your own baseline, constraints, and evidence. Evidence, governance, and responsible use Use the NIST AI Risk Management Framework to connect the initiative to governance, context, measurement, and ongoing management. The companion NIST AI RMF Playbook turns those functions into questions leaders can assign and review. The GAO AI Accountability Framework is useful for examining governance, data, performance, and monitoring across the system life cycle. Compare the plan with the OECD AI Principles, particularly transparency, robustness, accountability, and respect for people affected by the system. For generative AI, review the NIST Generative AI Profile and test representative cases using OpenAI’s evaluation guidance. Use the OWASP Top 10 for LLM Applications to discuss application threats before a model can access sensitive information or take actions. Check performance statements against the FTC’s guidance on AI claims, and review information handling with the FTC’s privacy and security resources. For a broader organizational management approach, study the ISO/IEC 42001 overview. Take this to the next leadership meeting Write the scale hypothesis, six production assumptions, five failure tests, cost ceiling, and decision thresholds for one active pilot. Record the owner, evidence source, decision date, and what would cause the company to stop. The goal is not to make the document look complete. The goal is to make the next decision explicit, measurable, and accountable. Continue with Build a Business Case Without Inventing AI ROI. Use Run a Quarterly AI Portfolio Review: Keep, Fix, Scale, or Stop to revisit the decision with current evidence.