What Is Changing
A proof of concept answers a bounded question: can this capability perform a defined task under defined conditions? That evidence can establish technical feasibility, expose data requirements and justify further investigation. RP01 draws a clear boundary between pilot proof and enterprise proof. Results still have to persist under normal operating conditions and repeat across the users, workflows, decisions or transactions that make the outcome material.
Why It Matters
The wider evidence shows why that boundary matters. BCG's 2024 survey of 1,000 senior executives across 59 countries placed 49% of companies at proof-of-concept stage, 22% in a group beginning to scale value and only 4% in its highest-value category. McKinsey's 2025 global survey also reported widespread AI use alongside limited enterprise-level EBIT impact from generative AI, with workflow redesign showing the strongest relationship with reported EBIT impact among the organizational attributes it tested. These findings are not causal proof, but they reinforce the need for different evidence at different stages of the investment decision.
The executive risk appears when one kind of proof is used to justify a different decision. Technical performance may show that the AI can perform the task. A scale decision also needs evidence that ownership is clear, the workflow works under normal conditions, data and integration can be repeated, users continue to adopt the capability, and costs and benefits remain credible.
The 6xD Reading
6xD's Digital Transformation 2.0 perspective treats scale as an execution test: can the enterprise operate the capability repeatedly under normal business conditions? A positive PoC result should therefore open the next evidence gate rather than settle the investment decision.
Leadership Takeaway
Executive test What has this PoC proved, what remains unproven, and what evidence would justify the next commitment of capital?
At your next AI investment review, require a clear separation between what the PoC has proved, what remains unproven and what evidence would justify the next commitment of capital. This turns a successful PoC into a disciplined funding decision rather than a blanket signal to expand.
The next time a PoC is labelled successful, ask for its proof boundary before you ask for the scale plan. If the evidence still stops at feasibility, fund the missing proof before funding wider scale.
See what your AI pilot still needs to prove before you scale
