AI Proof of Concept vs Production Economics
Why a successful proof of concept tells you almost nothing about whether the initiative is economically viable at scale.
A PoC proves feasibility, not viability
A proof of concept answers 'can this work?'. It does not answer 'is this worth operating at scale?'. The two questions have entirely different cost and value profiles.
What changes at production scale
Consumption costs rise with volume, integration and security requirements harden, monitoring and oversight become continuous, and reliability expectations increase sharply. Costs that were negligible in a PoC become the dominant operating expense.
What the PoC usually overstates
PoCs are run by motivated experts on curated data. Production runs across real users, messy data and imperfect adoption. Benefits observed in a PoC rarely transfer at full strength.
Bridge the gap with a production business case
Before scaling, rebuild the economics with production-level costs, realistic adoption and realization, and a three-year horizon. A PoC that looked compelling can become marginal — which is exactly what the business case is for.
Put this into practice.
Run the numbers for your own initiative in the free AI ROI calculator.