From AI Experimentation To Enterprise Value: Why CEOs Must Learn The Unit Economics Of Intelligence

Vaibhav Dani, CEO at Map Communications, specializing in enterprise AI architecture and digital transformation.

​For several years, companies have raced to prove they have an AI strategy—launching co-pilots, funding pilots, creating AI councils and embedding generative AI into workflows. That phase was necessary. It is also ending.

The question for CEOs is no longer whether the organization uses AI, but whether AI changes business economics. Does it create revenue, expand gross margin, reduce cost to serve or support growth without proportional increases in people and infrastructure? Most importantly, can those gains be seen in the financial statements?

The data suggests most companies cannot yet answer yes. McKinsey’s 2026 State of AI survey found that nearly nine in 10 organizations use AI regularly, yet only 37% attribute any EBIT impact to it and just 6% qualify as high performers. MIT’s GenAI Divide report found roughly 95% of enterprise pilots deliver little or no measurable P&L impact. Closing this adoption-to-value gap requires CEOs to understand the unit economics of intelligence.

Tokens are becoming a new enterprise variable cost.

Generative AI appears to offer nearly unlimited digital labor, but every prompt, agentic workflow, reasoning cycle and retrieval request consumes compute. Unlike traditional software, where the marginal cost of another interaction was negligible, AI introduces a meaningful variable cost.

Falling prices do not eliminate the issue. Andreessen Horowitz has documented equivalent-model inference costs falling roughly 10 times per year, yet consumption is rising faster. Gartner predicts that AI coding costs will surpass the average developer’s salary by 2028 and generative AI customer-service cost per resolution will exceed $3 by 2030. Context length, response length, reasoning steps, model choice and caching are now margin decisions.

The metric that matters is value per token.

Only a few mechanisms convert productivity into profit: