How to Measure AI Productivity Value?

Your AI tools are saving hours. So why can't the finance team find the money?

Nine in ten companies now use AI. Most cannot show it in their profit and loss statement. The reason is not the technology. It is the measure. "Hours saved" is the weakest way to value an AI investment, and it is the one almost everyone uses.

How to Measure AI Productivity Value? replaces it with one equation and five questions that any executive can apply to any AI proposal in an afternoon:

• How big is the pool? Size the problem in money, across all ten costs, before anyone shows you a tool.
• How much can AI move? Leverage is the addressable share times the improvement on it. The demo shows only the second.
• Will people use it? Plan for 60% adoption and 80% effectiveness, and know what moves them.
• Can we capture it? Freed time becomes money through four mechanisms, each with an owner and a date.
• What does it really cost? The licence fee is the tip of the iceberg. Price the whole thing, including the cost of being wrong.

Then it shows you how to rank a portfolio by value density and ROI velocity, score any opportunity out of 100, sort proposals on a two-by-two matrix, measure honestly after launch, and put the result in the accounts in a way an audit committee will accept.

Every method is illustrated with real, sourced cases: Klarna's 700-agent assistant and its reversal, Amazon's 4,500 developer-years, JPMorgan Chase's $2 billion, the airline held to its chatbot's invented policy, the bank that cut 45 jobs and rehired them within a month, the developers who felt 20% faster and were 19% slower. Plus the author's own stories from twenty years of building software and advising companies on where AI is worth the money.

Written for chief executives, finance directors, managing directors, business owners and the managers who report to them. No technical knowledge needed. Just arithmetic, and the willingness to ask where the money is.

Includes the Toolkit: the method on one page, the AI Value Worksheet, the 100-Point Scorecard, the 10x Test, and twelve questions a board should ask about any AI proposal.