The Boardroom AI Test
AI has won the board's attention and a share of its capital. The harder test is showing which use cases create measurable value, which only raise technology consumption and which should stop. This eight-part series sets out the discipline that answers that question: nine approval controls, benefit owners and baselines, journey instrumentation, separating consumption from value, a one-page board view with forecast, evidenced and verified benefit kept apart, stop criteria agreed in advance, a transfer test for vendor claims, and a benefits ledger run on a quarterly rhythm. One fictional South African financial services group, Indigo Mutual, carries the examples, and every figure is illustrative.
8 articles
- Part 1AI's boardroom honeymoon is over. Now prove the valueAI has won the board's attention and a share of its capital. The next test is harder: showing which use cases create measurable value, which only raise technology consumption, and which should stop. Part 1 sets out the evidence that should exist before more money is approved.9 min read
- Part 2The business case was approved. Who is tracking the benefits?Forecast benefits tend to disappear between funding approval and go-live: the sponsor moves on, the baseline is never recorded and three business cases quietly claim the same saving. Part 2 shows why, and what a benefit needs to survive delivery.7 min read
- Part 3Instrument the customer journey, not only the infrastructureAI platforms report latency, availability and tokens for free. The measures a board funds, such as completion, handling time and loss avoided, only exist if someone designs them into the journey. Part 3 shows how to build both layers and join them.7 min read
- Part 4AI consumption is not AI valueMost AI dashboards count users, prompts, licences, models and tokens. Every number can be accurate and still say nothing about whether the organisation is better off. Part 4 separates consumption from value and shows what an AI usage dashboard is actually good for.6 min read
- Part 5What an AI value dashboard should show the boardA board does not need prompt counts. It needs, for every material AI use case, the investment, the value realised, how confident the organisation is in that value, the risk and the next decision. Part 5 sets out a one-page view and the evidence levels behind it.6 min read
- Part 6When should an organisation stop funding an AI use case?AI portfolios are good at starting things and poor at stopping them. A use case on 'hold' for three quarters is usually one nobody wants to end. Part 6 sets out evidence-based stop, redesign and scale criteria, and why they must be agreed before the money is spent.6 min read
- Part 7Vendor promise or competitive advantage?Cloud, software and model vendors benefit when consumption rises, and their case studies show what is possible somewhere else. Part 7 sets out a transfer test for vendor claims and a way to tell genuine differentiation from more of what every competitor can buy.6 min read
- Part 8From AI portfolio to benefits ledgerA list of AI use cases is not a portfolio, and a portfolio is not managed until each use case is tied to an objective, an owner, a baseline, evidence and a next decision. Part 8 assembles the series into a benefits ledger and the quarterly rhythm that keeps it alive.6 min read
Working through any of this in your own organisation?
These articles come out of delivery work rather than theory. If the problems in this series look familiar, a short scoping conversation is usually the quickest way to work out what is worth doing first.
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