Board briefings, ROI autopsies, and governance playbooks for leaders evaluating enterprise AI readiness.
Takeaway. This hub collects executive AI reports you can cite in board and leadership discussions. Start with the featured whitepaper, then use the free Fluency course if you want to practise the frameworks.
Token prices are a vendor conversation. An asset has steady demand, a fit test, and a named utilisation owner. Idle capacity with no stake is still an expense.
MIT Project NANDA (2025): 95% of custom or integrated GenAI pilots had no measurable P&L impact. A board triage on when a pilot is still an experiment.
A lab headline is not a capital process. Require independent review, a denominator, and a result that stops the spend before you fund the claim.
Most AI pilots die in the room that writes the next cheque. Write the baseline, the off-slide costs, and the owner who will defend the number before you ask for year-two funding.
A licence count is a login. Fluency is a named decision, a standard of evidence, and a review path when the model is wrong.
A payback number without a baseline, omitted costs, and a named owner is a sales slide, not a financial model. Five reading tests before procurement.
The expensive mistake is buying model access before anyone owns the decisions that output is allowed to bind. Name the owner, the evidence, and the failure path first.
A step-by-step compliance and audit architecture for C-suite leaders navigating high-risk AI classification and mandatory transparency requirements.
Published methodology in the Journal of The British Blockchain Association for evaluating token velocity, speculative drift, and incentive stability with TokenLab.