AI for Executives: A Practical Briefing for Leadership Teams
The no-hype leadership guide to AI: what it genuinely does today, how to pick the first two use cases, and how to govern without stalling.
- Separate capability from demo: have your team show working internal examples, not vendor keynotes. The useful question is never 'what can AI do?' but 'where do we spend expensive human hours on work AI already does adequately?'.
- Pick two use cases by economics, not excitement: high volume × clear judgment boundaries (customer support deflection, code assistance, document review) beat moonshots for your first year.
- Fund the unglamorous foundations: data hygiene, access controls, and a short AI policy matter more than model choice — most failed rollouts die on data permissions and unclear rules, not model quality.
- Assign one accountable owner for AI outcomes per function, with a shared weekly scorecard (usage, hours saved, incidents). Diffuse 'everyone is responsible' means nobody is.
- Set the tone personally: executives who visibly use AI for their own work (briefing prep, board drafts, meeting synthesis) change company behavior faster than any mandate — and learn its limits firsthand.