Direct answer
Compare investments using full economics, adoption, strategic fit, risk, reversibility, and accountable benefit ownership.
1. Baseline
Apply this stage to AI for CEOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Strategy and scenario intelligence
AI can widen the evidence reviewed, surface weak signals, and challenge assumptions across strategic scenarios. The CEO must keep source quality, causal logic, uncertainty, and the difference between a plausible narrative and a board-approved strategy visible.
- Which external and internal evidence anchors the scenario?
- What would falsify the thesis?
- Which decision is reversible and by when?
Failure modes to test: convincing fabricated evidence; groupthink encoded in the source set; false confidence in long-range forecasts.
2. Cost and benefit
Apply this stage to AI for CEOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Portfolio and capital allocation
AI can organize initiative evidence and model sensitivity, but capital decisions require comparable baselines, full costs, adoption, risk, strategic fit, and accountable benefit owners. A pilot count is not a portfolio result.
- What is the value mechanism and accountable owner?
- What competing investment is displaced?
- What stop, scale, or redesign evidence will be reviewed?
Failure modes to test: sunk-cost escalation; benefit double counting; underfunded controls and change.
3. Strategic option value
Apply this stage to AI for CEOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Operating-model redesign
AI becomes consequential when authority, roles, workflows, information, and incentives change. CEOs should review which decisions move, which controls remain, how work quality is measured, and whether employees and customers experience an improvement.
- Which decision rights change?
- What work disappears, changes, or is created?
- How will quality and stakeholder impact be measured?
Failure modes to test: local automation with enterprise friction; accountability gaps; work intensification.
4. Risk and dependency
Apply this stage to AI for CEOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Board governance and oversight
The CEO can give the board a decision-grade view of AI inventory, material opportunities, high-impact uses, incidents, third parties, investment, and capability. Board reporting should avoid both technical noise and empty reassurance.
- Which AI matters to strategy or risk?
- What evidence supports management's claims?
- Which decisions or incidents require board attention?
Failure modes to test: boilerplate oversight; selective success reporting; unseen concentration risk.
5. Review gates
Apply this stage to AI for CEOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Customer value and product strategy
AI can change the product, service model, cost structure, and customer relationship. The CEO should require a clear customer job, trustworthy behavior, support model, pricing logic, and evidence that the change improves value rather than only shifting effort to the customer.
- What customer problem becomes meaningfully better?
- Who bears errors and review work?
- How do trust, support, and willingness to pay change?
Failure modes to test: feature-led strategy; customer harm; margin gains that degrade retention.
Evidence packet to retain
Apply this guide as a record of judgment, not as a disposable checklist. Keep the scope, current baseline, representative scenario, participating people, source materials, decision rights, observed exceptions, outcome measures, unresolved claims, and the date on which the conclusion must be reviewed again.
- Strategy and scenario intelligence: AI can widen the evidence reviewed, surface weak signals, and challenge assumptions across strategic scenarios. The CEO must keep source quality, causal logic, uncertainty, and the difference between a plausible narrative and a board-approved strategy visible.
- Portfolio and capital allocation: AI can organize initiative evidence and model sensitivity, but capital decisions require comparable baselines, full costs, adoption, risk, strategic fit, and accountable benefit owners. A pilot count is not a portfolio result.
- Operating-model redesign: AI becomes consequential when authority, roles, workflows, information, and incentives change. CEOs should review which decisions move, which controls remain, how work quality is measured, and whether employees and customers experience an improvement.
- Board governance and oversight: The CEO can give the board a decision-grade view of AI inventory, material opportunities, high-impact uses, incidents, third parties, investment, and capability. Board reporting should avoid both technical noise and empty reassurance.
The final packet should distinguish what an official source establishes, what was observed during evaluation, what a provider or participant reported, what the reviewing team inferred, and what remains unknown. That separation is essential when the result will influence an executive, employee, customer, investor, or regulated decision.
Evaluation worksheet
| Question | Required record | Approval condition |
|---|---|---|
| What changes? | Current and proposed workflow | Boundary and owner are explicit |
| What supports the output? | Source, rights, lineage, quality, and version | Material inputs are traceable |
| Who decides? | Review, approval, exception, and escalation rights | A real person has time and authority |
| What would prove value? | Baseline, population, period, measure, and exclusions | Activity is not substituted for outcome |
| When do we stop? | Thresholds, incidents, change triggers, and fallback | Exit is practical and controlled |
Final approval gate
Approve only when the role-specific decision is clear, the evidence supports the conclusion at the claimed level, material unknowns remain visible, ownership conflicts are disclosed, and the implementation can be monitored and reversed. Reject a universal winner conclusion when the evidence supports only conditional fit.
The publication supports research and executive decision preparation. It does not provide legal, financial, accounting, employment, clinical, cybersecurity, investment, procurement, or implementation advice.