Executive Playbook: Leading AI and Agents

Synthesis: what leaders must control

The executive frame (one sentence)

• AI and agents are a change in how decisions are made and how information flows — at scale.

Four questions (repeatable)

• What decision are we changing?
• What information does it require (and what’s missing)?
• How can it fail (and how will we notice early)?
• Who is accountable (and what is the escalation path)?

Where to focus (control points)

• Incentives/intent: what is being optimised, and by whom?
• Uncertainty: thresholds and “pause when unsure”.
• Trust & data rights: asymmetry, recourse, and auditability.
• Operating model: roles, decision rights, drills, incident response.

Agents: capability with constraints

Agent rollout ladder

• Sandbox → supervised operation → constrained autonomy → broader autonomy
• Increase autonomy only when monitoring + incident response prove reliable.
• Treat each step as a control upgrade, not just a capability upgrade.

Minimum viable controls

• Audit trail: inputs, tools used, outputs, approvals.
• Blast radius limits: scopes, rate limits, sandboxes, kill switches.
• Monitoring: drift/novelty, complaints, anomalies.
• Recourse: challenge/appeal path and named accountable owner.

30/60/90 day playbook

First 30 days: choose and instrument

• Pick 1–2 high-stakes decisions and write down:
  • objective, data, failure modes, triggers, owner.
• Establish logging/audit expectations (before automation).
• Identify where data rights and privacy constraints bite.

Days 31–60: operate and drill

• Put the decision into supervised operation with clear escalation.
• Run a pre‑mortem and an incident drill.
• Define metrics for decision quality (not just model accuracy).

Days 61–90: scale with governance

• Expand scope only after controls work in practice.
• Standardise runbooks, ownership, and post‑incident upgrades.
• Organise an executive debriefs: decisions, controls, incidents, outcomes.

Myths to avoid (optional wrap)

Five AI Myths

1. AI will be the first wave of automation that adapts to us.
2. Hearsay data has significant value.
3. The big tech companies have the landscape all ‘sewn up’
4. ‘data scientists’ will come and solve all problems.
5. The normal rules of business don’t apply to AI.

Mythbusting

• Area of good data:
  • Finance

Criteria for Success

• Executive sponsorship (Office of CEO).
• Technical Expertise (Open minded expert).
• Financial buy in (CFO).
• Assimilated knownledge (CTO).

Normal Organisational Rules Apply

• AI is not magical pixie dust
• Standard organisational instincts apply
• Disruption requires agile thinking.
  • Don’t be the Grand Old Duke of York
  • Be Special Forces