AI Leadership Delivered
How to Lead with Artificial Intelligence by Applying the RapidKnowHow 9‑Step System
RapidKnowHow + ChatGPT · Simplicity Delivered
Power Statement: AI leadership isn’t hype. It’s the disciplined ability to spot high‑value opportunities, deploy human‑in‑the‑loop systems, and scale results with trust.
Vision — Define AI’s Role
Objective: Clarify how AI supports strategy and value creation.
Example: “By 2030, 40% of revenue from AI‑powered services with zero trust breaches.”
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Tool: AI Vision Canvas
- Value areas: Customer · Operations · Innovation
- Trust promise: privacy · security · fairness
- North‑star metrics
Action Trigger: Write your one‑sentence AI north star.
Assessment — AI Readiness
Objective: Evaluate data, people, process, tech, ethics.
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Tool: AI Readiness Radar (1–10)
| Dimension | Score |
|---|---|
| Data Quality & Access | — |
| Talent & Skills | — |
| Processes & Governance | — |
| Tech Stack & MLOps | — |
| Ethics & Risk | — |
Pick two lowest for a 90‑day lift.
Action Trigger: Score each dimension 1–10 this week.
Values — Ethics & Trust
Objective: Codify principles and escalation paths for responsible AI.
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Tool: AI Ethics Charter (Top 5)
- Transparency & explainability
- Fairness & bias monitoring
- Accountability (named owner)
- Privacy & data minimization
- Security by design
Action Trigger: Approve and publish the charter.
Goals — Set SMART AI Objectives
Objective: Translate vision into measurable outcomes.
Example: Automate 30% of repetitive tasks; −15% churn via AI insights; +4pp gross margin.
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Tool: AI OKR Sheet
- Objective (qualitative)
- KR1, KR2, KR3 (quantitative)
- Owner & date
Action Trigger: Lock 3 AI goals with owners.
Strategy — Choose AI Pathways
Objective: Prioritize by impact × feasibility.
Example: Customer copilot; pricing optimizer; fraud detection; document automation.
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Tool: AI Opportunity Matrix
Map ideas by Business Impact (↑) and Delivery Feasibility (↑). Pick top‑right first.
Action Trigger: Select 3 high‑impact pilots for Q1.
Action Plan — 90‑Day AI Sprint
Objective: Convert ideas into pilots fast.
Example: Launch chatbot pilot for support; run A/B; measure CSAT & handle time.
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Tool: 90‑Day AI Sprint Planner
| Week | Deliverable | Owner |
|---|---|---|
| W1 | Data audit & success metrics | Data Lead |
| W2 | Prototype / prompt flows | AI PM |
| W3 | Pilot with cohort A | Ops |
| W4 | Review: scale / kill / pivot | SteerCo |
Action Trigger: Calendar‑block the 4‑week cadence.
Execution — Human‑in‑the‑Loop (HITL)
Objective: Deploy AI with human oversight for safety and quality.
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Tool: HITL Workflow Board
- Who reviews what, when
- Escalation triggers & fallbacks
- Continuous feedback to model/prompts
Action Trigger: Assign human reviewers & thresholds.
Measurement — AI Value & Trust Scorecard
Objective: Track ROI and risk together.
Metrics: ROI, accuracy, adoption, latency, bias incidents, ROICE score.
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Tool: AI Leadership Scorecard
| Metric | Baseline | Now | Target |
|---|---|---|---|
| Task Automation (%) | 10 | 18 | 30 |
| Model Accuracy (%) | — | 86 | 90+ |
| Adoption Rate (%) | — | 54 | 75 |
| Bias Incidents (#) | — | 1 | 0 |
| ROICE Score | — | 19 | 20+ |
Action Trigger: Review monthly; scale/kill by scorecard plus risk gates.
Sustain & Share — Build AI Culture
Objective: Institutionalize learning; scale best practices and guardrails.
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Tool: AI Legacy Journal
- Playbooks (use‑cases, prompts, fallbacks)
- Training paths (beginner → expert)
- Community & office hours
Action Trigger: Publish v1 AI playbook this quarter.
Tip: Pair with a risk register and prompt library for faster rollout.