Module 6: AI Strategy
Developing a comprehensive roadmap for AI implementation in your organization
Executive Summary
- An AI strategy aligns technical capabilities with business outcomes through a clear roadmap and prioritized use-case portfolio.
- Critical pillars: data infrastructure, talent development, governance & ethics, change management, and build/buy/partner decisions.
- Start with quick wins to demonstrate value while laying foundations for long-term transformative initiatives.
Key Concepts
AI strategy is a roadmap aligning AI with your business objectives. A comprehensive AI strategy includes:
- Use case portfolio: Prioritized AI applications across your organization
- Roadmap by maturity level: Staged implementation based on complexity and readiness
- Infrastructure readiness: Data, compute, and technical capabilities assessment
- Build/buy/partner decisions: Strategic choices about implementation approach
- Governance frameworks: Policies for responsible AI development and use
- Talent and change management: People strategies for AI adoption
An effective AI strategy connects technology capabilities to business outcomes while addressing organizational readiness.
Interactive Charts
This strategic roadmap shows year-by-year AI implementation milestones across different business functions.
This matrix helps prioritize AI use cases based on implementation feasibility and business value.
This diagram shows the key pillars of a comprehensive AI strategy. Select a pillar to see details.
Real-World Examples
Financial Services
Banks using NLP to review contracts and automate compliance checks, reducing review time by 60% while improving accuracy.
Retail
Retailers optimizing logistics and inventory with AI-powered demand forecasting, reducing stockouts by 30% and carrying costs by 25%.
Manufacturing
Manufacturers building AI platforms for predictive maintenance, reducing unplanned downtime by 45% and extending equipment life.
Organizational Structure
Companies creating AI Centers of Excellence and governance committees to standardize approaches and share best practices.
Discussion Prompts
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Where is your organization on the AI maturity curve? What are the gaps to address?
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What initiatives would you classify as quick wins versus long-term strategic bets?
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What risks need to be governed and by whom in your AI implementation?
Prompts for Real-World Use
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Current State Assessment: Conduct an internal survey: "Where are we using AI today and what's the impact?"
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Strategy Workshop: Hold a strategy workshop with stakeholders from data, IT, and operations teams.
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Prioritization Exercise: Prioritize potential use cases in a 2x2 matrix with your leadership team.
Call to Action
Commit to building your AI strategy deck. Include use case candidates, team readiness, and a 12-month action roadmap. Present it to your leadership or board as a strategic initiative.