AI-Driven Strategic Planning & Decision Making
Overview
Strategy work is changing: leaders can now test assumptions, scan markets and model options in hours rather than weeks. This course shows senior managers how to use AI responsibly at each stage of the planning cycle, from environmental scanning to scenario building and performance tracking, while keeping human judgement at the centre of every strategic decision.
Who should attend
Senior managers, strategy and planning officers, heads of departments, and members of transformation and performance teams.
Training methodology
Facilitated discussion, practical frameworks, case studies from different sectors, group exercises, short demonstrations of AI tools, and an action plan for each participant's organisation.
Objectives
By the end of this course, participants will be able to:
- Map where AI adds value across the strategic planning cycle
- Use AI tools to accelerate environmental and competitor analysis
- Build and stress-test strategic scenarios with AI support
- Apply structured decision frameworks that combine data, AI output and judgement
- Recognise the limits and risks of AI-generated insights
Course outline
Day 1AI and the Strategic Planning Cycle
- How AI is reshaping strategy work
- Strengths and blind spots of AI in planning
- Mapping AI use cases to each planning stage
- Setting ground rules for AI-assisted strategy
- Assessing your organisation's strategy process
- Case discussion: AI in a national strategy
Day 2AI-Assisted Environmental Analysis
- PESTLE and SWOT with AI support
- Market and competitor scanning
- Validating sources and checking facts
- Practical lab: building an environmental brief
- Customer and stakeholder insight from data
- Trend and weak-signal detection
Day 3Scenarios and Strategic Options
- Generating plausible futures with AI
- Testing assumptions and sensitivities
- Comparing options against criteria
- Avoiding over-reliance on a single model
- Wargaming competitor responses
- Group exercise: three futures for your sector
Day 4Decision Making with AI
- Human-in-the-loop decision frameworks
- Bias in data and in decision makers
- Explaining AI-supported decisions to stakeholders
- Case study: a high-stakes investment decision
- Group decisions and avoiding groupthink
- Documenting the rationale behind decisions
Day 5Execution, Monitoring and Action Plan
- AI for KPI tracking and early warnings
- Dynamic strategy reviews
- Governance of AI in the strategy function
- Personal 90-day action plan
- Linking strategy, budgets and initiatives
- Communicating strategy to the organisation
