GroveAI
StrategyFree Template

AI Strategy Roadmap Template

A comprehensive template for planning your organisation's AI adoption journey from current state to target vision. Designed for CTOs, heads of digital, and strategy leads who need to align AI initiatives with business objectives and secure executive buy-in.

Overview

What's included

Current state assessment framework with scoring rubric
AI vision and strategic goals worksheet
Use-case discovery and prioritisation matrix
12-month implementation timeline with milestones
Resource and capability gap analysis
Success metrics and KPI dashboard template
Executive summary one-pager for board presentation
Risk register with mitigation strategies
1

Current State Assessment

Current State Assessment

Organisation Profile

  • Organisation name:  
  • Industry:  
  • Number of employees:  
  • Annual revenue:  
  • Assessment date:  

AI Maturity Score

Rate each dimension from 1 (Ad-hoc) to 5 (Optimised):

DimensionScore (1-5)Notes
Data readiness 
Technical infrastructure 
Talent and skills 
Leadership buy-in 
Process maturity 
Governance and ethics 

Total score:   / 30

  • 6-12: Exploring — Focus on quick wins and education
  • 13-18: Experimenting — Ready for structured pilots
  • 19-24: Scaling — Expand successful pilots across the business
  • 25-30: Optimising — Focus on advanced use cases and continuous improvement

Current AI Initiatives

List any existing AI or automation projects:

InitiativeStatusOwnerBusiness Impact
 Planning / In progress / Live  
 Planning / In progress / Live  
 Planning / In progress / Live  

Key Strengths




Key Gaps




2

AI Vision & Strategic Goals

AI Vision & Strategic Goals

AI Vision Statement

Complete this sentence: "In 3 years, AI will enable our organisation to..."



Strategic Alignment

How does AI support your top 3 business priorities?

Business PriorityAI ContributionMeasurement
   
   
   

Strategic Goals (SMART Format)

Goal 1:  

  • Specific outcome:  
  • Measurable target:  
  • Timeline:  
  • Owner:  

Goal 2:  

  • Specific outcome:  
  • Measurable target:  
  • Timeline:  
  • Owner:  

Goal 3:  

  • Specific outcome:  
  • Measurable target:  
  • Timeline:  
  • Owner:  

Success Criteria

What does success look like at each stage?

  • 6 months:  
  • 12 months:  
  • 24 months:  
  • 36 months:  
3

Use-Case Prioritisation Matrix

Use-Case Prioritisation Matrix

Candidate Use Cases

List all potential AI use cases, then score each on the criteria below.

Scoring guide: 1 = Low, 2 = Medium, 3 = High

#Use CaseBusiness Impact (1-3)Feasibility (1-3)Data Readiness (1-3)Strategic Fit (1-3)Total
1      
2      
3      
4      
5      
6      

Prioritisation Quadrant

Plot use cases on this 2x2 matrix:

  • Quick wins (High impact, High feasibility): Start here
  • Strategic bets (High impact, Low feasibility): Plan for these
  • Low-hanging fruit (Low impact, High feasibility): Do if resources allow
  • Deprioritise (Low impact, Low feasibility): Revisit later

Selected Use Cases for Phase 1

  1. Use case:  

    • Expected outcome:  
    • Data requirements:  
    • Estimated effort:   weeks
    • Estimated value: £ 
  2. Use case:  

    • Expected outcome:  
    • Data requirements:  
    • Estimated effort:   weeks
    • Estimated value: £ 
4

Implementation Timeline

25 itemsto complete

12-Month Implementation Timeline

Phase 1: Foundation (Months 1-3)

  • Complete AI maturity assessment
  • Define AI vision and strategic goals
  • Identify and prioritise top 3 use cases
  • Establish AI governance committee
  • Conduct data readiness audit
  • Begin AI literacy training for leadership
  • Select technology partners / vendors

Phase 1 milestone: AI strategy approved by executive team

Phase 2: Pilot (Months 4-6)

  • Launch first AI pilot project
  • Set up data pipelines for pilot use case
  • Hire or upskill key AI roles
  • Establish model evaluation framework
  • Create AI acceptable use policy
  • Run weekly pilot retrospectives

Phase 2 milestone: First pilot delivering measurable results

Phase 3: Scale (Months 7-9)

  • Evaluate pilot results against success criteria
  • Launch second and third use cases
  • Implement MLOps / monitoring infrastructure
  • Expand AI training to wider organisation
  • Refine governance and compliance processes
  • Document lessons learned

Phase 3 milestone: Multiple AI solutions in production

Phase 4: Optimise (Months 10-12)

  • Conduct 12-month strategy review
  • Measure ROI across all initiatives
  • Identify next wave of use cases
  • Mature AI Centre of Excellence
  • Update roadmap for Year 2
  • Present results to board

Phase 4 milestone: AI strategy refresh and Year 2 roadmap approved

5

Success Metrics & KPIs

Success Metrics & KPIs

Business Impact Metrics

MetricBaseline6-Month Target12-Month TargetOwner
Revenue influenced by AI£ £ £  
Cost reduction from AI automation£ £ £  
Customer satisfaction (NPS/CSAT)    
Employee productivity gain % % % 
Time-to-market improvement  days  days  days 

Operational Metrics

MetricBaselineTargetFrequency
Number of AI models in production  Monthly
Model accuracy / performance % %Weekly
Data pipeline uptime % %Daily
AI incident count  Monthly
Mean time to resolve AI issues  hrs  hrsMonthly

Adoption Metrics

MetricBaselineTargetFrequency
Employees trained on AI  Quarterly
Teams actively using AI tools  Monthly
Internal AI use cases submitted  Quarterly
AI champion network size  Quarterly

Reporting Cadence

  • Weekly: Pilot progress, model performance
  • Monthly: Operational dashboard, risk register update
  • Quarterly: Executive summary, strategy alignment review
  • Annually: Full strategy review and refresh

Instructions

How to use this template

1

Assemble your AI strategy team

Gather 4-6 stakeholders from technology, operations, finance, and a business unit sponsor. Assign a strategy owner to drive the process.

2

Complete the current state assessment

Score your organisation across all six maturity dimensions. Be honest — an accurate baseline is more valuable than an optimistic one.

3

Define your vision and goals

Craft an AI vision that connects to existing business priorities. Set 2-3 SMART goals that you can track over 12 months.

4

Discover and prioritise use cases

Brainstorm at least 10 use cases across departments, then score them using the prioritisation matrix. Select 2-3 for Phase 1.

5

Build your implementation timeline

Populate the 12-month roadmap with specific milestones, owners, and dependencies. Ensure Phase 1 includes quick wins to build momentum.

6

Establish metrics and review cadence

Set baselines for all KPIs before launch. Schedule recurring reviews so you can course-correct early if targets are off track.

Watch Out

Common mistakes to avoid

Starting with technology instead of business problems — always lead with the use case, not the tool.
Trying to do too much at once — focus on 2-3 high-impact use cases rather than 10 underfunded experiments.
Ignoring data readiness — the best AI strategy fails without clean, accessible, well-governed data.
Treating AI strategy as a one-off document instead of a living roadmap that evolves quarterly.
Failing to secure executive sponsorship — AI initiatives without C-suite backing rarely survive past the pilot stage.

FAQ

Frequently asked questions

Most organisations complete the initial roadmap in 4-6 weeks with dedicated effort. This includes stakeholder workshops, data audits, and use-case prioritisation. The strategy should then be reviewed and updated quarterly.

No. The template is designed to be accessible to business leaders and strategy teams. However, you will benefit from involving someone with technical AI knowledge — either internal or an external adviser — particularly for the data readiness assessment and use-case feasibility scoring.

Use the executive summary one-pager section to communicate the business case clearly. Lead with specific use cases, expected ROI, and risk mitigation — not technology details. Showing quick-win pilots with measurable results is the most effective way to build ongoing support.

This depends on your maturity, budget, and strategic goals. The vendor scorecard template can help you evaluate options. In general, start with off-the-shelf AI tools for common use cases (e.g. chatbots, document processing) and build custom solutions only where AI creates a genuine competitive advantage.

We recommend a lightweight monthly review of active initiatives and a more thorough quarterly strategy review. The annual review should include a full maturity re-assessment and roadmap refresh for the next 12 months.

Need a custom AI template?

Our team can build tailored templates for your specific business needs. Book a free strategy call.