Creating an AI Roadmap: From Vision to 18-Month Implementation Plan

Executive Summary

• An AI roadmap translates strategy into a time-bound plan with specific milestones, dependencies, and resource allocations
• The 18-month horizon balances long enough for meaningful progress with short enough to maintain accountability
• Effective roadmaps include three phases: Foundation (months 1-6), Build (months 7-12), and Scale (months 13-18)
• Each phase has defined objectives, deliverables, success criteria, and decision gates
• Roadmaps must be living documents, reviewed quarterly and adjusted based on learning
• The best roadmaps balance ambition with realism—they're achievable but stretch capability
• Roadmap creation is a team exercise requiring input from business, technology, and operations

Why This Matters Now

Strategy provides direction. A roadmap provides a path.

Many organizations have AI strategies that never translate to action. The gap isn't commitment—it's specificity. "We will become an AI-enabled organization" is a vision. A roadmap specifies what happens in Q1, what capabilities must be in place by month 6, and what success looks like at month 18.

Without a roadmap:

• Teams pursue initiatives without coordination
• Resources aren't allocated to the right priorities
• Progress isn't measurable
• Leadership can't track execution against commitments

The 18-month horizon is deliberate. Shorter horizons don't allow for meaningful AI capability building. Longer horizons become speculative. Eighteen months provides enough time to demonstrate value while maintaining accountability.

AI Roadmap vs. AI Strategy

Strategy answers "What should we do?" Roadmap answers "When and how will we do it?"

If you haven't developed your AI strategy, start there. Roadmapping without strategy produces activity without direction.

The 18-Month Roadmap Structure

Phase 1: Foundation (Months 1-6)

Objective: Establish the capabilities necessary for sustainable AI deployment.

Foundation isn't glamorous, but it determines everything that follows. Organizations that rush past foundation work face repeated remediation later.

Key Workstreams:

Foundation Phase Milestones:

• Month 2: AI policy draft completed
• Month 3: Data governance framework approved
• Month 4: First pilot begins
• Month 6: Foundation phase review and decision gate

Decision Gate Questions (Month 6):

• Is our data foundation sufficient for planned pilots?
• Do we have the governance structure to manage AI risk?
• Are pilots on track? What have we learned?
• Should we proceed to Build phase as planned or extend Foundation?

Phase 2: Build (Months 7-12)

Objective: Demonstrate AI value through successful pilots and initial production deployments.

Build phase is where theory becomes practice. The focus is on learning through doing—understanding what works in your specific context.

Key Workstreams:

Build Phase Milestones:

• Month 8: First pilot results available
• Month 9: First production deployment decision
• Month 10: Second pilot begins
• Month 12: Build phase review and decision gate

Decision Gate Questions (Month 12):

• Have pilots demonstrated expected value?
• Are we ready to scale successful approaches?
• What capability gaps remain?
• What adjustments are needed for Scale phase?

Phase 3: Scale (Months 13-18)

Objective: Expand proven AI approaches across the organization and establish sustainable operating model.

Scale phase multiplies success. It's not about starting new experiments—it's about extending what works.

Key Workstreams:

Scale Phase Milestones:

• Month 14: Second production deployment
• Month 15: Year 1 ROI assessment
• Month 16: Year 2 strategy and roadmap drafted
• Month 18: Roadmap completion review

Decision Gate Questions (Month 18):

• What business value has been created?
• What capabilities have we built?
• What works? What doesn't?
• What should the next 18 months focus on?

SOP: Quarterly Roadmap Review

Roadmaps drift without disciplined review. This Standard Operating Procedure ensures roadmaps remain relevant and accountable.

Purpose

Quarterly review ensures roadmap alignment with strategy, tracks progress against milestones, and enables course corrections.

Frequency

Quarterly (aligned with business planning cycle)

Participants

• AI/Digital Leader (Chair)
• Executive Sponsor
• IT Leadership
• Business Unit Representatives
• Risk/Compliance Representative
• Finance Representative

Pre-Meeting Preparation (Owner: AI/Digital Leader)

One week before meeting:

1. Collect status updates from all workstream leads
2. Compile milestone progress (completed, in progress, at risk, not started)
3. Prepare variance analysis (actual vs. planned)
4. Document emerging risks and issues
5. Gather budget status (actual vs. planned spend)
6. Prepare draft roadmap adjustments for discussion

Meeting Agenda (90 minutes)

Decision Types

Post-Meeting Actions (Owner: AI/Digital Leader)

Within one week:

1. Distribute meeting notes and decisions
2. Update roadmap document with approved changes
3. Communicate adjustments to affected teams
4. Update risk register
5. Schedule follow-up on action items

Documentation

Maintain quarterly review records including:

• Meeting attendance
• Milestone status at time of review
• Decisions made
• Roadmap changes approved
• Action items and owners

Roadmap Template

Phase 1: Foundation (Months 1-6)

Phase 2: Build (Months 7-12)

Phase 3: Scale (Months 13-18)

Common Failure Modes

1. Overloading the Roadmap

Attempting too many initiatives simultaneously dilutes focus and exhausts resources.

Fix: Limit active workstreams. Two major initiatives executing well beats five struggling.

2. Ignoring Dependencies

AI initiatives have dependencies—on data, on infrastructure, on skills. Ignoring them creates bottlenecks.

Fix: Map dependencies explicitly. Don't schedule work that depends on incomplete prerequisites.

3. Fixed Thinking

Treating the roadmap as immutable when circumstances change.

Fix: Quarterly reviews with genuine authority to adjust. The roadmap serves the strategy, not the other way around.

4. Milestone Without Meaning

Milestones that don't represent genuine progress ("complete documentation") rather than outcomes ("pilot delivers 20% efficiency improvement").

Fix: Define milestones in terms of outcomes, not activities.

5. Disconnection from Budget

Roadmap plans without corresponding budget allocation.

Fix: Every roadmap element must have allocated resources. Unfunded initiatives are wishes, not plans.

Checklist: AI Roadmap Development

Preparation

• AI strategy approved and available
• Executive sponsor confirmed
• Roadmap development team identified
• Current state assessment completed
• Resource constraints understood

Phase Design

• Three phases defined with clear objectives
• Workstreams identified for each phase
• Milestones defined as outcomes, not activities
• Dependencies mapped between workstreams
• Decision gates defined with criteria

Resource Alignment

• Budget allocated to each phase
• People resources assigned or planned
• Technology requirements specified
• External support needs identified

Governance

• Quarterly review process established
• Decision authority defined
• Escalation path clear
• Reporting cadence set

Metrics to Track

Frequently Asked Questions

Next Steps

A roadmap transforms AI ambition into executable plans. It creates accountability, enables tracking, and provides a structure for learning and adjustment.

If you have a strategy but lack a concrete implementation plan, roadmap development is your next step.

Book an AI Readiness Audit with Pertama Partners to develop a roadmap grounded in your specific context, capabilities, and constraints.

Related Reading

• Building Your First AI Strategy
• 7 AI Strategy Mistakes That Derail Implementation
• AI Investment Prioritization: Allocating Budget for Maximum Impact