AI Implementation Roadmap - Complete Guide

Overview

You've decided to implement AI. Now you need to execute. This comprehensive roadmap provides the detailed, day-by-day guidance to take AI from "we want to do this" to "we have AI in production generating value"—in 90 days.

The playbook combines timeline structure with all the supporting tools you need: how to evaluate and select vendors, how to measure success, how to drive adoption through change management, how to prioritize use cases, and how to plan realistic budgets. It's the complete implementation toolkit.

What's Inside

• 90-Day Implementation Playbook: Week-by-week detailed plan with specific tasks, owners, deliverables, and dependencies for each phase
  • Days 1-30 (Foundation): Governance setup, strategy alignment, pilot selection, team formation
  • Days 31-60 (Build): Data preparation, model development, testing, integration planning
  • Days 61-90 (Deploy): Production hardening, launch, user training, adoption tracking
• Vendor Evaluation Matrix: Systematic methodology for evaluating and selecting AI tools, platforms, and service providers with weighted scoring criteria
• Success Metrics Dashboard: Business KPIs (ROI, efficiency gains, error reduction) and technical KPIs (model performance, system reliability) to track value realization
• Change Management Plan: Proven techniques for driving adoption and overcoming resistance including stakeholder analysis, communication planning, and training design
• Use Case Prioritization Tool: Framework for scoring and ranking potential AI use cases by business value, feasibility, and strategic alignment
• Budget and Resource Planning: Realistic cost estimates ($50K-$500K depending on scope) and resource requirements including team composition and skill needs
• Integration Playbook: Technical guidance for integrating AI with existing systems, data pipelines, and workflows
• Post-Implementation Review: Framework for evaluating project success and capturing lessons learned

Who This Is For

• Chief AI Officers responsible for AI delivery
• AI Product Managers leading implementation projects
• Project Managers executing AI deployments
• Business Leaders sponsoring AI initiatives
• Technology Leaders building AI delivery capabilities

Why This Resource

Generic project management doesn't address AI's unique implementation challenges: data preparation complexity, model iteration cycles, integration requirements, and adoption barriers. This roadmap is built specifically for AI implementation, with timelines and tasks calibrated to AI project realities.

The supporting tools eliminate common implementation gaps: vendor selection that considers AI-specific criteria, change management that addresses AI trust issues, and budgets that account for AI's iterative nature.

FAQ

Q: What's the realistic budget range for AI implementation?

A: Budget ranges from $50K-$500K depending on scope, complexity, and build-vs-buy decisions. The budget planning section provides detailed cost categories and realistic estimates for different project types.

Q: How does the 90-day timeline account for AI iteration cycles?

A: The Build phase (days 31-60) explicitly includes iteration: initial model development, testing, refinement, and re-testing. The timeline assumes 2-3 iteration cycles which is realistic for most use cases.

Q: What if we're using an AI vendor vs. building in-house?

A: The roadmap covers both scenarios. The vendor evaluation matrix helps with vendor selection; the integration playbook addresses vendor integration. Build timelines are adjusted for vendor vs. in-house approaches.