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AI Adoption Roadmap — A 90-Day Plan for Companies

Pertama PartnersFebruary 11, 202612 min read
🇲🇾 Malaysia🇸🇬 Singapore
AI Adoption Roadmap — A 90-Day Plan for Companies

Why 90 Days?

Ninety days is long enough to build proper foundations and see measurable results, but short enough to maintain urgency and executive attention. Companies that try to plan for 12 months before taking action often stall. Companies that rush into AI without governance create risks.

This 90-day roadmap strikes the balance: structured enough to manage risk, fast enough to capture value.

Before You Start: Pre-Requisites

Before beginning the 90-day roadmap, ensure you have:

  • Executive sponsorship — At least one C-suite sponsor who will champion the programme
  • A small governance team — 3-5 people from IT, legal/compliance, HR, and business operations
  • Budget clarity — Know what you can spend on tools, training, and external support
  • Baseline assessment — A rough understanding of where AI is already being used (formally or informally)

Phase 1: Foundation (Days 1-30)

Week 1: Assess and Align

Objective: Understand current state and set direction.

  • Conduct an AI readiness survey across the organisation (anonymous, 10-15 questions)
  • Interview 5-10 department heads about their AI pain points and aspirations
  • Audit existing AI tool usage (what tools are employees already using?)
  • Review competitor AI adoption (what are peers in your industry doing?)
  • Align with executive sponsor on goals, budget, and success metrics

Deliverable: AI Readiness Report — current state, gaps, and opportunities

Week 2: Governance Setup

Objective: Establish the governance framework.

  • Form the AI Governance Committee (3-5 members, cross-functional)
  • Draft the company AI policy (use our AI Policy Template)
  • Draft the AI acceptable use policy for employees
  • Define the AI tool approval process and checklist
  • Identify the Data Protection Officer's role in AI governance

Deliverable: Draft AI Policy and Acceptable Use Policy

Week 3: Tool Selection and Approval

Objective: Approve initial AI tools for company use.

  • Evaluate 2-3 enterprise AI tools against your approval checklist
  • Negotiate enterprise licences with preferred vendors
  • Set up enterprise accounts with SSO, admin controls, and audit logging
  • Configure data loss prevention (DLP) rules for AI tools
  • Block unapproved AI tools at the network/proxy level (if feasible)

Deliverable: Approved tools list and enterprise accounts configured

Week 4: Training Design

Objective: Plan the training programme.

  • Identify training cohorts (who gets trained first?)
  • Select a training provider or design internal training
  • Schedule training sessions for Phase 2
  • Create role-specific use case libraries
  • Apply for HRDF (Malaysia) or SSG/SFEC (Singapore) funding

Deliverable: Training schedule and funding applications submitted

Phase 2: Activate (Days 31-60)

Week 5-6: Training Rollout

Objective: Build AI skills across the organisation.

  • Deliver AI training to the first cohort (AI champions / early adopters)
  • Distribute the AI acceptable use policy to all employees
  • Launch the prompt library on your intranet or shared drive
  • Set up an internal AI help channel (Slack/Teams) for questions
  • Collect feedback from the first training cohort and adjust

Deliverable: First cohort trained, AUP distributed, internal support channel live

Week 7-8: Pilot Projects

Objective: Demonstrate value with quick wins.

  • Select 3-5 pilot AI projects across different departments
  • Each pilot should have a clear problem, an AI solution, and a success metric
  • Assign an AI champion to lead each pilot
  • Document the process, results, and lessons learned for each pilot
  • Present pilot results to the executive sponsor and governance committee

Example pilot projects:

DepartmentPilot ProjectSuccess Metric
MarketingAI-assisted content creationTime saved per content piece
FinanceAI-powered report summarisationHours saved per week
HRAI-assisted job description writingTime to publish reduced
Customer ServiceAI response drafts for common queriesResponse time reduction
OperationsAI analysis of process dataInsights generated per week

Deliverable: 3-5 pilot projects completed with documented results

Phase 3: Scale (Days 61-90)

Week 9-10: Expand Training

Objective: Train the broader organisation.

  • Deliver AI training to remaining departments/cohorts
  • Offer advanced training to AI champions
  • Update training content based on pilot learnings
  • Create department-specific prompt libraries based on pilot successes
  • Launch an internal AI newsletter or knowledge-sharing session

Deliverable: Organisation-wide training complete

Week 11-12: Institutionalise

Objective: Make AI part of normal operations.

  • Finalise and formally publish the AI policy (CEO endorsement)
  • Embed AI governance into existing risk management processes
  • Set up quarterly AI tool reviews and policy updates
  • Define ongoing AI training requirements (annual refresher)
  • Create an AI use case backlog for future projects
  • Present the 90-day results to leadership, including ROI data
  • Plan the next phase of AI adoption (months 4-12)

Deliverable: Formal AI policy published, governance embedded, leadership report

Success Metrics

Track these metrics throughout the 90 days:

MetricTargetHow to Measure
Employees trained80%+ of target cohortTraining attendance records
AI policy awareness90%+ of employeesSurvey or policy acknowledgement
Approved tools adoption50%+ of trained employees actively using toolsTool usage analytics
Pilot projects completed3-5Project completion tracker
Time/cost savings from pilotsMeasurable improvementDepartment-reported metrics
AI incidentsZero critical incidentsIncident log

Common Pitfalls to Avoid

  1. Starting with technology instead of governance — Approving tools before having policies leads to uncontrolled risk
  2. Training without follow-up — Skills decay quickly without reinforcement and ongoing support
  3. Piloting without measurement — If you do not measure results, you cannot justify scaling
  4. Excluding legal/compliance — AI governance is not just an IT responsibility
  5. Moving too slowly — If your 90-day plan takes 6 months, you lose momentum and executive attention

Adapting for Your Company Size

Company SizeAdjustments
Small (10-50 employees)Combine governance committee into 2-3 people; train everyone at once; 1-2 pilot projects
Medium (50-200 employees)Follow the roadmap as written
Large (200+ employees)Add a dedicated AI programme manager; train by department over 4-6 weeks; 5-10 pilot projects

Related Reading

Frequently Asked Questions

Yes. A 90-day roadmap will not transform the entire organisation, but it will establish governance, train key teams, complete pilot projects, and demonstrate measurable value. This creates the foundation and momentum for ongoing AI adoption in months 4-12 and beyond.

Governance should come first, but only slightly. In the 90-day roadmap, governance setup happens in weeks 2-3, and training starts in week 5. You need basic policies and approved tools in place before training employees, but do not let governance work delay training by more than 2-3 weeks.

Costs vary based on company size and ambition. For a mid-size company (50-200 employees), budget for: enterprise AI tool licences (S$10-30 per user/month), training (S$5,000-25,000 for workshops, often subsidised), and optionally external consulting support. Total investment is typically S$20,000-80,000, much of which is reclaimable through government subsidies.

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