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AI Readiness Guide · Appendix E

90-Day AI Readiness Action Plan.

Turn readiness findings into coordinated action through three focused phases: establish direction, prepare the organization, and launch one controlled experiment that produces evidence.

Developed by FridAI Learning Center Published Timeline 90 days Structure Three phases
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90-Day Plan Tools Move between the major planning checkpoints or print a working copy.

Start the plan Jump to Day 90 review

AI readiness becomes valuable only when it leads to action.

An organization may understand its strengths. It may identify gaps. Leadership may agree on priorities. Employees may be interested. A promising AI use case may be selected.

But unless those insights turn into specific actions, ownership, and deadlines, progress can stall.

This plan helps organizations move from assessment to implementation.

The objective is not to transform the entire organization in 90 days.

The objective is to build momentum.

  • Establish basic governance.
  • Create leadership alignment.
  • Prepare employees.
  • Identify and prioritize use cases.
  • Strengthen relevant data.
  • Launch one controlled experiment.
  • Measure what happens.
  • Decide what comes next.

How to use this action plan

Three Phases of Readiness

This plan is organized into three phases.

Days 1–30

Establish Visibility and Direction

Understand where the organization is today.

Days 31–60

Build Readiness and Select the Opportunity

Strengthen the foundations required for responsible experimentation.

Days 61–90

Pilot, Measure, and Learn

Move from preparation into controlled action.

Organizations should adapt the plan to their size, industry, resources, and level of AI maturity.

Not every action will apply equally.

Understand Prepare Test Measure Learn

Before Day 1

Establish the Starting Point

Before beginning the 90-day plan, complete the following where possible:

If those tools have not yet been completed, they can become part of the first 30 days.

90-Day Objective

Define What the Organization Will Accomplish

Write one sentence describing what you want the organization to accomplish over the next 90 days.

Example

Over the next 90 days, we will establish basic AI governance, prepare leadership and employees, identify our highest-value AI opportunity, and launch one controlled pilot with measurable outcomes.

Ownership

Assign the People Responsible for Momentum

Our AI Readiness Owner

Every 90-day plan needs clear coordination.

Responsibilities

Our Executive Sponsor

The executive sponsor should help remove barriers, allocate resources, reinforce expectations, and ensure AI readiness remains connected to organizational priorities.

Our Core AI Readiness Team

Depending on organizational size, include representatives from leadership, operations, technology, finance, human resources, legal or compliance, data, and frontline functions.

Name Role AI Readiness Responsibility

Smaller organizations may have only two or three people. That is sufficient if responsibilities are clear.

Phase 1

Days 1–30

Establish Visibility and Direction

The first 30 days should answer:

  • Where are we today?
  • What is already happening?
  • What are our biggest risks?
  • What matters most?

The objective is not to launch major AI projects immediately. The objective is to create organizational visibility and direction.

Action 1

Align Leadership

Leadership should agree on why the organization is exploring AI.

Discuss:

  • Why does AI matter to us?
  • What organizational priorities could it support?
  • What are we trying to improve?
  • What risks concern us?
  • What would responsible AI adoption look like?
Action 2

Inventory Current AI Use

Before planning future AI adoption, understand what is already happening.

Ask departments and employees:

  • What AI tools are you using?
  • How are you using them?
  • Are you using personal accounts?
  • What information are you entering?
  • What benefits are you seeing?
  • What concerns do you have?

Current AI Use Inventory

Department Tool Use Data Involved Approved? Owner
Action 3

Identify Immediate AI Risks

Review current use for potential problems.

Consider:

  • Unapproved tools.
  • Sensitive data exposure.
  • Shared accounts.
  • AI-generated work used without review.
  • Unknown vendor terms.
  • Unclear accountability.
  • High-risk decisions influenced by AI.

Immediate Risk #1

Immediate Risk #2

Action 4

Establish Basic AI Guardrails

Do not wait for a perfect policy before providing employees with basic guidance.

At minimum, address:

Action 5

Establish Approved AI Tools

Identify which tools employees may use for organizational work.

Approved Tool 1

Approved Tool 2

Action 6

Assess Leadership AI Literacy

Ask whether leaders can explain:

  • What AI is.
  • What generative AI is.
  • How predictive AI differs.
  • Where AI may create value.
  • Where AI may fail.
  • Why human oversight matters.
Action 7

Ask Employees Where the Friction Is

What part of your job would you most like to make easier?

Capture responses. Common themes may include:

  • Repetitive work.
  • Report preparation.
  • Data entry.
  • Searching for information.
  • Customer communication.
  • Manual analysis.
  • Forecasting.
  • Documentation.

These are potential AI opportunity signals.

Action 8

Identify Potential AI Champions

Look for employees who are curious, credible, practical, willing to experiment, and comfortable helping others.

Champion Department

Day 30 Review

Review Visibility and Direction

Phase 2

Days 31–60

Build Readiness and Select the Opportunity

The second 30 days should answer:

  • Where can AI create meaningful value?
  • What needs to be prepared before we test it?

This phase should move the organization from general AI awareness toward a specific, prioritized opportunity.

Action 9

Provide Foundational Employee AI Literacy

Employees should understand:

  • What AI is.
  • What it can do.
  • What it cannot reliably do.
  • How AI relates to their work.
  • What tools are approved.
  • What data is restricted.
  • When human review is required.
/
Action 10

Prepare Managers

Managers should understand:

  • Why the organization is exploring AI.
  • What employees are allowed to do.
  • How to discuss workforce concerns.
  • How to identify use cases.
  • How to support experimentation.
Action 11

Create the AI Opportunity List

Use employee feedback, leadership priorities, and process analysis.

Do not pursue all of them. The purpose is to create choices.

Action 12

Map One or Two High-Friction Processes

Select processes likely to contain meaningful AI opportunities.

Process 1

Process 2

Action 13

Prioritize AI Use Cases

Evaluate the strongest candidates using organizational value, frequency, process readiness, data readiness, technical feasibility, workforce readiness, measurability, speed to learning, risk, and strategic alignment.

Candidate Use Case Score
Top Candidate
/65
Second Candidate
/65
Third Candidate
/65
Action 14

Select the First Pilot Candidate

Action 15

Complete the Data Readiness Review

/5
Action 16

Define the Current Baseline

Before AI is tested, determine current performance.

Not every field will apply. Use the measures relevant to the selected problem.

Action 17

Define the Pilot Hypothesis

Use this structure:

We believe using for will improve from to without creating unacceptable .
Action 18

Define Success Criteria

Action 19

Identify Pilot Participants

Action 20

Complete Governance and Vendor Review

Before launch, confirm:

Day 60 Review

Confirm Readiness to Launch

Review Question Response
Have employees received basic AI education?
Are managers prepared?
Have potential AI opportunities been identified?
Has one pilot candidate been selected?
Is the problem clearly defined?
Is the relevant data sufficiently ready?
Has a baseline been established?
Are success measures defined?
Are governance requirements addressed?
Are we ready to launch the pilot?
Phase 3

Days 61–90

Pilot, Measure, and Learn

The final 30 days should answer:

Does this AI use case create enough value to justify doing more?

The objective is not to prove that AI works. The objective is to learn whether this application works for this organization.

Action 21

Train Pilot Participants

Training should cover:

/
Action 22

Launch the Pilot

Action 23

Track Quantitative Results

Metric Baseline Pilot Result Change
Time
Accuracy
Error Rate
Cost
Throughput
Response Time
Action 24

Track AI Errors and Corrections

Date Issue Type of Error Human Correction Required? Impact

Look for patterns.

Action 25

Collect Employee Feedback

Feedback Question Response
Did the AI make the work easier?
Did it save time?
Did it create additional work?
Did you trust the results appropriately?
Would you continue using it?
Action 26

Track Cost

Use reasonable estimates. Perfection is not required.

Action 27

Estimate Value

Credibility matters

Do not inflate estimates.

Action 28

Compare Against Success Criteria

Measure Target Actual Result
Primary Success Measure
Secondary Success Measure
Employee Experience
Risk Threshold
Action 29

Document What the Organization Learned

Action 30

Make the Pilot Decision

At the end of the pilot, choose one.

All four decisions are legitimate outcomes.

Day 90 Leadership Review

Review the Entire Readiness Cycle

90-Day Scorecard

Summarize Readiness Progress

Area Day 1 Status Day 90 Status Improvement
Leadership Readiness
Workforce Readiness
Governance
Data Readiness
Use-Case Readiness
Pilot Readiness
Internal Capability

90-Day Completion Checklist

Determine What Has Been Completed

The organization does not need every box checked to demonstrate progress. The checklist is intended to reveal what should happen next.

Sample 90-Day AI Readiness Plan

A Practical Example

Timeframe Priority Action Owner Completion Evidence
Days 1–15 Governance Draft basic AI-use guidelines COO Guidelines approved
Days 1–20 Visibility Inventory current employee AI use AI Lead Inventory completed
Days 15–30 Leadership Conduct leadership AI workshop CEO Workshop completed
Days 31–45 Workforce Deliver employee AI literacy training HR Training completed
Days 31–45 Use Cases Collect employee friction points Operations Opportunity list created
Days 40–50 Prioritization Score top five AI opportunities AI Team Top use case selected
Days 45–60 Data Evaluate priority dataset Data Owner Data review completed
Days 50–60 Pilot Define baseline and success measures Business Owner Pilot plan approved
Days 61–70 Training Train pilot participants AI Lead Participants ready
Days 70–90 Pilot Run controlled pilot Pilot Owner Pilot data collected
Day 90 Decision Evaluate pilot Leadership Scale / Modify / Pause / Stop

The dates may change. The discipline should remain.

Weekly Progress Tracker

Keep Progress Visible

Organizations may find it useful to review progress every week.

Week 1

Week 2

Week 3

Week 4

Repeat the same structure throughout the 90-day cycle if useful.

AI Readiness Decision Log

Capture Major Decisions

Date Decision Why Owner Review Date

This creates institutional memory.

AI Learning Log

Capture Lessons Throughout the 90 Days

90-Day Risk Log

Track Readiness and Pilot Risks

Risk Likelihood Impact Mitigation Owner Status

Potential risks may include sensitive data exposure, poor employee adoption, unreliable outputs, vendor issues, cost escalation, technical failure, or inadequate support.

90-Day Resource Plan

Make Resource Expectations Visible

The purpose is not to create a large budget. It is to make resource expectations visible.

Every 30-Day Review

Questions to Ask During Each Review

  1. What did we learn?
  2. What changed?
  3. What is blocked?
  4. What risk has increased?
  5. What risk has decreased?
  6. What new opportunity appeared?
  7. What assumption turned out to be wrong?
  8. What should we stop doing?
  9. What should we do next?

These questions keep the plan adaptive.

What Not to Do

Avoid These Mistakes During the First 90 Days

Do Not Try to Transform Everything

Choose a manageable scope.

Do Not Purchase Multiple Tools Without Clear Use Cases

Start with problems.

Do Not Spend Months Creating a Perfect Policy

Establish useful guardrails first.

Do Not Clean Every Dataset

Prepare the data required for the priority use case.

Do Not Train Employees Without Practical Examples

Connect AI to real work.

Do Not Run Pilots Without Baselines

Measure before changing.

Do Not Allow Pilots to Continue Indefinitely

Set an evaluation point.

Do Not Scale Because People Are Excited

Scale because evidence supports it.

Do Not Hide Failure

Document what was learned.

Do Not Confuse AI Activity With AI Value

Always return to the organizational outcome.

What Success Looks Like

Progress Does Not Require Organization-Wide Deployment

A successful first 90 days does not necessarily mean:

  • AI has been deployed everywhere.
  • Hundreds of employees are using AI.
  • Large financial returns have already appeared.
  • The organization has a complete long-term AI strategy.

A successful 90 days may mean something much more valuable:

That is progress.

The Next 90 Days

Begin the Next Cycle

The cycle continues.

From 90 Days to Organizational Capability

Establish a Repeatable Rhythm

The purpose of a 90-day action plan is not to finish AI readiness.

AI readiness is never truly finished.

The purpose is to establish a repeatable rhythm.

Assess Prioritize Prepare Pilot Measure Learn Decide Repeat

Each cycle should leave the organization:

  • More informed.
  • More capable.
  • More disciplined.
  • Better prepared to make the next decision.

Over time, the organization should need less external prompting to identify AI opportunities.

Employees will begin recognizing them. Managers will become more comfortable evaluating them. Leaders will ask better questions. Data owners will understand what information matters. Governance will become more mature. Successful workflows will spread. Weak ideas will be rejected earlier. The organization will learn faster.

That is how AI readiness becomes an enduring capability.

Final 90-Day Commitment

Define the Responsible Next Step

Then begin.

The greatest danger in AI readiness is not discovering that your organization has gaps.

It is learning what needs to happen and doing nothing with that knowledge.

You do not need to solve everything.

You do not need perfect certainty.

You do not need the perfect technology.

You need a responsible next step. Then another. Then another.

Ninety days is enough time to move from discussion to evidence.

Enough time to build clarity.

Enough time to begin learning.

And often, enough time to change the way an organization thinks about artificial intelligence altogether.

Last reviewed:

This action plan supports organizational planning and internal readiness work. It does not replace specialized legal, regulatory, privacy, security, financial, workforce, or technical review.

← Previous appendix Appendix D: AI Use-Case Prioritization Worksheet

Compare AI opportunities using organizational value, feasibility, readiness, measurability, risk, cost, and strategic alignment.

Return to the guide → The AI Readiness Guide

Return to the complete readiness series, chapter list, and organizational workbook collection.