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    AdoptionLab.AI · Plan Overview

    Navigator Recommendation Matrix

    This page shows every possible recommendation the Navigator can produce — 5 phases × 2 variants = 10 unique plans. Each phase has two variants based on how many questions the user answered "Yes" for that phase. All content is defined in src/config/navigatorData.js.

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    1
    Phase 1: Explore
    Map your current state and set guardrails
    Questions in this phase
    Q1.Has your organization completed a baseline AI assessment to document current usage, attitudes, and concerns?
    Q2.Do you have a written AI policy covering both prohibited uses and a forward-looking vision for AI adoption?
    Variant A — Neither question answered "Yes"

    Your AI adoption journey is ready to begin — start with clarity.

    Phase 1 is about understanding where you stand today before moving forward. Your most valuable first step is honest documentation of your team's current relationship with AI.

    90-Day Priorities
    Days 1–30
    Run a baseline AI assessment
    Conduct anonymous interviews across all levels of your team to surface current AI usage, attitudes, and concerns. Use this data to customize your adoption approach.
    Days 31–60
    Draft your AI policy
    Develop a two-part policy: a 'red lines' section defining prohibited uses, and a vision section describing where AI will take your team. Involve HR, IT, and Legal.
    Days 61–90
    Share findings and next steps
    Report back to your team within 60 days of the survey closing. Commit to transparency — share what you learned and what actions you are taking as a result.
    Quick Wins
    Schedule informal 1-on-1 conversations with 3–5 team members this week to ask how they are currently using AI
    Search online for your industry's most common AI use cases to build context before the formal assessment
    Watch Out For

    Don't skip the assessment and go straight to policy — without a real baseline, your policy will miss the mark.

    Variant B — At least one question answered "Yes"

    Your baseline is set — now turn insight into formal policy.

    You have done the important groundwork of understanding your team's AI landscape. The next priority is translating that insight into a clear, written policy that sets direction and reduces anxiety.

    90-Day Priorities
    Days 1–30
    Draft your AI charter
    Build a two-part policy: prohibited uses vetted by HR and Legal, and a forward-looking vision aligned to your mission. Circulate a draft to employee resource groups for input.
    Days 31–60
    Communicate the policy broadly
    Present both sections together as one coherent story — what your organization will not do, what it intends to do, and why. Host a live Q&A session to surface concerns.
    Days 61–90
    Schedule your first policy review
    Set a calendar reminder to revisit both policy sections in 90 days. As your AI knowledge grows, the policy should evolve with it.
    Quick Wins
    Review two or three AI policies from peer organizations this week to identify what resonates for your context
    Identify the key stakeholders (HR, Legal, IT) you need at the table before drafting begins
    Watch Out For

    A policy without a vision is just a list of restrictions — make sure the forward-looking section is as strong as the guardrails.

    Linked Resources (Phase 1)
    Your First Steps with AIAI Readiness Self-Assessment8 Steps to Improve Your AI Prompts↗
    2
    Phase 2: Experiment
    Run small pilots and learn fast
    Questions in this phase
    Q3.Have you identified and documented AI pilots across your team — including any informal or unsanctioned usage?
    Q4.Has your team established directional metrics that connect AI efforts to existing strategic priorities?
    Variant A — Neither question answered "Yes"

    It is time to move from awareness to active experimentation.

    Phase 2 is where strategy meets practice. Your team needs a safe, structured space to explore AI through real work — and leadership needs visibility into what is already happening.

    90-Day Priorities
    Days 1–30
    Surface and document pilots
    Appoint an AI Coordinator (suggest 50% allocation) to identify all current AI usage across your team, including informal use. Document each pilot at a high level for comparison.
    Days 31–60
    Establish directional metrics
    Connect AI efforts to 1–2 measures you already track, such as resolution rate or client satisfaction. Avoid creating entirely new metrics — anchor AI to existing priorities.
    Days 61–90
    Celebrate early attempts
    Host a brief 'lessons learned' session where team members share what they tried — successful or not. Recognizing the attempt normalizes experimentation and accelerates learning.
    Quick Wins
    Send a brief, anonymous pulse survey this week asking: 'Are you currently using any AI tools in your work? If yes, how?'
    Identify one trusted early adopter on your team who could become your informal AI Coordinator
    Watch Out For

    Hidden AI use is happening whether you know it or not — surface it with curiosity, not punishment, or you will drive it further underground.

    Variant B — At least one question answered "Yes"

    Pilots are surfaced — now connect them to outcomes that matter.

    You have visibility into your team's AI activity, which puts you ahead of most organizations. The next step is creating a measurement framework that connects these experiments to results your leadership team already cares about.

    90-Day Priorities
    Days 1–30
    Define 2–3 directional metrics
    Select existing measures — client satisfaction, first-contact resolution, time to delivery — that AI pilots could plausibly influence. Establish a simple before/after tracking approach.
    Days 31–60
    Reduce duplication across pilots
    Review your documented pilots for overlap. Where two pilots address the same need, consolidate them or designate one as the priority. This focuses energy and simplifies measurement.
    Days 61–90
    Share a leadership progress update
    Produce a brief monthly update for your leadership team covering active pilots, early results, and lessons learned. Use AI to help draft it — model the behavior you want to see.
    Quick Wins
    List your top 3 existing team metrics and ask: 'Which of these could AI move?' — that list becomes your measurement starting point
    Schedule a 30-minute pilot review with your AI Coordinator to identify which experiments are ready to be measured
    Watch Out For

    Avoid creating entirely new AI-specific metrics — if leadership does not already track it, they will not trust it as evidence of progress.

    Linked Resources (Phase 2)
    Everyday AI Use CasesPDSA TrackerWhy Most AI Pilots Stall — And What to Do Instead
    3
    Phase 3: Extend
    Scale what works across the team
    Questions in this phase
    Q5.Have you selected high-potential pilots to scale, with clearly defined go/no-go criteria and success measures?
    Q6.Is there an opt-in AI training and coaching program in place, including role-specific practice environments?
    Variant A — Neither question answered "Yes"

    Your experiments are ready — now build the structure to scale them.

    Phase 3 is about moving from individual experiments to team-wide impact. Before scaling anything, take time to assess what you have learned and define what success looks like at greater reach.

    90-Day Priorities
    Days 1–30
    Audit your pilot portfolio
    Review all active pilots against your directional metrics. Identify which 1–2 are delivering the clearest value and are most ready to expand. Formally close pilots that are unlikely to scale.
    Days 31–60
    Define go/no-go criteria
    Before expanding any pilot, agree on what success looks like, who decides, and what would trigger a pause or redesign. Document this so decisions are based on evidence, not momentum.
    Days 61–90
    Build MVP training materials
    Create minimum viable training for your first scaled pilot. Test it with willing early adopters and incorporate their feedback before rolling out more broadly.
    Quick Wins
    List your active pilots and rate each one: 'High value and ready to scale / Promising but needs work / Low value — consider closing'
    Identify two or three team members who have been most engaged with AI pilots — they are your natural scaling champions
    Watch Out For

    Scaling too many pilots at once is the most common Phase 3 mistake — start with one, learn how to scale, then expand.

    Variant B — At least one question answered "Yes"

    Pilots are selected — now build the support systems to grow them.

    You have identified which work is worth expanding. Now the focus shifts to training, measurement validation, and ensuring the people doing the work feel supported as the pilot grows beyond its original team.

    90-Day Priorities
    Days 1–30
    Validate metrics at scale
    Test whether your pilot's success measures hold up when more people use the tool. Are outcomes consistent? Are you collecting data in a way that is sustainable? Refine now, before full rollout.
    Days 31–60
    Launch opt-in training program
    Deploy your MVP training with an opt-in approach. Pair new participants with experienced pilot users for peer coaching. Capture feedback every two weeks using a short PDSA cycle.
    Days 61–90
    Prepare go/no-go decision
    At the 60-day mark, convene your AI Coordinator and leadership team to assess the scaled pilot against your pre-defined criteria. Make a clear embed or pause decision with documented reasoning.
    Quick Wins
    Send a 3-question feedback survey to current pilot participants this week: What is working? What is frustrating? What would help you use this more?
    Identify who in your organization is not yet opted in — they will need extra support if the pilot becomes standard practice
    Watch Out For

    Watch for the sunk cost trap — if a scaled pilot is not delivering, document why and pause it. Continuing out of momentum is expensive.

    Linked Resources (Phase 3)
    A Leader's Roadmap to Human-Centered AIPDSA TrackerFrom Curiosity to Capability: A Practical Path
    4
    Phase 4: Embed
    Make proven practices standard
    Questions in this phase
    Q7.Have AI processes been formally integrated into SOPs, onboarding materials, and standard team workflows?
    Q8.Have you partnered with HR to update job descriptions and performance expectations to reflect AI responsibilities?
    Variant A — Neither question answered "Yes"

    Proven work is ready to become permanent — formalize it now.

    Phase 4 is a significant milestone. Your pilots have demonstrated real value, and it is time to stop treating AI as an experiment and start treating it as the standard way certain work gets done.

    90-Day Priorities
    Days 1–30
    Update SOPs and documentation
    Integrate AI-enabled steps into standard operating procedures, playbooks, and onboarding materials. Involve the people who ran the pilots to ensure documentation reflects practical reality.
    Days 31–60
    Partner with HR on role updates
    Work with HR to update job descriptions for roles where AI is now standard. Add clear language about AI responsibilities. Include a note in new job postings that the organization actively uses AI.
    Days 61–90
    Sustain through monitoring
    Establish a regular check-in cadence between your AI Coordinator and the teams using embedded processes. Confirm consistent usage, capture refinements, and recognize strong adopters as peer advisors.
    Quick Wins
    Identify the one process most ready to be embedded and draft a single updated SOP section this week to build momentum
    Schedule a conversation with your HR partner to brief them on where you are — they should not be surprised when job description updates arrive
    Watch Out For

    Embedding without updating onboarding creates a two-tier team — new hires will not have the same capability as those who went through the pilot.

    Variant B — At least one question answered "Yes"

    Processes are embedding — now make it stick through people systems.

    You have begun formalizing AI into your workflows, which is a major achievement. The remaining work is about making sure the human systems — hiring, onboarding, performance — reinforce what you have built.

    90-Day Priorities
    Days 1–30
    Complete HR integration
    Finalize updates to job descriptions, performance expectations, and onboarding modules for all roles where AI is now standard. Ensure internal transfers receive the same onboarding as new hires.
    Days 31–60
    Recognize and celebrate milestones
    Have your executive sponsor or senior leader visibly celebrate the embedding achievement with the team. Share a concrete story of how the change improved work for staff or clients.
    Days 61–90
    Monitor for drift and improvement
    Set a quarterly review to confirm embedded processes are being used as intended. Create a lightweight channel for users to suggest refinements — the best improvements come from the people doing the work.
    Quick Wins
    Ask your AI Coordinator: 'Are the embedded processes actually being used consistently?' — if not, surface the barriers before they become habits
    Draft a two-paragraph success story about the embedding journey to share with your broader organization this week
    Watch Out For

    Embedding can quietly drift back to old habits without regular visibility — schedule check-ins before you think you need them.

    Linked Resources (Phase 4)
    A Leader's Roadmap to Human-Centered AIThe Human Side of AI Adoption
    5
    Phase 5: re-Envision
    Redesign roles around AI capability
    Questions in this phase
    Q9.Has your team co-created a future-state vision for AI-enabled roles, shifting capacity toward higher-value work?
    Q10.Are you actively sharing your AI journey with the broader organization to accelerate adoption across teams?
    Variant A — Neither question answered "Yes"

    Your foundation is strong — now reimagine what your team can become.

    Phase 5 is not about adding AI to existing work — it is about asking what work should look like now that AI is part of your team's capability. This is your opportunity to lead a genuine reinvention.

    90-Day Priorities
    Days 1–30
    Map automation opportunities
    Work with your AI Coordinator to identify tasks that are now automatable or significantly simplified. Use attrition and internal movement — not layoffs — to rebalance workloads toward higher-value activities.
    Days 31–60
    Co-create future-state roles
    Invite frontline employees into structured design sessions to reimagine what their roles could look like when AI handles the routine. People who shaped the pilots are your best partners for envisioning what is next.
    Days 61–90
    Reimagine your value proposition
    Shift attention outward: what new value can you now deliver to clients or community members that was previously out of reach? Where can AI extend access, personalization, or equity for the people you serve?
    Quick Wins
    Ask your leadership team: 'If AI handled 20% of our routine work, what would we do with that capacity?' — write down the answers
    Identify one external outcome — something you deliver to clients or community members — that AI could meaningfully improve
    Watch Out For

    Do not use capacity freed by AI to reduce headcount — your team's institutional knowledge is your greatest competitive advantage at this stage.

    Variant B — At least one question answered "Yes"

    You are leading the way — now share what you have learned.

    Your team has achieved something rare: a functioning, human-centered AI adoption practice. The most valuable thing you can do now is continue evolving while helping the rest of your organization catch up.

    90-Day Priorities
    Days 1–30
    Share your journey broadly
    Make your team available for informational interviews with other departments. Document your key lessons in a brief internal case study that others can learn from and adapt.
    Days 31–60
    Explore emerging capabilities
    Return to Phase 1 with fresh eyes — run a lightweight assessment of new AI capabilities that have emerged since you began. Identify 1–2 small pilots worth testing with your now-experienced team.
    Days 61–90
    Embed continuous learning
    Make reflection a permanent part of your team culture: quarterly reviews of what changed, what surprised you, and what you would do differently. An adaptive team is more valuable than any individual AI tool.
    Quick Wins
    Write down the three things you wish you had known at the start of this journey — that list is the beginning of your internal case study
    Identify one peer leader in your organization who is earlier in their AI journey and offer to share what you have learned
    Watch Out For

    Resting on your current capability while AI continues to evolve is the fastest path to falling behind — stay curious.

    Linked Resources (Phase 5)
    A Leader's Roadmap to Human-Centered AIFrom Curiosity to Capability: A Practical Path
    AdoptionLab.AI · Human-Centered AI Adoption by Matt Humer, MBA← Back to Navigator