Approach

How it worksfor leaders, teams and the organization.

AI fluency is the ability to understand, use and adapt to AI in your own work. The program answers three questions: what people learn, who makes it stick, and how it keeps going. It grows from personal use to the whole enterprise, in three phases.

Three questions

What we do,question by question.

WhatWhat do we drive fluency around?

One foundation for everyone, then learning built for each role

Everyone gets the same foundation. After that, learning is specific to the role. Persona paths are built from interviews with the people who do the work, so exercises use their tasks, data and risks. Playbooks and challenges give people a reason to practice.

What changes

Role-relevant capability with a clear progression from first use to helping others.

  • Foundations for every employee: concepts, safe use, prompting, judging outputs
  • Persona paths with levels of advanced learning, built from persona interviews
  • Learning-by-doing playbooks: prompt-a-thons and hackathons on real tasks
  • Daily challenges and weekly quizzes
  • A tool layer for the AI platform you have approved
  • Your policies, terminology and examples built into the content
See the scale and the maturity matrix

AI fluency maturity

EveryoneUse casesEnterpriseEmbedRedesigned personal workRe-engineered workflowsNew roles and operating modelApplyDaily AI habitsUse cases in workflowsFunction-wide enablementExploreAI productsAI use casesAI-powered functions
WhatWhat people learn

Fluency starts with your own workand reaches how the organization runs.

AI for the enterprise

  1. 5Enterprise operating model and governanceThe organization makes deliberate choices about roles, decision rights, investment and governance.Usually in Embedded
  2. 4Entire functionsA function such as finance or HR redesigns how its work is done with AI and agents.Usually in Embedded
  3. 3Use cases and workflowsTeams apply AI to shared tasks, and a sequence of work changes, with AI handling defined steps and people reviewing the result.Usually in Scaling

AI for everyone

  1. 2Persona and role-based useLearning and practice are built for each role, so a finance analyst and a plant supervisor each work on their own tasks.Usually in Foundation
  2. 1AI product and tool deploymentPeople apply the approved AI tools to their own work and know when to check, challenge or escalate an output.Usually in Foundation
AI fluency maturity
Embed new ways of workingApplyExplore
Redesigned personal workRe-engineered workflowsNew roles and operating modelDaily AI habitsUse cases in workflowsFunction-wide enablementAI productsAI use casesAI-powered functions
AI for everyoneUse cases and workflowsThe enterprise

Building fluency takes learning programs that

  1. 1Build a shared foundation, with gamification and social energy as the catalyst
  2. 2Use engaging material that keeps evolving
  3. 3Teach by doing, in the flow of work
WhoWho makes it stick

Leaders, champions and learnersturn together, like gears.

LeadersChampionsLearners

  • Interconnected parts

    Fluency happens only when all three gears turn together.

  • Ripple effects, both ways

    Vision flows down, and adoption momentum flows up.

  • Compounding momentum

    As adoption begins, fluency builds on itself.

Leaders

Executives and senior leaders

Role-model AI fluency and guide the transformation: individual pre-meets, an executive program and a 30/60/90-day plan with named commitments.

Champions

Managers, trainers and early adopters

  • Managers embed behaviors

    They turn priorities into team action: set expectations, reinforce new ways of working, and help people bring AI into daily work.

  • Trainers build capability

    They build advanced expertise and spread it through coaching, targeted guidance and informal learning.

  • Early adopters create momentum

    They explore new tools, test new ways of working, share feedback and show how AI applies to everyday work.

Learners

The broader workforce

  1. 1Learn. A foundation in AI, responsible use and the available tools.
  2. 2Practice. Experiment in low-risk settings to build confidence.
  3. 3Apply. Bring AI into everyday tasks to improve quality and problem-solving.
  4. 4Create value. Share what works and contribute to team and organizational outcomes.

How leaders shift, from their own work to the enterprise

For leader conversations: how leaders work (head) and how they lead (heart).

ScopeHead shift: how leaders workHeart shift: how leaders lead
Foundation: a common languageA shared AI foundation: mindset, productivity and use casesThe role of leaders: co-create the organization's why story
AI for meDay in the life: apply AI to your own work and projectsPsychological safety: address concerns and fears about AI
AI for the teamTeam practice: set expectations and practice on real workFunctional leadership: build team rituals and a culture where failing safely is fine
AI for the enterpriseEnterprise value chain: redesign how people and AI create valueCulture of experimentation: build experimentation into daily work
The road aheadEnterprise roadmap: set priorities and next stepsLeadership activation: commit to an AI-fluent organization
HowHow it keeps going

Technology, governance and ritualsthat keep pace with AI.

Tech and data

Tools that bring fluency into daily work and measure adoption and value.

Capgemini demonstrator and cockpit demo, synthetic data.

Governance

The framework to scale AI safely, responsibly and within your standards.

  • AccountabilityClear responsibility for AI safety, compliance and governance decisions.
  • GuardrailsStandards, controls and approved use cases for AI across the organization.
  • OversightRisks reviewed and controls adjusted as AI capabilities change.

Process and rituals

The cadence that keeps capabilities, learning and adoption moving.

  1. 1. Refresh learningKeep content, guidance and good practice current as AI changes.
  2. 2. Evolve workflowsAdapt ways of working to new AI capabilities and opportunities.
  3. 3. Scale innovationA repeatable way to evaluate, prioritize and deploy new AI ideas.
Certification path

Five belts,each one opening the next.

Learning, practice and visible behavior all count. Belts show progress in the hub and in the cockpit. They are never used to assess individual performance.

  1. White belt

    AI literacy and safe use

    How to earn

    Literacy
    Foundations pathways
    Gamification
    One weekly quiz
    Reinforcement
    Not required
  2. Yellow belt

    AI experimentation

    How to earn

    Literacy
    Experimenter pathway and two learning labs
    Gamification
    Five daily challenges
    Reinforcement
    One manager kudos
  3. Green belt

    Applied AI proactivity

    How to earn

    Literacy
    Practitioner pathway
    Gamification
    Ten daily challenges and a prompt-a-thon
    Reinforcement
    Two manager kudos
  4. Blue belt

    AI implementation

    How to earn

    Literacy
    Expert pathway
    Gamification
    A hackathon
    Reinforcement
    Lead one fluency initiative
  5. Black belt

    Enterprise AI transformation leader

    How to earn

    Literacy
    Support learning labs and drive adoption in a function
    Gamification
    Ten daily challenges and a weekly quiz
    Reinforcement
    Lead three fluency initiatives

Literacy: training completion. Gamification: streaks and leaderboard. Reinforcement: behavior demonstrated.

Three phases

Three phases, from a pilot groupto an AI-native organization.

  1. 1Near term

    Foundation

    A pilot group is enabled

    • Set the plan for AI enablement
    • Build the core learning assets
    • Run the first hands-on pilots

    Works toward: A common language and the core assets.

  2. 2Mid term

    Scaling

    A wider population is enabled

    • Build out the full set of enablers
    • Learning paths for every fluency level
    • First wins with specific AI products and use cases

    Works toward: Compliance and risk under control, and employee productivity.

  3. 3Long term

    Embedded

    Ongoing enablement

    • Communities of practice that sustain themselves
    • Learning that keeps pace with innovation
    • Governance built into how work is done

    Works toward: Cost reduction, revenue and innovation.

What you bring

  • An executive sponsor
  • Business and persona representatives for interviews and reviews
  • Access to the approved AI tools for learners and facilitators
  • Capacity to publish learning in your LMS
  • Owners for content, data and support
Responsible use and platforms

Responsible use

  • Learning and the agent use only approved tools and approved content.
  • Engagement and learning data are reported in aggregate. They are never used to rank or assess individual employee performance.
  • Estimates are labeled as estimates, and data freshness is shown.

Platforms

Built and proven on Microsoft Copilot.

The framework and content carry to Claude and Gemini. Integrations are adapted and tested per platform.

For other AI platforms, we assess fit and integration effort with you before committing to scope.