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Build AI fluency across the organization

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We help leaders guide the transition, enable employees to improve real work with AI, and put the internal structures in place for adoption to continue long after the initial engagement.

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  1. Strategy & Vision

    Strategy & Vision decides what should change and why.

  2. Literacy & Enablement

    Literacy & Enablement helps people develop the practice and judgment to work differently.

  3. Design & Build

    Design & Build turns the redesigned work into production systems.

  4. Operate & Enhance

    Operate & Enhance keeps those systems reliable and uses production evidence to improve them.

AI adoption commonly falls short because of four gaps

Organizations often invest in technology without building the human capability and operating discipline required to make it valuable. Initial enthusiasm fades, usage remains concentrated among a handful of early adopters, and teams return to familiar ways of working.

  • The adoption gap

    Tools launch but never become part of everyday work, because people lack the skills, context or support to use them.

    Closed byHands-on application and coaching

  • The confidence gap

    A few advanced users pull ahead while most people are unsure what AI can do, when to use it and how to check its output.

    Closed byOrganization-wide literacy

  • The application gap

    Generic training teaches features and prompting without connecting them to each role's real tasks and decisions.

    Closed byRole-based learning

  • The operating gap

    Governance exists on paper but not in daily behavior. Ownership is unclear and nobody improves how AI is used.

    Closed byChampions and adoption routines

Enablement from the leadership team to every function

We combine leadership enablement, enterprise-wide literacy, practical application, and sustained change management to embed AI into how the organization works.

Leadership enablement

Hands-on fluency for leaders, plus clear sponsorship, accountability and ways to fund what works.

Organization-wide literacy

A shared vocabulary, baseline skill with your approved tools, and judgment about when AI is and isn't the right call.

Role-based learning

Paths built on each function's real workflows, from first steps to advanced use.

Champions and adoption routines

Internal leaders, playbooks and governance in daily practice, so adoption keeps going after formal training.

How we build practice that lasts

We use a capability-building process designed to move people from awareness to confident application and, ultimately, internal ownership.

01 · Listen

Learn how each team works before teaching anything

We talk with leaders and teams, role by role, to see where AI already helps, where it should not be used, and where confidence is uneven. Leaders agree on what the effort should achieve and how progress will be measured.

What you get

  • An AI fluency baseline by role
  • The tasks each team wants help with
  • Leadership goals and success measures
  • Early adopters who could become champions

02 · Practice

Build skill on the work each team does every week

Leadership sessions and role-specific workshops run on real tasks, not a generic curriculum. People practice responsible use and learn to judge AI output, not just write prompts.

What you get

  • Leadership enablement sessions
  • Role-specific workshops
  • Recorded sessions for everyone
  • Playbooks and reference guides

03 · Apply

Use AI on real work and measure what changes

Teams pick tasks from their own work, build the prompts and workflows, and test them where they will be used. What works is written down so other teams can reuse it.

What you get

  • Team-built workflows and prompts
  • Measured results for each workflow
  • A shared library of what works

04 · Support

Keep support in place after the workshops end

Coaching cohorts, 1:1 coaching and office hours help new habits stick. We train internal champions and set up a center of excellence, a small internal group that owns AI practice, so support does not depend on us.

What you get

  • Coaching cohorts and 1:1 coaching
  • Office hours
  • Trained internal champions
  • A center-of-excellence charter

05 · Raise the standard

Define what good work looks like, then raise it

We measure adoption against the baseline and set out what good AI-assisted work looks like in each role. Learning is refreshed as tools and policies change, and what works spreads to new teams and new hires.

What you get

  • Adoption measured against the baseline
  • Quality standards for AI-assisted work by role
  • Refresher and advanced sessions
  • Onboarding materials for new employees

Four programs, one for every level of the organization

Not everyone needs the same depth, but every level needs a role in adoption. Start at the step that fits.

  1. 1 · Align leadership

    ExecOS Training

    Leaders get personally fluent and leave with a productivity system they run themselves.

    Four working sessions · Leadership team

  2. 2 · Build the foundation

    AI Fluency at Scale

    Capable, responsible AI use becomes the standard across the organization.

    Scoped per engagement · Everyone

  3. 3 · Develop integration leaders

    AI Integration Leadership Program

    Confident users become leaders who drive AI integration in their own function.

    8–12 weeks · About 25 per cohort

  4. 4 · Keep adoption going

    AI Champions Program

    Facilitated cohorts build solutions their teams use, while leadership funds what they surface.

    Monthly, per cohort · Ongoing cohorts

What our clients say

“They opened our eyes to using AI completely differently.”
Megan BrandowDirector of Marketing
“Dual Logic created a structured approach that combined foundational AI fluency, communities of practice, and team-specific working sessions focused on building real solutions.”
Jonas HirshfieldChief Information Officer
“We moved faster on AI in months than I thought possible.”
Debra BenAvramChief Executive Officer

The services follow the life of the work

The sequence is useful, but it is not mandatory. We enter where the need is clearest, then connect the work to whatever must come before or after it.

  1. Strategy & Vision

    Strategy & Vision decides what should change and why.

    Explore Strategy & Vision
  2. Literacy & Enablement

    Literacy & Enablement helps people develop the practice and judgment to work differently.

    You’re here
  3. Design & Build

    Design & Build turns the redesigned work into production systems.

    Explore Design & Build
  4. Operate & Enhance

    Operate & Enhance keeps those systems reliable and uses production evidence to improve them.

    Explore Operate & Enhance

Straight talk on AI strategy and the work that follows

Notes from our engagements on what works, what doesn’t, and what it takes to put AI to use.

Read the latestView all resources
Read the latestView all resources

The questions mid-market leaders ask first

Short answers on how engagements start, what they involve and how we work with your team. Ask us anything else directly.

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How is AI enablement different from AI training?

AI training teaches people how a tool works; AI enablement changes how they do their jobs with it. Dual Logic’s Literacy & Enablement work trains people on their real tasks and decisions, not generic features and prompting. Then coaching, internal champions and adoption routines keep the new habits going after the sessions end, so the capability stays with your team.

How long does an AI enablement program take, and how much time does it ask of people?

Dual Logic’s enablement programs range from four sessions to ongoing cohorts. ExecOS Training gives leaders four hands-on sessions of about an hour each, plus light practice between them. The AI Integration Leadership Program runs 8 to 12 weeks at about five hours a week per participant. The AI Champions Program runs monthly per cohort, and AI Fluency at Scale is scoped to your organization.

Should AI training start with the leadership team or with everyone?

Many organizations start AI training with the leadership team, so leaders can model credible use and know what to fund next. But every level needs a role in adoption, even if not the same depth. Organization-wide literacy gives everyone a shared vocabulary and baseline skill, and role-based paths build on each function’s real workflows. You can start at whichever step fits.

Which AI tools does Dual Logic train people on?

Dual Logic trains people on the AI tools your organization has approved, such as Microsoft 365 Copilot, Google Gemini, ChatGPT or Claude. ExecOS Training, for leaders, builds each person’s productivity system in Claude or Codex. Every program teaches judgment as well as features: when AI is and isn’t the right call, and how to check its output before using it.

How does Dual Logic measure whether AI training worked?

Dual Logic measures AI training by what changes in the work, not by attendance. Each engagement starts with an AI fluency baseline by role, and adoption is measured against it using real usage data. AI Fluency at Scale adds a certification that makes “fluent” measurable. Skills and readiness results are reported separately from operational and financial ones, so each is judged on its own terms.

What happens after an AI training program ends?

After a Dual Logic training program, internal champions keep adoption going. We train them to support their colleagues with playbooks and adoption routines, so governance becomes daily practice rather than a document. Coaching and office hours continue where they’re useful, and the AI Champions Program can carry the work on monthly, with cohorts building solutions their teams use while leadership funds what they surface.

Can people with no technical background take part in AI training?

Yes, Dual Logic’s AI training is built for people with no technical background. It starts with a shared vocabulary and baseline skill with your approved tools, and ExecOS Training assumes no prior AI experience. Sessions use each team’s real work, so people learn on tasks they already know. Advanced users can go further through role-based paths.

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Start with a conversation.

Thirty minutes with a partner to talk through your priorities and a sensible first step.

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