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Optimize your real competitive advantage:
the human in the loop.

Leaders facilitate change. Torch coaches leaders at scale, facilitating organizational adoption and execution.

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Two colleagues talking through their work at a sunlit office table, a stock photograph
New tools.
Human judgment.
A different way to work.

What is AI-adoption
coaching at Torch?

AI-adoption coaching helps leaders turn an AI strategy into decisions, conversations and working habits. A coach can help a leader understand hesitation, clarify expectations and plan a responsible experiment within company policy. The focus is the human work of adoption, not simply whether people have access to a tool.

It complements technical training, policy and implementation support; it does not replace them.

Strategy sets the direction.
Culture determines whether people move.

Make expectations clear.

Help leaders explain where AI should change the work and where human judgment remains essential.

Treat concerns as information.

Distinguish uncertainty from valid questions about quality, workload, accountability or risk.

Create room to try.

Choose bounded experiments people can discuss, review and improve within your policies.

Make the next
change specific.

One proposed design runs across nine months, moving from a shared imperative to practice and review. Duration, coaching formats and cadence should adjust to the organization; this is not a fixed delivery commitment.

  1. Start with the work, not the tool.

    Choose a business priority, the workflows it affects and the decisions people need to make differently.

  2. Match experience to the transition.

    Agree the relevant technology and change experience for coach selection, then confirm the people, formats and cadence.

  3. Practice the moments that matter.

    Use coaching to prepare for questions, disagreements and workflow experiments within your organization’s AI policies.

  4. Review adoption and remove barriers.

    Consider agreed feedback and work measures together, distinguishing development needs from obstacles the business must resolve.

Business priorityCoach fitPracticeReview & adjustReturn to the work

Know what is changing,
and what is not.

Agree a baseline, review dates and evidence owners before launch. Keep confidence, observed behavior and actual workflow adoption separate.

A fuller picture of adoption.

Implementation

  • Workflow adoption
  • Lower-level task automation
  • Capstone development

Adoption

  • AI enthusiasm
  • AI familiarity
  • AI experimentation
Bring different evidence together.
Keep the measures distinct.
Illustrative implementation and adoption dimensions, carried forward from the earlier concept. Not customer data, a validated assessment, or product UI.

Leadership behavior

What do colleagues notice?

Ask relevant colleagues about specific behaviors, such as inviting concerns or explaining decision boundaries.

Changes in the workflow

What changes in the work?

Use approved business data to review agreed experiments, repeated use and quality or rework measures.

Participant perspective

What does the leader report?

Review self-reported confidence and goal progress as experience measures, not proof of adoption or financial return.

Prepare for the question
beneath the resistance.

Optional Spark AI can support participant-led reflection and rehearsal. This illustrative exchange does not use a human-session transcript.

Explore Spark AI

Human judgment stays in the loop.
Practice stays within your policies.

Leader

My team thinks using AI for first drafts means their judgment no longer matters. I need to introduce a pilot without dismissing that concern.

Spark

What judgment will they still own, and what boundaries can you make explicit?

Leader

They will check the evidence and decide what reaches the client. We will use approved tools and only permitted information.

Spark

Try opening with those responsibilities, then ask which part of the pilot needs a clearer safeguard.

Take it into the work.

Agree one permitted drafting experiment and who reviews its output.

After the experiment, discuss quality, effort and concerns before deciding what to repeat.

Select for the technology, leadership and organizational-change experience your program requires. Confirm the available coaches and their fit before launch.

Experienced leaders. Worth your leaders’ time.

  • Every coach is ICF-credentialed
  • At least five years of coaching experience
  • Industry leaders with first-hand experience
  • Many doctoral-qualified psychologists and therapists
  • Matched to leaders and their responsibilities
Meet our coaches

  • Coach Sandeep

    Led businesses at Gap Inc. and Mars before coaching C-suite leaders and founders. MBA, Georgetown.

    Previously at
    Gap Inc. Mars The Body Shop

  • Coach Evelyn

    Former CEO of The RNA Society and COO of Parkinson Wellness Recovery. PhD, Cornell.

    Previously at
    RNA Society Parkinson Wellness Recovery American Chemical Society

  • Coach Rafal

    Former Chief Learning Officer at Deloitte Switzerland and Vice President at Barclays. ICF Master Certified Coach.

    Previously at
    Deloitte Barclays JP Morgan

  • Coach Sheryl

    Former Executive Vice President at Wells Fargo and Managing Director at Barclays.

    Previously at
    Wells Fargo Barclays UBS

  • Coach Jorge

    Former CEO of Axion Energy, a BP joint venture, and SVP of Global Strategic Partnerships at BP.

    Previously at
    Castrol BP Axion Energy

  • Coach Sophia

    Former Vice President and Business Unit CFO at Kraft Heinz.

    Previously at
    Kraft Heinz Procter & Gamble Walker & Company

  • Coach Jon

    Former Partner at Bain & Company and The Bridgespan Group.

    Previously at
    Bain & Company The Bridgespan Group Bannock Consulting

  • Coach Shirley

    Former Chief People Officer at Zadara and Callisto Media. PhD, Organizational Psychology.

    Previously at
    Zadara Callisto Media

  • Coach Andrew

    Former Chief Technology Officer at Parametric and COO at Synoptic Data.

    Previously at
    Parametric Microsoft Synoptic Data

  • Coach Anita

    Former Partner in Accenture's global strategy practice and Head of Innovation at KPMG Strategy.

    Previously at
    Accenture KPMG

  • Coach Shamar

    Led coaching and development programs at AvidXchange and GEICO. U.S. Navy veteran.

    Previously at
    AvidXchange GEICO U.S. Navy

  • Coach Marie

    Former Head of Commercial Excellence at Merck and Head of Marketing at Novartis.

    Previously at
    Novartis Merck

  • Coach Kevin

    Former VP of Product Management at BILL and Head of Global Product Marketing for QuickBooks at Intuit.

    Previously at
    BILL Intuit LinkedIn

  • Coach April

    Former Director of R&D at Johnson & Johnson. PhD, Organizational Leadership.

    Previously at
    Johnson & Johnson OraPharma Delaware Valley University

  • Coach Don

    Former Executive Vice President and COO at Gateway Ticketing Systems; led IT at Universal Orlando Resort and Walt Disney World.

    Previously at
    Gateway Ticketing Systems Walt Disney World Universal Orlando Resort

  • Coach Catherine

    Former APAC Chief Strategy Officer at Siemens Industry Software and regional director at IBM.

    Previously at
    Siemens IBM Cisco Systems

  • Coach Frank

    Former VP of Professional Services for North America at Unit4 and VP of Customer Success at Actifio.

    Previously at
    Unit4 SAP SuccessFactors Actifio

  • Coach Vanessa

    Former Chief Human Resources Officer and Chief Operating Officer. Executive coaching certificate, Columbia University.

    Previously at
    Michaud Cooley Erickson Wayside Recovery Center Control Data Corporation

  • Coach Jeff

    Former President of Healthcare Solutions at Budco Financial and VP of Marketing and Product Development at Dialog Direct.

    Previously at
    Budco Financial Dialog Direct

  • Coach Andrea

    Former Senior Director of Direct-to-Consumer Marketing at Procter & Gamble.

    Previously at
    Procter & Gamble PayPal

A related case on participant confidence and coaching experience, not evidence of faster AI adoption.

Explore the related case

Questions about coaching for AI adoption.

Does this teach people how to use AI tools?

It addresses the leadership and behavior side of adoption. Your technical teams retain responsibility for tool training, policy, security and implementation.

Is this a fixed nine-month program?

Nine months is one proposed design, not a standard delivery commitment. Agree the scope, coaching mix and cadence around your readiness, priorities and available time.

What would the organization see?

Agree the measures, review inputs, audience and permissions before launch. A program review does not imply access to private coaching conversations or automatic analysis of them.

What should an AI-readiness coaching program measure?

Track confidence, behavior and implementation separately. A leader may feel more confident before a team changes its workflow. Agree which approved experiments, working practices or business measures matter, and review them alongside participant and colleague feedback. The adoption graphic on this page is illustrative, not a customer result or validated assessment.

What should we look for in an AI-adoption coach?

Look for experience leading people through technology change, the ability to question assumptions and the judgment to work within your organization’s AI policies. Discuss the relevant industry and leadership background during matching. A coach supports leadership development; technical, security and policy decisions remain with your organization’s responsible teams.

What is Torch?

Torch is a leadership coaching and alignment platform for organizations developing their people through change. Experienced human coaches support practical development around the work, with optional Spark AI for reflection and rehearsal.

What needs to change
after the tools arrive?

Start with the work your people need to approach differently.

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