IndustryArticle 13Transformation

Most Gen AI Adoption Programs Are Missing the Workforce Rethink

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Organizations are deploying Gen AI tools into unchanged workforce structures and then wondering why productivity gains are modest.

Three Takeaways

  • 1

    Tool adoption is not transformation. Transformation requires redesigning the work around the tool.

  • 2

    The organizations with the highest Gen AI ROI redesigned roles before deploying technology.

  • 3

    Workforce rethink is not an HR program. It is a business decision with HR as the operating architect.

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Amrita Sandhu
April 23, 2026
6 min
302 words
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KPMG frames the Gen AI challenge correctly: realizing value requires a complete workforce rethink, not just technology deployment.

Most organizations are doing the reverse. They are deploying technology and treating workforce adjustment as a consequence rather than a precondition.

The Sequence Problem

Here is how most Gen AI adoption programs work: leadership approves a Gen AI investment, IT deploys the tool, employees receive training on how to use the tool, and adoption metrics are tracked.

Here is what is missing: the deliberate redesign of work that the tool is being deployed into.

Without that redesign, you get a powerful tool being used to do the same work slightly faster. This is automation, not transformation. The productivity gains are real but bounded.

The Correct Sequence

Organizations that extract the most value from Gen AI investments do something different. They start by asking: If this tool can do what the vendor says it can do, what should change about how this work gets done?

That question opens a design conversation. It surfaces assumptions about roles, workflows, and accountability structures. It reveals where the real value is.

Then they deploy the tool into the redesigned work.

Why This Is Hard

This sequence requires organizations to have operating model design capability. Most do not. They have technology deployment capability and change management capability. These are necessary but not sufficient.

Operating model design requires understanding how decisions get made, where accountability lives, and how work actually flows. It requires someone who can hold the system view.

The Gap Is Not Technical

The organizations struggling with Gen AI ROI do not have a technology problem. They have an operating model design problem. The tools are capable. The organizations are not configured to use them.

Source: KPMG, "HR holds the keys to creating value from generative AI," 2024

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Disclaimer: The views and opinions expressed in this article are for informational purposes only and do not constitute professional advice. Readers should consult with qualified professionals before making any decisions based on this content.

About the Author

Amrita Sandhu brings 22 years of experience in organizational transformation, talent strategy, and enterprise architecture. She has held senior leadership roles at JPMorgan Chase, Nomura, and McKinsey & Company, leading transformations across 100,000+ employees and delivering significant organizational impact through structured change management and governance frameworks.

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