Published
Piyush Mehta, CHRO and Country Manager, India for Genpact, shares how Genpact is transforming its HR function through AI, skills intelligence, workforce insights, and a connected data foundation, to support its journey toward becoming an autonomous enterprise.
As organizations look to accelerate AI adoption at scale, many are discovering that technology alone is not the primary constraint. Legacy operating models, fragmented workforce data, disconnected systems, and accumulated enterprise debts often limit transformation before AI initiatives can scale.
In this Everest Group Practitioner's Perspective, Arkadev Basak, Partner, HR & Talent, Everest Group, sits down with Piyush Mehta, as they explore how we are transforming our HR function as Client Zero, applying internally the approaches and advanced technology solutions we use to help clients address similar challenges.
The conversation offers a candid look at what we learned by doing the work ourselves – from simplifying HR operations and reducing talent debt to creating a skills-led workforce model that supports business agility and growth.
Download the report to learn how Genpact approached HR transformation as Client Zero and the lessons that may help leaders address enterprise debt, strengthen skills intelligence, and prepare for a more autonomous enterprise.
Key takeaways:
Apply Client Zero as a transformation strategy: Genpact applies transformation principles internally as Client Zero, using its own HR journey to inform how it helps clients address similar challenges
Address enterprise debt before scaling AI: The journey began with simplification, reducing complexity across processes, applications, integrations, and workforce data to establish a trusted foundation for AI adoption
Build a skills-led workforce model: By connecting skills intelligence, learning, workforce planning, and internal mobility, Genpact created a more adaptive workforce capable of responding to changing business demand
Reimagine HR as an enterprise capability: The transformation demonstrated that workforce, technology, operating model, and data decisions must evolve together to accelerate progress toward the autonomous enterprise