Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Released Thursday, 7th August 2025
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Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey

Thursday, 7th August 2025
Good episode? Give it some love!
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What does it take to scale AI across a global enterprise without breaking what already works? And how do you unlock value at scale — without losing sight of people, processes, and trust?


On this season finale episode of Where AI Works, host Serguei Netessine speaks with

Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson, about how AI is transforming operations behind the scenes at the iconic global healthcare and medtech company. Together, they explore how shared services — spanning HR, finance, procurement, and more — are being reimagined through an AI-first lens, unlocking new value while improving speed, decision quality, and employee experience. They also discuss how GenAI tools like JAIDA are helping 138,000 employees navigate complex internal systems and policies, reducing friction and freeing up time for higher-value work. For business leaders navigating their own AI journeys, this episode offers a clear-eyed look at where to start, how to scale, and what it takes to turn AI from a technical experiment into a strategic operating capability.

 


Episode Highlights:


5:12 - Ajay explains how AI is being integrated into J&J’s processes and services, with a focus on improving complex interactions for the company’s 138,000 employees.


8:18 - Ajay discusses the KPIs — the “Three E framework” — that J&J uses to assess the effectiveness of its AI implementation efforts.


17:06 - Ajay lays out his four-point strategy for other business leaders who are looking to engage with traditional, generative, or agentic AI.

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