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From Silos to Pods: Scaling AI in Life Sciences

Cross-functional collaboration is the real differentiator between those that see meaningful returns and those that don’t.

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From Silos to Pods: Scaling AI in Life Sciences
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Life sciences organizations have long operated in functional silos. But now, AI is breaking those boundaries down. Business leaders are exhibiting unprecedented demand for deeper partnership and joint ownership with technology teams.

Most pharma and medtech organizations understand the need for executive-level oversight of AI programs. But it's ongoing cross-functional collaboration at the team level that's helping successful scalers—companies that deploy AI at scale and see meaningful returns—pull further ahead of early explorers, or companies with limited AI deployment and minimal measured value.

AI leaders know that innovating in isolation won’t cut it anymore. These organizations are around five times more likely to have replaced ad hoc cross-functional interactions with an ongoing, embedded operating model that more closely mirrors how software organizations work. They are adopting Agile development pods that unite AI experts, tech talent, business and process owners, transformation leads, and HR and talent leads. Successful scalers are also twice as likely to embed AI liaisons in every business unit. The result is faster development, smarter workflows, higher organization-wide AI adoption, clear plans for a hybrid workforce of the future, and, most important, tangible value.

Related

In Life Sciences, AI Moves Fast, but Only When Leaders Do

Why do some companies struggle to successfully scale AI? A lack of leadership buy-in.

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