AI Update: What’s Your AI Adoption Strategy?
AI is accelerating every aspect of the life sciences, and companies in pharma and diagnostics are preparing for the transformation.
So far this year, Indianapolis’ own Eli Lilly and Company joined NVIDIA in investing $1 billion in a co-innovation lab, and Roche announced the expansion of its global AI infrastructure with a NVIDIA AI factory. Meanwhile, AI companies are investing in life sciences: Claude creator Anthropic recently acquired Dimension-backed startup Coefficient Bio for $400 million.
What’s your plan for adapting to AI? Two recent surveys from NVIDIA and WRITER offer insights about adoption and strategies for approaching AI strategy amidst rapid change.
Life sciences perspective
NVIDIA’s second annual State of AI in Healthcare and Life Sciences survey report offers a pulse check on how organizations are adapting to AI. Drawn from 600+ respondents in life sciences and healthcare, the survey found that 70% of organizations are actively using AI. Other highlights include:
- 69% said they’re using generative AI and large language models
- 82% said open source software and models are moderately to extremely important to their organizations’ AI strategy
- 85% of executives said AI is helping increase revenue
Workforce implications
It’s clear AI is fueling changes in the life sciences and beyond, and many of those changes relate to the workforce — and layoffs. A new global AI adoption survey from WRITER showed that 60% of companies plan to lay off employees who won’t adopt AI, and 77% of executives who resist AI won’t be considered for promotions or leadership roles. Fast Company offered perspective on the survey and how companies are adapting.
Building an AI adoption strategy
What’s the best way to adapt to AI in your business? Here are four tips gleaned from the articles:
- Treat AI as business transformation rather than a technology rollout. Focus on aligning AI initiatives with measurable business outcomes, ensuring investments are tied to growth and operational improvements rather than experimentation alone. “The organizations seeing impact are those that embed AI into existing workflows instead of layering AI on top as a separate tool,” said Dr. Annabelle Painter, clinical AI strategy lead at Visiba U.K.
- Start with administrative streamlining. In the next year, the most visible and scalable impact of AI will come from logistics and administrative streamlining, said John Nosta, president of NostaLab, a healthcare think tank. “That’s where adoption curves are already steep.” Focus on tasks like documentation and coding.
- Encourage experimentation, but set guardrails. The most successful approaches to AI adoption empower employees to experiment with AI tools while providing clear guardrails. Establishing governance frameworks for AI systems ensures innovation won’t outpace oversight. Approaching AI adoption as both a top-down and bottom-up effort empowers people at all levels to learn and grow.
- Deploy AI thoughtfully. “Open models will shape the intellectual field,” Nosta said. They’re essential for exploration and “keeping the field honest.” But in clinical environments where safety, liability and accountability are nonnegotiable, “proprietary systems will remain necessary for validation, integration and trust.” In other words: Deployment demands stewardship.
At ASG, we take a thoughtful approach to AI adoption. “AI is a support tool, not an author or owner of ideas,” said Meagan Koeneman, marketing and business development lead. “It helps us with research, clarity and efficiency, but it doesn’t replace expertise, creative voice or accountability.”
How are you adapting to AI in your business?
Read NVIDIA’s article and download the report. Read Fast Company’s article about AI adoption in the workplace.
