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February 13, 2023

Within3 in Datanami: how pharma should think about AI

A company’s decision on how to apply AI significantly impacts the outcome of AI investment.
approach to artificial intelligence

The life science industry is eager to leverage the power of artificial intelligence to make drug development faster and more accurate. And while many pharma companies are investing in their own AI initiatives or looking for startups with promising technology, questions remain about when and how to apply it most effectively. Recently in Datanami, Within3 CTO Jason Smith makes a case for a considered approach to artificial intelligence. “In today’s corporate world, for a business model to not include AI as a strategic business objective is about as incongruous as a mathematician with arithmophobia,” says Smith.

The pressure to leverage AI to produce transformative results is a heavy burden for organizations and will only intensify if expectations and reality are misaligned. Thus, Smith recommends an incremental approach founded on key principles of aligning strategic business goals to the practical implementation of AI.

“Building AI solutions in stages with various resources, whether it is human feedback or changing computational resources,” says Smith, “allows AI to improve performance and results.”

A successful, incremental AI approach typically includes the following: customer interviews, testing and validation, and initial deployment to a limited user group.

“If users can provide feedback on how the AI was delivering value…the information will prove highly valuable.”

Incremental steps are key in establishing best practices and ROI, writes Smith. While the promise of AI is great, it won’t happen overnight – measuring and quantifying small wins holds the promise of tapping into the true and potentially life-altering benefits of artificial intelligence.

Read the full article.

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