Life science companies sift through large amounts of data to close the insight gap and extract actionable insights – those inflection points that inform strategic decisions. Companies must be able to understand the data they are working with, how to use it, the models needed to interpret it, and tease out the business impact of these efforts. AI is often part of the solution, but misunderstandings about AI persist. What should industry leaders do to increase AI literacy in life science?
To best answer these questions and for business leaders and stakeholders to become more at ease with implementing AI strategies, they need to take a bite-sized approach.
“AI maximizes the time and money [life science companies have] invested,” writes Within3 CTO Jason Smith in Pharmaphorum, “driving business efficiencies and positive patient outcomes.” But achieving meaningful adoption means looking at AI not as a silver bullet but as a strategic tool to deliver incremental, compounding gains.
An incremental approach is critical for understanding the long-term value of AI and is key to establishing longevity in an AI strategy. Often, life science companies struggle with AI adoption because the business has positioned AI, and technology in general, as a blanket solution for every problem and inefficiency. “Blanket approaches make it difficult for business executives to measure and understand the return on their investments,” writes Smith. “And, subsequently, they make it difficult to communicate the value to end consumers.”
Being realistic about AI applications, which comes from understanding what AI is and what it can do, elevates the ability of life sciences companies to make the most of the data at their disposal and get products onto the market faster and safer.
Smith points out that when used intelligently, AI can accelerate efficiency. “Once businesses can apply it to one problem, applying it to the next becomes considerably easier.” Life science teams can build confidence and avoid mistakes with this bite-sized approach – one where companies set realistic targets, regularly reflect on progress made, and share learnings with stakeholders.
Read the full article in Pharmaphorum.
