The biopharmaceutical industry has crossed the threshold into the AI era. As scientific and technological advancements accelerate, trials and data management complexity is growing exponentially. To keep pace with these trends, it is imperative to think of “AI native” processes or processes with intrinsic and trustworthy AI capabilities for achieving scalable outcomes.
And those who consider AI as a niche or leverage AI for a discrete set of use cases risk falling behind in a rapidly evolving landscape. AI technology is advancing at a groundbreaking pace. With the widespread commoditisation and applications of AI and the integration of chatbots like ChatGPT and Google’s Gemini into everyday life – from summarising search results to assisting users with several tasks by responding to queries or voice – AI is no longer viewed as an advanced technology, but is now an integral part of user experience and expectations and a necessity to pervasively embed for intelligence and automation at scale.
In life sciences and clinical development, this shift was gradual and then sudden. Teams no longer have the luxury of experimenting with AI, but must fully integrate it into core business processes and decisions. Soon, AI-driven innovation will be assumed and expected to address complex problems much like the internet, mobile revolution, or cloud computing.
The pressure on clinical development to reduce cycle times while doing more with less is intensifying. Advances in science an.
