The explosive growth of Gen AI has caused plenty of consternation as well as celebration, but there’s no turning back the clock on this far-reaching technology This summer marked 50 years since the design of the internet was released in a paper by Vint Cerf and Robert Kahn. That work on a protocol, architecture and philosophy for the sharing of resources between different networks was foundational to today’s world.

Over the following five decades since Cerf and Kahn’s publication we’ve certainly come a long way and there have been a steady stream of major technological milestones. Those taking us towards the central place online tech occupies today include the first mobile phone in 1983 and 1991’s invention of the World Wide Web, with many more important steps that could be added to that short list.

One of the most recent developments was the public release of Chat-GPT in November 2022 and the subsequent explosion of interest in, and applications for, generative AI (Gen AI). Fuelling this new world has been the proliferation of data – both structured and unstructured – which underpins all Gen AI applications in their quest to speed, simplify, summarise and otherwise support individuals and businesses.

Today, Gen AI is cutting a swathe through almost every sector, including – of course – life sciences and healthcare. What’s particularly noteworthy about Gen AI is the lightning speed with which it’s hit the mainstream, and the last two years have been like no other period in the more than two decades that I’ve been writing about and commentating on ‘digital pharma’.

However, there are many important considerations for commercial pharma executives if they are to benefit from the ascendence of Gen AI in life sciences, starting with the need to assess the current position of this fast-moving technology.

Preparing to succeed with AI in pharma
The current state of AI will likely have changed by the time you read these words, and it will certainly keep changing. Today, there’s such a proliferation of data and the use of Gen AI capabilities that many people already view Chat-GPT as old news. […]

Is Gen AI ready for life sciences?