Post by Som Sarangi

Back in January, we launched our research on AI in biopharma R&D. A few months on, what’s striking isn’t the level of ambition—we continue to see that everywhere in client conversations. 𝐈𝐭’𝐬 𝐭𝐡𝐞 𝐠𝐚𝐩 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐢𝐧𝐭𝐞𝐧𝐭 𝐚𝐧𝐝 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧. Across the industry, leaders are aligned on the potential of AI. But the discussion has shifted. It’s no longer “𝘥𝘰𝘦𝘴 𝘪𝘵 𝘸𝘰𝘳𝘬?” — it’s “𝘩𝘰𝘸 𝘥𝘰 𝘸𝘦 𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘢𝘭𝘪𝘴𝘦 𝘪𝘵 𝘢𝘵 𝘴𝘤𝘢𝘭𝘦?” What we’re hearing from clients now is consistent: ▶️ Data readiness is still the biggest constraint 🎗️ Operating models haven’t caught up with the ambition 🧑‍✈️ And too much AI remains trapped in pilots rather than powering core workflows The organisations starting to pull ahead are treating AI less as an innovation agenda and more 𝐚𝐬 𝐚𝐧 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐲, embedding it into R&D processes, decision-making, and ways of working. That’s where the real shift is happening. Let me know how you feel about this? And if you’d like a deep dive on this topic, our latest research report should have you covered: https://bit.ly/4vh52u2 Rob Pears Jo Coppins Henal Shah (She-Her) Megha Dutt Therés Gårdenborg Justin Melnick Ivana Knyght Arry Balachandran (MCMI ChMC) Gert-Jan Schoppert Georgie Cusack Anusha Karande Ella Broome Charlene Engelbrecht Sagar K. Bharat Bhusan Swain Thorsten Alexander Rall

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