Over 400 delegates arrived in Dubrovnik this May with AI on their minds. The NextPharma Summit promised a window into the future of life sciences: faster launches, deeper customer relationships, and more innovative commercial models. And yet, as the sessions unfolded, it became clear that a fundamental truth had been perhaps overlooked.
Everyone spoke of artificial intelligence. Some acknowledged the foundational data capability needed to support it. Everyone referenced cross-functional engagement as a key to success. Few asked whether our teams were working with the coherent, accessible, and orchestrated customer knowledge that enables it. At the root of this dissonance is a technology we once celebrated and now ignore: the CRM.
For over a decade, we treated CRM as a compliance box, a sales force tracker, and an archive. Today, it has become a graveyard of siloed screens. And that matters because CRM is no longer a passive tool. It is the starting point of every conversation with HCPs, the root of every insight, and the nexus of every AI use case we claim to pursue within commercial operations. Moreover, the war announced between Veeva and Salesforce and a new contender to save the day, such as Microsoft, makes the Commercial Ops team truly wonder if this is going to take time and effort in the next few months for another transition.
By design, CRMs must become the fabric for making pharma a data-driven organisation. We often hear we have data (or buy it), but do we? Really? It seems the data we seems having is frozen, in duplicated silos and therefore far from being a currency that can augment value from one department to the other. This core layer from which microservices, intelligent automation, and agent-to-agent (A2A) ecosystems are born seems to be far from being set and understood. Without it, our AI efforts are sandcastles in the tide. Without it, our field forces are flying blind.
Over those two days in Dubrovnik, what stood out was the way commercial leaders are beginning to connect the dots between ambition and adoption. It became clear that the transformation engine is not the technology itself, but the precision with which we align it to how people work, decide, and deliver in the field. This is about making things click—between teams, between systems, and most importantly, between intent and impact.
