Make-or-break moments for pharmaceutical companies: How artificial intelligence is rewriting the rules of customer engagement

Human connections have always been the key to meaningful customer interactions in the pharmaceutical industry. No channel can match the impact of well-prepared, well-supported representatives. Our research shows that up to 70% of influencer sales are driven by on-site engagement – far more than direct-to-consumer (DTC) or impersonal promotions. However, sales reps are dealing with fragmented customer relationship management (CRM) systems and incomplete data. Only a quarter of field teams felt fully supported by the CRM, indicating that the site needed modernization. After years of cobbling together tools, the space is looking for a seamless omnichannel experience that can be guided.

We’ve reached a point where representatives can walk into a meeting with a single AI-curated brief that blends medical insights, market trends and previous interactions. Instant guidance can display compliance content and suggest key points based on real-time signals and digital sequences that trigger actual landings after the call. AI can predict needs, recommend the next best action, and connect what happens on the call to what happens in the digital channel. It makes every interaction clearer, more timely, and more relevant.

But AI alone will not achieve the reshaping the industry needs. The real transformation is organizational: redesigning roles, workflows, and governance so that AI becomes connective tissue across teams rather than an add-on tool.

This coordination is important because the stakes are high. Pharmaceutical companies face a once-in-a-decade opportunity to move away from traditional CRM and fragmented engagement models and create products that are more intelligent, coordinated and insight-driven. Those who act first will reduce service costs, increase rep productivity, and deliver a personalized rather than programmatic customer experience. Those who wait may risk falling behind as competitors turn engagement into a true differentiator.

Artificial intelligence changes the way work is done

Discussions about artificial intelligence in the pharmaceutical industry often focus on tools and capabilities. But the deeper story is about the work itself. Artificial intelligence doesn’t just automate tasks; It reshapes roles, ways of working, decision-making authority and how talent is deployed. It empowers people and eliminates low-value work, freeing up time for higher-value interactions. This means leaders must view this as a transformation of the operating model (skills, incentives, workflows) rather than the rollout of a point solution. Reinvention is organizational, not just technical.

Consider the ripple effects: Medical affairs, marketing and field teams working on a shared data backbone rather than siled systems. Compliance guardrails are embedded in AI workflows to reduce risk while speeding execution. A governance model that defines how human judgment and machine intelligence intersect. These changes are not optional—they are prerequisites for AI to work at scale.

What does this look like on the ground? It starts with clearer call preparation: providing customer context, intent signals, and recommended talking points in one view. During the interaction, AI can display next-best actions and compliant content in real-time, helping reps adjust as the conversation evolves. After the call ends, AI can trigger personalized digital sequences that extend the conversation and keep customers engaged. The result is not just more contacts, but a better journey, with each interaction building on the last.

This shift also changes the way success is measured. Volume metrics (number of calls, emails) are giving way to effectiveness metrics: Did the interaction deliver value to the customer? Does it foster relationships? AI makes these issues measurable by connecting engagement data across channels and providing critical insights.

The value of doing this correctly

Why is this important now? Because the economics of participation are under pressure. Service costs continue to rise, while customer expectations for relevance and speed continue to rise. Reinventing AI engagement isn’t just about efficiency, it’s about growth. Companies that do this will unlock new pools of value by improving how they engage, not just how engaged they are. They will move from decentralized, reactive models to insights-driven systems that anticipate demand and coordinate responses across the enterprise.

The rewards are clear: lower service costs, higher sales rep productivity, and a more consistent, personalized experience for customers. But the window is closing. The recent wave of platform shifts has exposed the fragility of traditional CRM backbones. AI-driven CRM now sets the pace, and hesitant leaders risk being left behind.

What leaders should do next

So where should leaders start? First, choose a journey that is critical to your reps (e.g., pre-call planning) and use AI to automate it end-to-end. Gauge your return to the court. Second, create a single “frontline brief” that consolidates medical, market and interaction data for each key account. Third, strengthen the feedback loop between field and marketing so that digital sequences adapt to what is actually happening on the call. Finally, establish lightweight governance for the use of AI—content control, compliance guardrails, human-computer interaction oversight. These initiatives are not glamorous, but they provide momentum and credibility for broader transformation.

bottom line

Reinventing customer engagement isn’t about replacing systems, it’s about designing work so that every interaction creates value for customers. AI can make this possible, but only if leaders view it as an enterprise-wide transformation rather than a technology project. Companies that do this will redefine what good looks like in pharmaceuticals and set new standards for the industry.

Photo: Thai Noipho, Getty Images

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