The next era in life sciences: agentic AI and other innovations transforming HCP engagement

Biopharma leaders anticipate a significant impact from their AI investments. In fact, our research shows 86% forecast a 5%+ sales uplift and 55% expect 10%+ cost savings.  However, for many organisations, the promise of AI has stalled as pilots fail to scale, undermining potential ROI. MIT research highlights a stark 95% failure rate for enterprise AI projects, as companies often rely on generic, stand-alone tools with high adoption but low transformation of real-world processes.

The industry is now entering the next era by embedding AI directly into the software field teams’ use every day. The step change is led by biopharmas deeply integrating agentic AI into critical commercial processes. Only when the system can adapt to context, maintain governance and improve over time through learning loops will it be possible to scale AI beyond isolated pilots to deliver the promised value in a compliant way.

A unified technology foundation with AI built at its core and real-time access to data and content empowers complex field teams for coordinated intelligence-driven engagement. Embedded AI agents go beyond simple responses by proactively connecting signals, anticipating needs and taking action, increasing productivity and precision. These innovations transform how sales, marketing and medical functions collaborate and engage with healthcare professionals (HCPs).

Coordinating HCP engagement begins when sales, marketing and medical teams have a single customer view in an omnichannel CRM with connected data and content.  Embedding agentic AI into this unified platform enables companies to act with rapid precision, ensuring valuable and timely HCP interactions.

Biopharmas are focusing on highly specialised AI agents for industry-specific use cases, including pre-call engagement planning, semantic search across content and media libraries, voice-to-data entry records and capturing free-form notes compliantly. Integrating these agents directly in users’ applications streamlines everyday tasks.

Agentic AI built at the core of a unified platform understands context and enables dynamic orchestration. Real-time data helps to continuously coordinate activities adjusting the persona, the channel and content for a particular HCP. Building on previous interactions, third-party data, or sentiment analysis, AI agents can prioritise signals through a scoring system and proactively surface recommendations, automate CRM actions or trigger actions in external systems. These innovations transform how commercial teams work, delivering efficiency and effectiveness.

Scaling omnichannel engagement requires fast, personalised content, yet this often clashes with the time-intensive medical, legal and regulatory (MLR) review process. The industry is now shifting MLR from a bottleneck into a strategic enabler, reducing approval times while maintaining quality and compliance.

Embedding AI directly into content management applications helps accelerate the MLR process. Moderna has already implemented quick-check agents that automatically check content for compliance flags, reference validation and claim accuracy, allowing human experts to focus on complex areas. While AI streamlines the process, human expertise remains accountable, making change management and AI literacy training essential to successful AI investments.

The ability to scale AI and execute personalised, coordinated engagement depends entirely on the underlying data foundation. But today, 73% of biopharmas experience data quality challenges and 96% believe their data is not AI-ready.

To address this, many organisations are harmonising data globally by standardising and integrating data from different sources, countries and formats using a common data architecture. Bayer AG is building a new data model consolidating CRM history engagement data, third-party reference data and customer profiles in a global master data management platform that eliminates costly integrations and data fragmentation. This establishes a 360-degree customer view and breaks down data silos. Field teams not only get access to the entire customer master universe, they can also provide direct input for data changes, ensuring the latest customer information.

At the core of this strategy is trusted reference data. A globally harmonised source for accurate and comprehensive HCP and healthcare organisation profiles provides a clear picture of the customer landscape, unlocking scalable analytics. Transforming this wealth of information into actionable intelligence requires seamlessly connecting data and software. AI-ready data flowing into the CRM fuels faster insights and smarter commercial execution.

AI is no longer a promise, but a reality when embedded in users’ daily systems and processes. Agentic AI and other innovations are shaping the next era in life sciences by driving omnichannel orchestration, deeper customer insights and faster compliant content delivery. The strategic technology and data choices biopharmas make today lay the foundation for AI scaling success and a future-proof commercial model that improves HCP engagement and maximizes patient impact.