Over the past several years, Medical Affairs has evolved from a largely supportive, reactive function into a primary strategic pillar. In 2026, proving the value of Medical Affairs is no longer necessary; rather, its focus is expected to shift to scaling capabilities to meet the increasingly complex demands of modern healthcare ecosystems.
Artificial Intelligence (AI) has been a buzzword in the industry for years; yet, for many Medical Affairs leaders and Medical Science Liaisons (MSLs) on the ground, its practical applications have often felt distant—stuck in pilots or relegated to basic administrative automation. In 2025, however, it became abundantly clear that AI is no longer a “future tech” concept; it is becoming an operating system necessary to stay current and competitive. Now, the question is: will 2026 be the year when Medical Affairs teams transition their processes from human-dependent workflows to AI-augmented ecosystems, enabling team members to focus solely on high-value scientific strategy?
The Case for AI Augmentation in Medical Affairs
Despite its evolution over the years, many Medical Affairs teams still face challenges with data overload and fragmentation, scalability, generation and utilization of real-world evidence (RWE), suboptimal patient-centricity, and inefficient cross-functional knowledge-sharing and collaboration (1).
AI has the potential to bridge all of these gaps, and more, by automating complex tasks, synthesizing real-world evidence, and personalizing content. In turn, this could free Medical Affairs teams from time-consuming and labor-intensive manual processes, allowing them to shift focus to higher-value scientific tasks (1).
The “MSL 2.0” — Enabling Deeper Field Insights, Enhanced KOL Engagements, and Real-World Evidence-generation
Although AI can be a double-edged sword, depending on who you ask, it is not expected to diminish the MSL’s role. If anything, AI can make the role more sophisticated. The days of the “rolodex approach” to Key Opinion Leader (KOL) management—relying on static CRM notes and periodic check-ins—are over.
Now, in 2026, we’re at the point where AI is enabling true intelligent engagement. By utilizing advanced analytics frameworks, Medical Affairs can move beyond historical interaction data to analyze real-time prescription flows, publication and clinical trial data, and digital engagement metrics and sentiments to enhance RWE generation, deepen scientific credibility, and individualize KOL engagement strategies (2).
By analyzing these data, AI can help identify knowledge gaps and unmet needs among both KOLs and patients, as well as guide future research and evidence-generation initiatives, content creation priorities, and engagement plans (2).
At the same time, AI can also help summarize scientific literature or provide tailored, pre-approved materials based on each KOL’s specific questions or learning preferences, allowing MSLs to transition from generic data presentations to hyper-personalized and straight-to-the-point scientific exchanges (2, 3). This is not about replacing the MSL’s relationship-building skills; it is about arming them with laser-specific tools to ensure every KOL interaction delivers maximum value.
Closing the Feedback Loop
Perhaps one of the most profound shifts predicted for 2026 is the death of the static dashboard. For too long, medical insights have been retrospective; now, with what is becoming known as “Agentic AI”—that is, AI that continuously monitors diverse data streams (e.g., electronic health record data, social media trends, congress presentations, advisory boards, and competitive intelligence), identifies emerging patterns, and autonomously recommends next steps—the game is about to change. This shift could enable Medical Affairs teams to close the feedback loop and move from retrospective analyses to continuous, insight-driven decision-making (4).
AI tools can flag emerging unmet needs or shifting sentiments before they become obvious to the human eye, greatly shortening the “insight-to-action” cycle. Instead of waiting months to identify a data gap, Medical Affairs teams can now do so in near-real time. However, the value of agentic AI lies in its ability to unlock strategic capacity by freeing Medical Affairs teams from time-consuming manual tasks through automated insight generation and by allowing them to focus on higher-value strategic work (4).
AI also plays a role in supporting KOL engagement globally, namely through asynchronous virtual platforms (2). Whether in the form of a virtual advisory board or an online community board, these secure and compliant platforms enable structured dialogue with international and multidisciplinary KOLs, along with around-the-clock accessibility. This removes or minimizes key barriers such as travel and scheduling conflicts, suboptimal diversity, and environmental concerns (2, 5). By adding built-in AI-powered summaries or prompts, ongoing conversations are encouraged, leading to a more meaningful experience for participating KOLs and richer insights for the Medical Affairs team.
Optimizing Content and Minimizing the MLR Bottleneck
Generative AI tools have the potential to dramatically reduce the time needed to craft or review technical and scientific documents (3). However, the insatiable demand for tailored medical content across omnichannel touchpoints frequently clashes with the realities of the tedious yet necessary Medical-Legal-Regulatory (MLR) review process. Here, generative AI has the potential to act as a critical release valve and time-saver on both sides.
We are rapidly moving toward workflows in which Large Language Models (LLMs), trained on verified internal datasets, serve as the “drafting desk.” On one hand, generative AI can generate first-pass response letters, hyper-targeted slide decks and educational materials, or plain language summaries of scientific data in hours rather than days (3, 6). However, it is still key to consider the importance of the human element: while AI can handle volume, speed, and initial drafting, skilled Medical Writers and MSLs are needed to handle scientific nuance, context, and final validation before MLR submission. AI is here to assist and augment, not to replace the human workforce.
At the same time, AI can also help MLR reviewers streamline the process by tracking previously approved materials and references, automatically reviewing materials for potentially problematic language or incorrect claims, and drawing on previously approved language to instantly offer compliant rephrasing options, potentially resulting in two- or three-fold faster approval processes (3).
Potential Pitfalls: Navigating Compliance and Ethics
With great power comes significant regulatory scrutiny; moving forward, tracing the lineage of an AI-generated insight back to its source data will be critical, and Medical Affairs leaders will need to learn to navigate evolving regulatory frameworks, ensuring that patient anonymity and scientific rigor remain the immutable boundaries of innovation.
Leading the Culture Shift in 2026
While AI as a technology has the potential to transform Medical Affairs, the success and ease of transformation will depend more on culture than technology. The onus is now on leadership to move beyond ‘implementing tools’ to ‘reimagining roles.’ Leadership will need to rethink AI governance models and implement more formalized organization-wide frameworks and data standards, clearly linked to scientific and business value, to ensure ethical and compliant use. They need to understand that implementing AI models cannot be a peripheral initiative; it should be a top priority (2,3,7).
In 2026, AI is expected to move beyond tactical and administrative use cases to play a key part in Medical Affairs strategy. It has the potential to enable Medical Affairs to become more efficient, strategic, data- and insight-driven, and patient-focused (6). At the end of the day, AI will not replace Medical Affairs professionals or MSLs, but MSLs who learn to effectively leverage AI may eventually replace those who do not.
By Natalie Yeadon, Co-founder of Impetus Digital
References:
- https://eularis.com/how-ai-is-transforming-medical-affairs/
- https://themsljournal.com/article/the-future-of-kol-engagement-transforming-scientific-collaboration-with-ai-support/
- https://www.mckinsey.com/industries/life-sciences/our-insights/generative-ai-in-the-pharmaceutical-industry-moving-from-hype-to-reality
- https://medicalaffairs.org/innovate-article-the-future-is-agentic-unlocking-ai-potential-for-medical-insights/
- https://link.springer.com/article/10.1007/s40290-024-00531-0
- https://themsljournal.com/article/digital-transformation-of-medical-affairs-through-artificial-intelligence/
- https://www.wolterskluwer.com/en/expert-insights/2026-healthcare-ai-trends-insights-from-experts
