The chatter about artificial intelligence (AI) is getting louder. AI is a powerhouse, shaking up everything in healthcare from how we design clinical trials to predicting what’s next. And it’s not just noise – AI has earned a seat at the strategic table.
AI’s power is especially advantageous for Medical Affairs, transforming the way MSLs (medical science liaisons) engage with thought leaders by offering unprecedented insights. Here, we’ll explore how AI is modernizing these interactions and provide tips for harnessing its power while avoiding potential pitfalls.
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AI quickly uncovers established and “unsuspecting” KOLs
Traditionally, identifying KOLs (key opinion leaders) has involved a time-consuming, human-led process relying on combing through patient treatment data and published research. AI disrupts this approach by quickly analyzing vast datasets, including clinical trial data, scientific research, medical journals, conferences, electronic health records (EHR), and claims data. This helps MSLs uncover both established leaders and “unsuspecting experts” faster and with a higher degree of accuracy, unearthing invaluable insights that might have otherwise gone unnoticed. MSLs can also utilize AI to identify digital-savvy thought leaders – or digital opinion leaders (DOLs) – who are active on social media and digital channels.
Further, unlike traditional approaches that refresh KOL lists maybe once per year, these lists can now be updated in real-time with AI. This ensures that MSLs are always working with the most current information to identify emerging leaders and adjust engagement strategies promptly. The ability to quickly find these influential figures is redefining the landscape of thought leadership, enabling MSLs to engage with a broader spectrum of experts who can offer unique perspectives and expertise.
AI frees up time to focus on relationship building
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AI not only enhances the accuracy of KOL identification, but significantly improves efficiency.
Healthcare leaders publish research papers on a weekly basis. Combine this with the influx of data from EHRs and claims, and it presents a formidable challenge for manual analysis.
MSLs can leverage AI to streamline workflows, allocate resources more judiciously, and refine strategies for engaging thought leaders. For instance, AI tools can swiftly sift through diverse datasets, identifying relevant information even when presented in obscure journals, across multiple websites, in foreign languages, or in non-standard storage formats.
The impact is undeniable, with processes that might traditionally take six months or longer now accomplished with a simple click. This frees MSLs from manual, time-consuming tasks and redirects their time and energy towards cultivating meaningful relationships with thought leaders. Automating the data analysis process also minimizes the risk of overlooking potential KOLs among the wealth of information.
AI enhances personalized and targeted KOL outreach
The amount of healthcare data is overwhelming, and it’s increasing at a rate of 47% per year. Yet, despite this wealth of information, two-thirds of medical professionals complain about being inundated with generic content and data from McKinsey shows that many U.S. physicians want less face-to-face and more digital pharma engagement, with 60% saying interactions across channels is crucial.
Clearly there is an opportunity for deeper and more personalized outreach.
AI refines KOL outreach by quickly uncovering the intricate details of individual thought leaders. AI tools can analyze preferences, behaviors, and interests, equipping MSLs with a comprehensive understanding of each individual KOL. It can also craft outreach content, fine-tuning messages for tone, voice, and style to appeal to a particular KOL. AI can even recommend the “next best” action and advise on the most opportune times for engaging with stakeholders. This personalized insight allows MSLs to tailor their approach, create more engaging interactions, and build lasting relationships.
Tips for success (and pitfalls to avoid)
AI-driven KOL engagement marks a transformative era for MSLs. By leveraging AI, MSLs can identify, connect, and collaborate with modern thought leaders and KOLs far more effectively.
As you get started, keep in mind these tips:
- Do think of AI as a strategic partner – AI is not just a tech fad. Instead, think of it as a new member of your team. Align it with your goals and engagement strategies for thought leaders. Treat it as a strategic investment, akin to evaluating a new hire in the eyes of Medical Affairs.
- Don’t overrely on AI – While powerful, AI should complement human intuition and expertise, not replace it. Balance AI insights with the experience and judgment of MSLs and Medical Affairs professionals.
- Do ensure data adequacy and security – AI tools are only as good as the data that feeds it. Ensure that your underlying datasets are comprehensive, reliable, up-to-date, and free from bias. Security, too, is paramount – especially when dealing with sensitive medical information.
- Don’t ignore hallucinations – AI operates based on the data it receives. AI systems can “hallucinate” or make up responses when it can’t find the data it needs. It’s important to ensure data is complete, and interpretations are scrutinized by human experts to avoid misinterpretations.
- Do assess fit and ease-of-use – MSLs should view AI as a collaborative tool. They will only benefit from the power of AI if it’s aligned with an organization’s culture, is easy to use, and produces meaningful results.
Don’t forget human touch & oversight – While AI offers many benefits, the human touch remains indispensable. No technology can replace the experience of an MSL, and personal connections are vital in thought leader engagements. Let AI augment, not replace, human rapport-building.
Photo: ipopba, Getty Images
Rob Consalvo is Senior Director of Strategic Commercial Engagement at H1. He works with H1’s strategic partners to provide guidance on the platform's data, platform and role/impact within the healthcare ecosystem.
Rob has enjoyed over a decade of work within various commercial organizations spanning multiple industries with a focus on emotional intelligence, data fluency and understanding client needs.
He graduated from Rutgers university with a BA in Cultural Anthropology.
