{"id":95442,"date":"2026-03-19T00:13:56","date_gmt":"2026-03-18T23:13:56","guid":{"rendered":"https:\/\/www.veeva.com\/eu\/?post_type=resources&#038;p=95442"},"modified":"2026-04-06T18:28:51","modified_gmt":"2026-04-06T16:28:51","slug":"the-role-of-medical-affairs-in-times-of-ai","status":"publish","type":"resources","link":"https:\/\/www.veeva.com\/eu\/resources\/the-role-of-medical-affairs-in-times-of-ai\/","title":{"rendered":"The Role of Medical Affairs in Times of AI"},"content":{"rendered":"<style>\n.veeva-2024 .fa-ul li p {\n  margin-top: 5px;\n}\n.veeva-2024 .content-block .fa-check-circle {\n  color: #f7981d;\n  font-weight: 400;\n  font-size: 20px;\n}<\/p>\n<p>@media (min-width:768px) {\n.veeva-2024 .sidebar-info-box--quote p {\n    font-size: 42px;\n    line-height: 1;\n    text-indent:0em;\n}\n}<\/p>\n<p>@media (min-width:768px) {\n.veeva-2024 .sidebar-info-box--quote h5 {\nfont-size: 22px;\n}\n}\n<\/style>\n<h2>AI is here. What does that mean for medical affairs?<\/h2>\n<p>\nWith <a href=\"https:\/\/2025-physicians-ai-report.offcall.com\/\" target=\"_blank\" rel=\"noopener\">nearly 70% of physicians using AI daily<\/a>, it has emerged as a primary tool<br \/>\nfor increasingly time-constrained healthcare professionals (HCPs) seeking<br \/>\nscientific information. Usage is only poised to grow as a new generation of<br \/>\nphysicians, trained in the digital age, views AI as an integral component of how<br \/>\nthey get their work done.\n<\/p>\n<div class=\"gray-box\">\n<p>\nAs AI continues to rapidly change physicians\u2019 behavior,<br \/>\nmedical affairs faces three critical questions:<\/p>\n<ul>\n<li>Will HCPs still need medical affairs for scientific information?<\/li>\n<li>How can medical affairs ensure AI tools ingest proprietary<br \/>\ndata and share it accurately and reliably?<\/li>\n<li>If an HCP trusts an AI tool but gets misinformation that<br \/>\ncauses a detrimental effect, who is liable?<\/li>\n<\/ul>\n<\/div>\n<p><strong>Current use of AI among physicians<\/strong><\/p>\n<section class=\"quote-3-up quote-3-up--light\" style=\"margin: 40px 0\">\n<div class=\"quote-3-up__quotes container\">\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>67%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>Use AI daily<\/h5>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>89%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>Use AI weekly<\/h5>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>84%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>Believe AI makes them better at their jobs<\/h5>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p>\n<sup><br \/>\nSource: <a href=\"https:\/\/2025-physicians-ai-report.offcall.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">The 2025 Physicians AI Report<\/a><br \/>\n<\/sup>\n<\/p>\n<p>\nThe challenge is not whether AI will be used, but rather, what role will medical<br \/>\naffairs play as AI reshapes how individuals access and interpret scientific<br \/>\ninformation. In this white paper, we explore the path forward for medical affairs<br \/>\nand the necessary shift toward a dual approach that centers on:<\/p>\n<ul>\n<li><strong>The science:<\/strong> Take proactive responsibility for data accessibility in the<br \/>\ndigital ecosystem, making the right information available to stakeholders<br \/>\nand the tools, platforms, and channels they use to find it.<\/li>\n<li><strong>The relationship:<\/strong> Protect and strengthen the irreplaceable human<br \/>\nconnection of medical affairs, emphasizing the one-to-one relationship<br \/>\nand mutual value created through deep scientific collaboration<br \/>\nbetween biopharma and healthcare.<\/li>\n<\/ul>\n<p>\nThe opportunity is significant: Organizations that respond intentionally to this<br \/>\nnew mandate will strengthen relevance, trust, and influence. Those that don\u2019t,<br \/>\nstand to lose all three.\n<\/p>\n<h2>Where generative AI and medical affairs converge<\/h2>\n<div class=\"gray-box\" align=\"center\">\nTraditional data<br \/>\ndissemination is dying<br \/>\nas generative AI and<br \/>\nmedical affairs converge.\n<\/div>\n<p>\nAt their core, both generative AI (GenAI) and medical affairs disseminate<br \/>\nknowledge, and to some extent, are interpreters of evidence. This has<br \/>\nintroduced a competitive dynamic, not because AI and medical affairs serve<br \/>\nidentical purposes, but because they increasingly address the same job to<br \/>\nbe done. Therefore, the first and most immediate risk is that HCPs may stop<br \/>\ncoming to medical affairs for information.<\/p>\n<p>\nAccess to data, experts, and curated evidence forms the foundation of<br \/>\nscientific exchange. Previously, human-bound constraints like availability,<br \/>\neffort, and turnaround time often limited access. GenAI changes this,<br \/>\nremoving the friction points that traditionally governed data dissemination.<\/p>\n<p>\nWith this new ease of access comes a shift in perceived value. If time-constrained<br \/>\nHCPs get answers that satisfy them at their first point of need, then the<br \/>\nthreshold for engaging with medical affairs fundamentally changes.\n<\/p>\n<p>\n<strong>This is the earliest signal of a burning platform that has quietly taken<br \/>\nshape, where maintaining the status quo carries more risk than change.<\/strong>\n<\/p>\n<p>\nBurning platforms are rarely obvious in real time \u2014 more often they\u2019re<br \/>\nrecognized in hindsight, after the environment has already changed. The<br \/>\nimpact isn\u2019t always immediately visible or stark, making it difficult to grasp a<br \/>\nreal sense of urgency to respond.<\/p>\n<p>\nFor medical affairs, this shift has gone unseen primarily due to the way AI<br \/>\nentered the enterprise conversation. Across industries, and particularly in life<br \/>\nsciences, leaders have mainly focused on the inward-facing view of AI as a tool<br \/>\nfor operational gain. How can it help cut costs, simplify operations, and drive<br \/>\nproductivity across the business?<\/p>\n<p>\nWhile these efforts are necessary and exciting, they only represent one side of<br \/>\nthe story. The other side \u2014 the outward-facing view \u2014 is just as important to<br \/>\nconsider. From it comes a second underlying risk that precedes the behavioral<br \/>\nshifts we\u2019re seeing with AI adoption across healthcare. It\u2019s more structural, and<br \/>\narguably even more consequential, because it affects public health discourse<br \/>\nand patient safety at large.\n<\/p>\n<h3>The information blind spot: What\u2019s training AI?<\/h3>\n<p>\nMost AI models are primarily trained on public data, possibly missing critical<br \/>\ninformation like proprietary data from biopharma companies that medical<br \/>\naffairs stewards. This brings an inevitable risk that when an HCP or a patient<br \/>\nprompts the tool, the tool gets it wrong. It believes it is right because it doesn\u2019t<br \/>\nknow what it doesn\u2019t know.<\/p>\n<p>\nSynthesizing conclusions without access to the full body of relevant data or on<br \/>\nincomplete, outdated, or even secondary interpretations of evidence creates a<br \/>\nblind spot that contributes to a growing challenge: the spread of<br \/>\nmisinformation and disinformation.\n<\/p>\n<section class=\"quote-3-up quote-3-up--light\" style=\"margin: 40px 0\">\n<div class=\"quote-3-up__quotes container\">\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>40%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>of online health content on<br \/>\nmajor public health topics<br \/>\ncontains inaccuracies (<a href=\"https:\/\/www.who.int\/europe\/news\/item\/20-10-2022-collaboration-is-key-to-countering-online-misinformation-about-noncommunicable-diseases--new-who-europe-toolkit-shows-how\" target=\"_blank\" rel=\"noreferrer noopener\">WHO<\/a>)<\/h5>\n<\/div><\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>67%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>of patients believe they<br \/>\nhave been exposed to<br \/>\nmisinformation about their<br \/>\ncondition in the past 12<br \/>\nmonths (<a href=\"https:\/\/havaslynx.com\/news\/doctored-truths-health-misinformation\/#:~:text=Havas%20Lynx's%20%22Doctored%20Truths%22%20white%20paper%20highlights,clinical%20data%20to%20combat%20this%20growing%20threat\" target=\"_blank\" rel=\"noreferrer noopener\">HAVAS<\/a>)<\/h5>\n<\/div><\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>61%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>of HCPs say misinformation<br \/>\nhas caused a loss of trust<br \/>\nbetween them and their<br \/>\npatients (<a href=\"https:\/\/havaslynx.com\/news\/doctored-truths-health-misinformation\/#:~:text=Havas%20Lynx's%20%22Doctored%20Truths%22%20white%20paper%20highlights,clinical%20data%20to%20combat%20this%20growing%20threat\" target=\"_blank\" rel=\"noreferrer noopener\">HAVAS<\/a>)<\/h5>\n<\/div>\n<\/div><\/div>\n<\/section>\n<p>\nSeveral leading global organizations have also directly addressed the issue as<br \/>\nit relates to public health:<\/p>\n<ul>\n<li>The World Health Organization has warned that health misinformation<br \/>\nand disinformation is a <strong>major threat to global health.<\/strong><\/li>\n<li>The European Parliament identifies health disinformation as a<br \/>\n<strong>systemic, ongoing threat to public health and democracy.<\/strong><\/li>\n<li>The World Economic Forum cites misinformation and disinformation<br \/>\nas the <strong>top short-to-medium term global risk.<\/strong><\/li>\n<li>ECRI cites wide availability and viral spread of medical<br \/>\nmisinformation as <strong>the top 3 patient safety concern.<\/strong><\/li>\n<\/ul>\n<p>\n<sup><br \/>\nSource: World Health Organization, Review (2024);<\/sup><sup>European Parliament Study (2024);<\/sup><sup>World Economic Forum, The Global Risks Report 2025 (2025);<\/sup><sup>ECRI, Top 10 Patient Safety Concerns 2025 Report (2025).<br \/>\n<\/sup>\n<\/p>\n<p>\nWhile AI did not create this problem, it accelerates the impact. When medical<br \/>\naffairs\u2019 input is absent from the digital ecosystems that shape AI output, it<br \/>\ncreates a vacuum filled by secondary and often non evidence-based means.\n<\/p>\n<p>\nThe challenge for medical affairs today is how to remain the trusted scientific<br \/>\nauthority to healthcare in an environment where AI increasingly mediates<br \/>\nscientific understanding. In the larger ecosystem of public health, AI is just as<br \/>\nimportant to the solution.\n<\/p>\n<h2>Using core strengths to meet new realities<\/h2>\n<p>\nMedical affairs has a new mandate to reposition itself by extending its core<br \/>\nstrengths to meet new realities. This requires a dual commitment.\n<\/p>\n<ul>\n<li><strong>The science:<\/strong> When it comes to information access, scientific<br \/>\nstewardship in digital spaces must become intentional and<br \/>\nproactive. That means ensuring accurate, evidence-based scientific<br \/>\ninformation is more accessible not only to the stakeholders \u2014 but to<br \/>\nthe tools, platforms, and channels they are using to find it.<\/li>\n<li><strong>The relationship:<\/strong> Medical affairs maintains the advantage of one-to-one<br \/>\nrelationships: knowing exactly who to talk to and cultivating those<br \/>\nrelationships through coordinated activities. The biopharma<br \/>\nindustry has spent decades anchoring to an engagement model that<br \/>\nmeets the stakeholder at eye level. This remains an invaluable<br \/>\ndifferentiator for medical affairs, but it can and must evolve.<br \/>\nLet\u2019s look at each core strength in more detail and explore the actions medical<br \/>\naffairs can take to get there.<\/li>\n<\/ul>\n<h2>The science: Improving accessibility in a digital-first environment<\/h2>\n<p>\nMedical affairs is responsible not only for the quality of evidence, but for how evidence<br \/>\nis represented, contextualized, and interpreted. Should medical affairs have this<br \/>\nresponsibility in an AI-mediated environment too?\n<\/p>\n<p>\nImproving accessibility in the digital space is about making information discoverable<br \/>\n\u2014 anytime, anywhere. That requires both operational discipline and content evolution.\n<\/p>\n<div class=\"gray-box\">\n<p>Consider the following questions:<\/p>\n<ul>\n<li>How often does a Gemini summary cite your evidence?<\/li>\n<li>Does OpenEvidence correlate your real-world evidence with<br \/>\nthe standard of care?<\/li>\n<li>If you ask ChatGPT or Claude about the scientific position of<br \/>\na given product, does its answer align with your company\u2019s?<\/li>\n<\/ul \n\n<\/div>\n<h3>Model optimization: Why machine readability matters<\/h3>\n<div class=\"gray-box\" align=\"center\">\nIf AI is the engine, data is<br \/>\nthe fuel. Dirty fuel gets you<br \/>\nnowhere. The same with<br \/>\nan empty tank.\n<\/div>\n<p>\nThinking beyond a document-based approach to data and content management<br \/>\nhelps medical affairs influence how scientific information shows up in AI-mediated<br \/>\nspaces. The shift focuses on the technical mechanics that allow machines to<br \/>\ndiscover, interpret, and cite evidence with the same nuance as a human expert.\n<\/p>\n<p>\nBefore AI-powered search, the standard for digital content visibility was search<br \/>\nengine optimization (SEO). The focus was on specific techniques to improve<br \/>\nhow content ranks in search engine results pages (SERP).\n<\/p>\n<p>\nAI is changing that model. Instead of optimizing for high SERP rank, the<br \/>\nprimary goal now is to ensure AI cites or references your data, studies, or<br \/>\ncontent. This practice of generative engine optimization (GEO) builds on SEO<br \/>\nby optimizing for generative models using approaches that make content<br \/>\neasier for AI systems to understand, trust, and reuse.\n<\/p>\n<p>\nGEO optimizes for comprehension and citation \u2014 rather than clicks \u2014 and requires:\n<\/p>\n<p>Digital strategies must fundamentally change to accommodate what AI<br \/>\nengines think is quality, relevant information to surface. Think about it as a<br \/>\nshift from digital content to machine-readable science.\n<\/p>\n<h3>Machine-readable science requires content evolution<\/h3>\n<p>\nMachine readability is critical to support an AI-enabled content supply chain.<br \/>\nIn this context, content evolution optimized for an AI ecosystem is a win-win.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"single source of truth\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-1.png\"><\/p>\n<h3>Structured data<\/h3>\n<p>\nModels need structured inputs to interpret concepts that should ground its<br \/>\noutputs. Fortunately, medical affairs already has an advantage. The core<br \/>\ninformation to communicate has a set structure already defined in a scientific<br \/>\ncommunication platform (SCP). But in this context, it\u2019s about managing the<br \/>\ninformation itself rather than a document that contains it.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"SCP hierarchy\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-2.png\"><\/p>\n<p>These structured components give AI the context it needs to understand:<\/p>\n<ul>\n<li>What a scientific statement is<\/li>\n<li> How it relates to other concepts<\/li>\n<li>What evidence supports it<\/li>\n<\/ul>\n<p>\nBut what happens when that context changes? Perhaps an MSL identified an<br \/>\neducation gap in the field and you recently published new evidence that closes<br \/>\nit. Updating the component updates the context \u2014 accurately and consistently<br \/>\n\u2014 across content and channels.\n<\/p>\n<h3>Content reuse<\/h3>\n<p>\nBreaking down information into format-free components allows reuse in different<br \/>\ncontexts. By tagging information with metadata \u2014 data that describes other data \u2014<br \/>\nsystems then can identify and interpret that information when used in content.\n<\/p>\n<p>\nThis approach links content to structured components that teams have already reviewed<br \/>\nand approved. If an individual asset needs to be tailored for a specific audience or<br \/>\nlocalized for a specific market, for example, structure enables reuse to support these<br \/>\nneeds. This approach ensures content always reflects the approved scientific truth.\n<\/p>\n<h3>Dynamic distribution<\/h3>\n<div class=\"gray-box\" align=\"center\">\nIf mere data dissemination<br \/>\nis losing its value, the time<br \/>\nfor field medical to be \u201cjust\u201d<br \/>\na provider of scientific<br \/>\ninformation is gone.\n<\/div>\n<p>\nDynamic distribution means <strong>delivering the right information at the right moment.<\/strong><br \/>\nInformation is not fixed to a single format or channel but is \u2018living and breathing,\u2019<br \/>\noptimized for both AI model retrieval and human consumption.\n<\/p>\n<p>\nInstead of static, one-off publishing, teams can deliver information dynamically<br \/>\nand make it discoverable across push and pull channels. For example:<\/p>\n<ul>\n<li>Push to field teams when new evidence surfaces<\/li>\n<li>Pull through search or an agent chat in response to a medical inquiry<\/li>\n<\/ul>\n<p>\nInformation delivered in these contexts stays accurate and consistent. Structure<br \/>\nenables traceability, tying external usage of information back to the system from which<br \/>\nit originated. This creates visibility into usage that can help inform future strategy.\n<\/p>\n<h2>The relationship: Improving scientific exchange with deeper dialogue and debate<\/h2>\n<p>\nAs AI increasingly becomes the first touchpoint for knowledge-seeking HCPs, relevance<br \/>\nand influence in biopharma engagement will depend more on specialization in the field.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"Shifts in the engagement mix\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-3.png\"><\/p>\n<h3>The reimagined MSL: Value beyond the LLM<\/h3>\n<p>\nHCPs and KOLs want instant access to information and personalized<br \/>\ninteraction. As AI becomes a frontline tool, MSLs will differentiate themselves<br \/>\nthrough their expertise, perspective, and deep scientific collaboration.\n<\/p>\n<p>\nExpertise is the depth of your knowledge. MSLs can provide information, but<br \/>\nthe real benefit is the context and insights they bring to the conversation.\n<\/p>\n<p>\nPerspective is the angle from which you apply knowledge. For MSLs, that<br \/>\nmeans clearly articulating how the organization interprets and contextualizes<br \/>\nthe total body of evidence, what scientific position it holds, and how it believes<br \/>\nthat evidence should or should not translate into clinical practice. They must be<br \/>\nwilling to defend that position, debate it, and refine it, if and where necessary.\n<\/p>\n<p><a href=\"https:\/\/www.veeva.com\/eu\/resources\/2025-kol-satisfaction-report\/\">Research<\/a> shows that KOLs highly value this type of exchange with MSLs:<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"Research\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-4.png\"><\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"KOL Survey\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-5.png\"><\/p>\n<p>\n<sup><br \/>\nSource: <a href=\"https:\/\/www.veeva.com\/eu\/resources\/2025-kol-satisfaction-report\/\">KOL Satisfaction Survey<\/a><br \/>\n<\/sup>\n<\/p>\n<div class=\"keyline-wrapper\">\n<p>\n<strong>Best practices for sharing<br \/>\na scientific opinion:<\/strong><\/p>\n<ul>\n<li>Disclose all<br \/>\nunderlying evidence<\/li>\n<li>Maintain a fair and<br \/>\nbalanced view<\/li>\n<li>Steer clear of<br \/>\nmarketing language<\/li>\n<li>Use scientific<br \/>\nargumentation<\/li>\n<\/ul>\n<\/div>\n<p>Deeper scientific collaboration focuses on the breadth of mutual value through<br \/>\none-to-one relationships, which AI cannot replicate. This includes distinct elements:<\/p>\n<ul class=\"fa-ul\">\n<li><span class=\"fa-li\"><i class=\"far fa-check-circle\"><\/i><\/span>\n<p><strong>Stakeholder ownership<\/strong><\/p>\n<p>\nOwnership starts as early as segmentation and targeting. This<br \/>\nincludes finding exactly who you want to talk to, getting to know their<br \/>\ninterests, preferences, and needs, and maintaining the relationship<br \/>\nover time through coordinated activities. LLMs are simply not built to<br \/>\nengage with this level of sophistication.<\/p>\n<\/li>\n<li><span class=\"fa-li\"><i class=\"far fa-check-circle\"><\/i><\/span>\n<p><strong>Scientific debate<\/strong><\/p>\n<p>\nAnother distinct but somewhat overlooked source of shared value<br \/>\nis in scientific debate. Scientific disagreement is a critical source<br \/>\nof progress that machines cannot simulate because they lack the<br \/>\ncontext to \u2018care\u2019 about being wrong.\n<\/p>\n<p>\nIf an HCP disagrees with what AI presents, the HCP is not likely to<br \/>\nengage in a debate with the agent. By contrast, when an HCP challenges<br \/>\na scientific position an MSL presents during an interaction, they will<br \/>\nlikely engage in debate. That tension is often a vital source of scientific<br \/>\nlearning, delivering critical insights for the organization.\n<\/p>\n<\/li>\n<li><span class=\"fa-li\"><i class=\"far fa-check-circle\"><\/i><\/span>\n<p><strong>Insights sharing<\/strong><\/p>\n<p>\nThe irreplaceable human connection is arguably most evident when<br \/>\nit comes to insights. AI is a useful tool for surfacing insights, but the<br \/>\nexchange comes from the dialogue itself.\n<\/p>\n<p>\nKOLs share, on average, nine insights per year across a broad range of<br \/>\ntopics, with some KOLs sharing as many as 60 insights with companies<br \/>\nthey\u2019re engaging with. While these insights are extremely valuable to<br \/>\nbiopharmas, <a href=\"\/eu\/resources\/closing-the-insights-gap-the-kol-perspective\/\">data<\/a> shows there is room for improvement.\n<\/p>\n<\/li>\n<\/ul>\n<section class=\"quote-3-up quote-3-up--light\" style=\"margin: 40px 0\">\n<div class=\"quote-3-up__quotes container\">\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>60%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>of insights shared with<br \/>\nbiopharma <strong>are not used<\/strong>,<br \/>\naccording to surveyed KOLs<\/h5>\n<\/div>\n<\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>100%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5><strong>want to receive feedback<\/strong> on<br \/>\nthe insights they share<\/h5>\n<\/div>\n<\/div>\n<div class=\"sidebar-info-box sidebar-info-box--quote sidebar-info-box--light\">\n<p>82%<\/p>\n<div class=\"sidebar-info-box__author\">\n<h5>want to hear about<\/strong> insights<br \/>\n<strong>other KOLs<\/strong> have shared<\/h5>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<p>\nMedical affairs has made <a href=\"\/eu\/resources\/measuring-the-impact-of-medical-affairs-determining-the-quality-and-actionability-of-insights\/\">insights collection<\/a> a core priority, yet many organizations<br \/>\nstruggle to trace how this data is used to change medical strategy or inform future<br \/>\nactivities intended to close clinical care gaps. Operational improvements will be the<br \/>\ndefining element of transformation going forward.\n<\/p>\n<h3>Holistic transformation will deliver measurable impact<\/h3>\n<p>\nAI does not diminish the importance of medical affairs but does change<br \/>\nthe standard for creating value. This is especially true when it comes to<br \/>\nhow medical affairs is working toward delivering <a href=\"https:\/\/www.veeva.com\/eu\/medicalimpact\/\">measurable impact<\/a>.<br \/>\nStrengthening the <a href=\"\/eu\/resources\/measuring-the-impact-of-medical-affairs-operational-effectiveness\/\">operational foundation<\/a> ensures key enablers can work<br \/>\ntogether to drive the desired outcomes: scientific belief alignment, clinical<br \/>\npractice optimization, and ultimately improved patient outcomes.\n<\/p>\n<h4>The Medical Impact Model<\/h4>\n<p>\nThe <a href=\"https:\/\/www.veeva.com\/eu\/resources\/measuring-the-impact-of-medical-affairs\/\">medical impact model<\/a> is a framework to structure exchange on<br \/>\nthe intricate topic of measurement. Every module stands for a desired<br \/>\noutcome and how medical affairs teams can approach measuring each.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"Medical Impact Model\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-6.png\"><\/p>\n<p>\nBut biopharmas cannot demonstrate impact if the solution to every challenge is applied in<br \/>\nisolation. Holistic transformation is the only path forward, shifting focus from \u201cwhat tools<br \/>\ndo we deploy\u201d to \u201cwhat outcomes can our operating model enable?\u201d\n<\/p>\n<h2>The path forward: Unify the medical affairs operating model<\/h2>\n<div class=\"gray-box\" align=\"center\">\nLeaders must embrace<br \/>\nthe ecosystem effect of<br \/>\nAI \u2014 and the ecosystem<br \/>\nchange it necessitates.\n<\/div>\n<p>\nAI will not replace humans, nor will it replace the core applications they use.<br \/>\nIn fact, it will increasingly depend on both. Because AI is systematic by nature,<br \/>\nit doesn\u2019t distinguish between internal and external environments. It learns<br \/>\ncontinuously from the information it\u2019s given and the systems that enable it.<br \/>\nThat means AI is only as effective as the:<\/p>\n<ul>\n<li>Quality and<br \/>\nstructure of the<br \/>\ndata it learns from<\/li>\n<li>Consistency in<br \/>\nthe processes<br \/>\nthat govern it<\/li>\n<li>Strength of the<br \/>\nunderlying platforms<br \/>\nthat support it<\/li>\n<\/ul>\n<p>\nFor medical affairs, AI changes the mandate but not the fundamentals.<br \/>\nInvestment in the most sophisticated AI tool will never compensate for an<br \/>\necosystem that isn\u2019t built to support it.\n<\/p>\n<p>\nStrengthening underlying data and technology foundations may not be the<br \/>\nflashiest investment, but it is critical work. It\u2019s what enables AI to work safely,<br \/>\nreliably, and consistently at scale \u2014 regardless of where or how it\u2019s being<br \/>\napplied. In this context, the limitations of point solutions become more acute.\n<\/p>\n<p>\nAI depends on continuity \u2014 consistent data structures, shared context,<br \/>\nand connected workflows. Point solutions are not built to support this.<br \/>\nAccumulating a collection of tools designed to work in isolation fragments<br \/>\nthe ecosystem, reinforces silos, and places the burden of coordination on<br \/>\npeople rather than systems:<\/p>\n<ul>\n<li>Teams spend time stitching together information that should<br \/>\nalready be connected<\/li>\n<li>Evidence moves through the content lifecycle with no reliable<br \/>\nchain of custody<\/li>\n<li> Engagement activities lack coordination and any potential<br \/>\ninsights derived from them slip through the cracks <\/li>\n<\/ul>\n<p>\nYou don\u2019t have to reinvent these activities to effectively orchestrate them.<br \/>\nBuild a foundation that creates continuity from where the science takes<br \/>\nshape to where relationships create meaningful value and insights in the field.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"Flywheel effect in medical affairs\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-7.png\"><\/p>\n<p>\nWhen these pieces connect, they start reinforcing each other. Medical affairs<br \/>\noperates in a coordinated motion, with AI becoming a natural enabler to<br \/>\naccelerate impact across the full cycle of work.\n<\/p>\n<h3>Investing in effective change management<\/h3>\n<p>\nAI and other technology does not create impact on its own. Impact comes<br \/>\nfrom an entire organization willing to rethink how work gets done and commit<br \/>\nto making the required changes.\n<\/p>\n<p>\nEffective change management aligns people, processes, and platforms<br \/>\naround shared outcomes. Once you\u2019ve assessed where and how to leverage<br \/>\nAI to support those goals, you can turn your attention toward organizational<br \/>\nreadiness. Here are some ways to get started.\n<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" alt=\"Change management stratgies\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/03\/Medical-Affairs-White-Paper-Img-8.png\"><\/p>\n<h4>THE BOTTOM LINE<\/h4>\n<h2>AI changes what\u2019s possible, but<br \/>\nmedical affairs decides what\u2019s next<\/h2>\n<p>\nOrganizations that embrace holistic transformation will create an environment for<br \/>\nchange to flourish \u2014 no matter how much or how fast technology evolves. AI has<br \/>\nbrought a fundamental change in how society engages with information. Within<br \/>\nlife sciences and across the healthcare ecosystem, it\u2019s important to remember<br \/>\nthat this change is driven by the ultimate goal of improving patient care.\n<\/p>\n<p>\nSee ³Ô¹Ï±¬ÁÏ&#8217;s <a href=\"\/eu\/resources\/medical-solutions-product-demo\/\">end-to-end medical solutions<\/a> in action.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This white paper explores the role and path forward for medical affairs as AI reshapes how individuals access and interpret scientific information.<\/p>\n","protected":false},"featured_media":95488,"parent":0,"template":"","class_list":["post-95442","resources","type-resources","status-publish","has-post-thumbnail","hentry","resource-area-20-medical","resource-product-20-medical-crm","resource-product-20-vault-medcomms","resource-product-20-medical-insights","resource-product-20-publications","resource-type-white-papers","region-eu"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/resources\/95442"}],"collection":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/resources"}],"about":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/types\/resources"}],"version-history":[{"count":1,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/resources\/95442\/revisions"}],"predecessor-version":[{"id":95445,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/resources\/95442\/revisions\/95445"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/media\/95488"}],"wp:attachment":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/media?parent=95442"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}