{"id":90582,"date":"2025-11-19T22:07:21","date_gmt":"2025-11-19T21:07:21","guid":{"rendered":"https:\/\/www.veeva.com\/eu\/?post_type=resources&#038;p=90582"},"modified":"2026-09-17T16:29:37","modified_gmt":"2026-09-17T14:29:37","slug":"ai-in-mlr-insights-from-101-content-professionals","status":"publish","type":"resources","link":"https:\/\/www.veeva.com\/eu\/resources\/ai-in-mlr-insights-from-101-content-professionals\/","title":{"rendered":"AI in MLR: Insights from 101 Content Professionals"},"content":{"rendered":"<style>\n.veeva-2024 .content-block__content .takeaway-box {\ndisplay: block;\nborder-left:3px solid #f5670e;\nborder-top-left-radius: 0px;\nborder-bottom-left-radius: 0px;\nfont-size:20px;\nwidth:100%;max-width:550px;\nmargin-top:40px;\n}\n.veeva-2024 .content-block__content .button-icon.button-icon--white {\nbackground-color:#f5670e;\nmargin-top: 5px;\n}\n<\/style>\n<h2>A snapshot of expectations and attitudes about AI<\/h2>\n<p>This infographic presents findings from the Veeva AI for PromoMats Focus Group, composed of leaders from ten biopharma companies. To gather this data, focus group members surveyed stakeholders in their organizations. These targeted internal surveys captured expectations, attitudes, and challenges regarding the integration of AI into the medical, legal, and regulatory (MLR) review process.<\/p>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph with data about the responders\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/1-AI-in-MLR-Survey-Graph-with-data-about-the-responders.png\"><\/p>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph with data about the ease with using AI\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/2-AI-in-MLR-Survey-Graph-with-data-about-the-ease-with-using-AI.png\"><\/p>\n<h2>Concerns about AI<\/h2>\n<p>Over half of respondents have no concerns about using AI<br \/>\nin promotional content review and approval processes. However, 48% report that the following issues warrant attention:<\/p>\n<ul>\n<li>Accuracy and reliability of AI outputs in regulated content<\/li>\n<li>Compliance, auditability, and traceability<\/li>\n<li>Data privacy and security<\/li>\n<li>Ensuring human oversight<\/li>\n<\/ul>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph about concerns in using AI in the copy approval process\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/3-AI-in-MLR-Survey-Graph-about-concerns-in-using-AI-in-the-copy-approval-process.png\"><\/p>\n<h2>Expected benefits of AI in promotional copy approvals<\/h2>\n<p>Speed and compliance are the two most-anticipated benefits from AI\u2019s addition into the promotional copy approval process.<\/p>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph showing the top 5 benefit in using AI during the approval process\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/4-AI-in-MLR-Survey-Graph-showing-the-top-5-benefit-in-using-AI-during-the-approval-process.png\"><\/p>\n<h2>Most requested AI pre-checks<\/h2>\n<p>Respondents were asked what AI assistance they would seek before submitting content for MLR review and approval. The answers were wide-ranging but fell into 11 primary categories (listed below in no particular order).<\/p>\n<p>What would you like AI to check for prior to submitting content for review?<\/p>\n<ul>\n<li><strong>Claims and references accuracy<\/strong><br \/> Validate scientific statements, ensure supporting data is included, and detect missing or outdated references<\/li>\n<li><strong>Tagging and linking<\/strong><br \/>\nConfirm claim-to-ISI\/PI\/references connections and auto-link metadata<\/li>\n<li><strong>Metadata and fields<\/strong><br \/>\nVerify completion of all required metadata, forms, and version details<\/li>\n<li><strong>Spelling, grammar, and punctuation<\/strong><br \/>\nCatch editorial errors in copy before submission<\/li>\n<li><strong>ISI\/PI inclusion and accuracy<\/strong><br \/> Check for presence, position, and correctness of safety information<\/li>\n<li><strong>Formatting and layout<\/strong><br \/>\nValidate templates, logos, and layout consistency<\/li>\n<li><strong>Labeling and annotations<\/strong><br \/>\nFlag missing or incorrect annotations and cross-labels<\/li>\n<li><strong>Brand and fair-balance alignment<\/strong><br \/> Ensure tone, check disclaimers, and balance compliance<\/li>\n<li><strong>eCTD\/2253 compliance<\/strong><br \/> <br \/>\nReview content structure and readiness for FDA submission<\/li>\n<li><strong>Copyright and trademark use<\/strong><br \/> Detect unapproved brand marks, imagery, or third-party content<\/li>\n<li><strong>Duplicate or outdated content<\/strong><br \/>\nFlag reused or expired material prior to routing<\/li>\n<\/ul>\n<p><em>Data: (n = 86)<\/em><\/p>\n<h2>Common issues during content review<\/h2>\n<p>Content stakeholders face similar challenges in ensuring material is compliant and error-free. While the most-cited issue was unsupported claims, the survey captured numerous other top hurdles, as respondents were encouraged to check all that apply.<\/p>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph showing most common issue during content review\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/5-AI-in-MLR-Survey-Graph-showing-most-common-issue-during-content-review.png\"><\/p>\n<p><img decoding=\"async\" style=\"border-radius: 25px;\" class=\"img-responsive mw-700\" alt=\"AI in MLR Survey Graph showing the growth of AI in MLR process in 2028\" src=\"https:\/\/www.veeva.com\/wp-content\/uploads\/2026\/06\/6-AI-in-MLR-Survey-Graph-showing-the-growth-of-AI-in-MLR-process-in-2028.png\"><\/p>\n<div class=\"takeaway-box cta-box\">\n<a  style=\"color:black;\" href=\"\/eu\/resources\/veeva-ai-for-promomats-quick-check-agent-and-ai-chat\/\"><\/p>\n<div style=\"float:right\" class=\"button-icon button-icon--white\" target=\"_self\"> <\/div>\n<div>\n      <strong>See <span style=\"color:#f5670e\">Quick Check Agent and Content Agent<\/span> &#8211; agentic AI that provides the fastest path to compliant, approved content.<\/strong>\n   <\/div>\n<p><\/a>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Where will AI deliver the most value in the MLR process? How much of the workload will AI take on by 2028? Biopharma content stakeholders offer ideas on what to watch for as AI\u2019s impact grows.<\/p>\n","protected":false},"featured_media":90585,"parent":0,"template":"","class_list":["post-90582","resources","type-resources","status-publish","has-post-thumbnail","hentry","resource-area-20-commercial","resource-product-20-commercial-content-promomats","resource-type-infographic"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO Pro 5.0.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"We asked 101 biopharma content stakeholders how AI is impacting MLR. 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