{"id":93712,"date":"2026-02-03T10:50:13","date_gmt":"2026-02-03T09:50:13","guid":{"rendered":"https:\/\/www.veeva.com\/eu\/?p=93712"},"modified":"2026-03-17T21:28:42","modified_gmt":"2026-03-17T20:28:42","slug":"agentic-ai-for-mlr-the-highest-impact-area-of-content","status":"publish","type":"post","link":"https:\/\/pantheon.veeva.com\/eu\/blog\/agentic-ai-for-mlr-the-highest-impact-area-of-content\/","title":{"rendered":"Agentic AI for MLR: <br>The Highest-Impact Area of Content"},"content":{"rendered":"<p>With widespread deployment of AI in commercial biopharma, a key learning has emerged: Aligning AI with high-value business needs can deliver benefits beyond productivity gains, driving greater strategic value to an organization. In the content supply chain, that high-value area is medical, legal, and regulatory (MLR) review.<\/p>\n<blockquote><p>\n\u201cMLR is the backbone of this industry. Without this team, we cannot get content out.\u201d<br \/>\n    <span>Senior vice president and regulatory operations director<\/span>\n<\/p><\/blockquote>\n<p>Content volume keeps rising as the industry craves highly personalized and impactful material \u2014 yet MLR resources are stagnant or decreasing. MLR review is the core of the content lifecycle and an obvious target for AI optimization and promised returns, enabling faster delivery of accurate, compliant treatment information for HCPs and patients. <\/p>\n<p>Moreover, applying AI in MLR has a compelling business impact by structurally improving processes, freeing highly skilled experts for strategic work where human input is critical. The value is not just in providing a shortcut for reviews, but as an aid to make processes more effective while maintaining high-quality material. <\/p>\n<p>As one regulatory operations director and senior vice president puts it, \u201cMLR is the backbone of this industry. Without this team, we cannot get content out.\u201d For many biopharmas, Veeva Vault is the platform of choice for MLR processes and therefore is a high priority for Veeva as we develop purpose-build agentic AI solutions for the industry.<\/p>\n<h2>Transforming MLR through agentic AI<\/h2>\n<p>Built natively into the Vault Platform, <a href=\"\/eu\/products\/veeva-ai-for-promomats\/\">Veeva AI for PromoMats<\/a> introduces intelligent AI agents directly in users\u2019 core processes to perform quality checks, provide document insights, and assist reviewers. <a href=\"\/eu\/resources\/veeva-ai-for-promomats-quick-check-agent-and-content-agent\/\">Quick Check Agent and Content Agent<\/a> streamline MLR review to deliver personalized, impactful, and compliant material faster.<\/p>\n<p>Agentic AI, which can manage multi-step processes autonomously, is uniquely capable of handling compliance pre-checks and flagging risks while avoiding a rework of the end-to-end content supply chain. Compliance and final direction remain firmly human-led. <\/p>\n<p>AI agents deeply embedded in a commercial content platform work in concert with other technology and <a href=\"\/eu\/resources\/building-the-future-of-mlr-with-ai-fastest-path-to-approved-content\/\">process improvements<\/a> \u2014 such as tier-based review, content reuse, and claims management and harvesting \u2014 to drive efficiencies and produce the most relevant assets with faster approval times.<\/p>\n<p><a href=\"\/eu\/products\/crm-suite\/\">Quick Check Agent and Content Agent<\/a> are the first of numerous Veeva AI agents that will work together in PromoMats to retool end-to-end content operations. Agentic MLR will follow, supporting the fastest path to approved content. Collectively, these AI agents not only help MLR, but enable marketing teams and their agency partners to deliver better content to the reviewers, accelerating the delivery of compliant content.<\/p>\n<h2>Test, learn, and scale AI within the MLR framework<\/h2>\n<p>Data, content, and now AI agents work in core applications like PromoMats and <a href=\"\/eu\/products\/crm-suite\/\">Veeva Vault CRM<\/a> to optimize industry business processes and deliver impactful content to customers. The shared infrastructure allows for a frictionless lifecycle where digital assets and metadata flow organization wide. For example, once promotional content is approved, documents are immediately available in Vault CRM for distribution. The deeply embedded AI agents understand business rules and logic, use application-specific prompts, and access data and documents securely. <\/p>\n<p>With this foundation, biopharmas can focus on identifying high-value AI use cases with the \u2018<a href=\"\/eu\/blog\/from-pilot-to-impact-focus-on-people-and-processes-to-deliver-ai-value\/\">Test, Learn, Scale\u2019 framework<\/a>:<\/p>\n<ol>\n<li>Quantify the tangible business value and change impact for each use case to prioritize investments and projects.<\/li>\n<li>Reshape processes and drive adoption with a defined subset of workers.<\/li>\n<li>Redistribute time gained to higher-value tasks across the content model.<\/li>\n<li>Measure ROI and remove process or adoption barriers.<\/li>\n<li>Scale:\n<ul>\n<li>Globally, attending to language and local regulations.<\/li>\n<li>Across brands or therapeutic areas.<\/li>\n<li>To additional use cases and AI agents that become available.<\/li>\n<li>Support AI investments with key industry learnings<\/li>\n<\/ul>\n<\/ol>\n<h3>Framework for success prior to scaling AI<\/h3>\n<p><img decoding=\"async\" class=\"img-responsive mw-700\" alt=\"\" src=\"\/wp-content\/uploads\/2026\/02\/in-blog-agentic-ai-for-mlr-image-1.png\"><\/p>\n<p>Even at this early stage of AI adoption in MLR, there are reliable KPIs to use as guides. For example, measure short-term qualitative factors such as reviewer trust and longer-term quantitative results including time savings.<\/p>\n<h3>It\u2019s not too early to set KPIs<\/h3>\n<p><img decoding=\"async\" class=\"img-responsive mw-600\" alt=\"\" src=\"\/wp-content\/uploads\/2026\/02\/in-blog-agentic-ai-for-mlr-image-2.png\"><\/p>\n<p>In addition, biopharmas can shore up AI investments with industry insights and learnings: <\/p>\n<ul>\n<li><strong>Prepare people and processes<\/strong> for AI with efforts equal to those in making technology decisions. <a href=\"https:\/\/fortune.com\/2025\/08\/18\/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo\/\" target=\"_blank\" rel=\"noopener noreferrer\">MIT<\/a> findings back this idea: \u201cMost [AI projects] fail due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations.\u201d <\/li>\n<li><strong>Distinguish between short- and long-term AI initiatives<\/strong> to achieve the desired outcomes at the lowest cost. Short-term pilot tests are often necessary but can quickly consume more than their share of resources, negatively affecting long-term AI ambitions.<\/li>\n<li><strong>Understand current governance and compliance models<\/strong> for AI solutions and prepare to make any changes needed. Engage compliance professionals early in the process of incorporating AI, allowing them to help define the rules and mitigate risks.<\/li>\n<li><strong>Periodically evaluate ROI from AI<\/strong> so teams continuously measure and adjust without process and adoption barriers, especially as the technology improves. Successful change with AI requires optimizing with humans in the loop.<\/li>\n<\/ul>\n<p>We believe AI is meant to enhance the MLR experience by automating manual and repetitive work while humans maintain critical-thinking efforts \u2014 such as the difficult judgment calls needed in content approvals. Content teams are excited about a future where AI agents support them in being more productive and responsive to HCPs and patients. <\/p>\n<p>In fact, in a recent <a href=\"\/eu\/resources\/ai-in-mlr-insights-from-101-content-professionals\/\">Veeva PromoMats survey<\/a> of 101 content professionals from 10 biopharmas, participants said they expect <a href=\"\/eu\/resources\/ai-in-mlr-insights-from-101-content-professionals\/\">38%<\/a> of the MLR process to be AI-driven by 2028. And they cited \u2018faster MLR review times\u2019 as the number one anticipated benefit of AI in promotional copy approvals.<\/p>\n<p>Focusing AI agents on the high-impact area of MLR provides biopharmas with a clear path to scale the technology, maximize its strategic value, and ultimately meet growing needs for rapid, compliant content delivery. A deep understanding of compliance and MLR is critical to making AI work in content, positioning Veeva and Veeva Business Consulting to guide biopharmas along this journey. <\/p>\n<p>Uniquely equipped with the investments of time, resources, and effort on AI projects that deliver measurable business value, we are helping the industry and its people work in a more efficient and connected way.<\/p>\n<p>Ensure your teams are prepared to leverage the full impact of AI agents with <a href=\"\/eu\/services\/business-consulting-services\/\">Veeva Business Consulting&#8217;s<\/a> in-depth analysis.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A key learning is emerging from AI use in the content lifecycle: prioritizing AI in MLR review delivers benefits beyond productivity gains to drive greater strategic value.<\/p>\n","protected":false},"author":183,"featured_media":81950,"comment_status":"closed","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"product":[1470,996],"area":[1469,972],"coauthors":[1507],"class_list":["post-93712","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","product-ai-veeva-ai","product-commercial-content-promomats","area-ai-veeva-ai","area-commercial","blog-area-commercial","blog-product-content-management","blog-html-content-yes"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/posts\/93712"}],"collection":[{"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/users\/183"}],"replies":[{"embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/comments?post=93712"}],"version-history":[{"count":9,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/posts\/93712\/revisions"}],"predecessor-version":[{"id":94089,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/posts\/93712\/revisions\/94089"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/media\/81950"}],"wp:attachment":[{"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/media?parent=93712"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/categories?post=93712"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/tags?post=93712"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/product?post=93712"},{"taxonomy":"area","embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/area?post=93712"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/pantheon.veeva.com\/eu\/wp-json\/wp\/v2\/coauthors?post=93712"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}