{"id":25102,"date":"2025-10-21T17:26:58","date_gmt":"2025-10-21T22:26:58","guid":{"rendered":"https:\/\/blog.planview.com\/?p=25102"},"modified":"2025-10-21T17:27:00","modified_gmt":"2025-10-21T22:27:00","slug":"ai-at-the-inflection-point","status":"publish","type":"post","link":"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/","title":{"rendered":"AI at the Inflection Point"},"content":{"rendered":"\n<p><strong>Note from Editor: <\/strong><em>This post is adapted from Dr. Rich Sonnenblick\u2019s presentation at the 30<sup>th<\/sup> European Biopharma Project, Program, &amp; Portfolio Management Conference in Basel. In his presentation, Dr. Sonnenblick dispelled the hype surrounding AI and agents, while sharing concrete examples of how drug development teams are saving hundreds of hours, de-risking their clinical pipelines, and gaining critical strategic and operational insights through Artificial Intelligence.<\/em><\/p>\n\n\n\n<p>If there was one major takeaway from this year\u2019s Basel conference, it was how AI has crossed the threshold from promise to performance in life sciences portfolio management.<\/p>\n\n\n\n<p>The conference was filled with sessions where speakers debated how to connect strategy and execution, how to manage patent cliffs, and how to create transparency across sprawling R&amp;D networks. But beneath all the slides and frameworks, the real story was about how AI is redefining the rhythm of decision-making in drug development.<\/p>\n\n\n\n<p>For Planview, that shift has been years in the making.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Our mission has always been to help organizations turn connected work data into connected intelligence. Today, AI allows us to do that faster, sooner, and with far greater precision.<\/p>\n<\/blockquote>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_80 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#From_Data_to_Decision_The_AI_Capability_Horizon\" >From Data to Decision: The AI Capability Horizon<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#Why_AI_Matters_Now\" >Why AI Matters Now<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#Lessons_from_the_Basel_Conversations\" >Lessons from the Basel Conversations<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#The_Planview_Vision_From_Connected_Work_to_Connected_Intelligence\" >The Planview Vision: From Connected Work to Connected Intelligence<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\" id=\"h-from-data-to-decision-the-ai-capability-horizon\"><span class=\"ez-toc-section\" id=\"From_Data_to_Decision_The_AI_Capability_Horizon\"><\/span><strong>From Data to Decision: The AI Capability Horizon<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In my presentation, <em>\u201cManaging Drug Development Initiatives: Trends in AI,\u201d<\/em> I described Planview\u2019s model for evolving AI capability. <\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"629\" height=\"354\" src=\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/Planview-Capability-Horizon.png\" alt=\"\" class=\"wp-image-25106\" srcset=\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/Planview-Capability-Horizon.png 629w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/Planview-Capability-Horizon-300x169.png 300w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/Planview-Capability-Horizon-150x84.png 150w\" sizes=\"auto, (max-width: 629px) 100vw, 629px\" \/><\/figure>\n<\/div>\n\n\n<p>This model is built on <strong>Foundational Infrastructure<\/strong> to enable <strong>Early Warning<\/strong>, <strong>Simulation and Optimization<\/strong>, <strong>Scenario Planning<\/strong>, and finally <strong>Generative AI<\/strong>.<\/p>\n\n\n\n<p>Each solution area represents a practical step toward true decision intelligence.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-1-foundational-infrastructure-becoming-a-good-steward-of-connected-work-data-sources\"><strong>1. Foundational Infrastructure: Becoming a good Steward of Connected Work Data Sources<\/strong><\/h3>\n\n\n\n<p>Every insight begins with connected data.<\/p>\n\n\n\n<p>Drug development generates massive volumes of structured and unstructured information. Information like clinical milestones, resource assignments, dependency maps, risk logs, and regulatory documents.<\/p>\n\n\n\n<p>Planview\u2019s Data Fabric stitches those elements together across products, portfolios, and teams, forming the substrate for machine learning and predictive analytics.<\/p>\n\n\n\n<p>Planview\u2019s Connected Work Graph provides a visual representation of your network of work, resources, and outcomes so you can identify and address dependencies and risks.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"558\" src=\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-1024x558.jpg\" alt=\"\" class=\"wp-image-25114\" style=\"width:1024px;height:auto\" srcset=\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-1024x558.jpg 1024w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-300x164.jpg 300w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-150x82.jpg 150w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-768x419.jpg 768w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph-1536x837.jpg 1536w, https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/planview-connected-work-graph.jpg 1910w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"has-text-align-center\"><em><sub>The Connected Work Graph provides a powerful visual representation of work, resources, and objectives for instant identification of dependencies, at-risk work, and much more.<\/sub><\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-2-early-warning-seeing-trouble-before-it-shows-up\"><strong>2. Early Warning: Seeing Trouble Before It Shows Up<\/strong><\/h3>\n\n\n\n<p>By the time status fields turn red, it\u2019s already too late.<\/p>\n\n\n\n<p>Planview circumvents this by using historical execution data, activity patterns, and even project discussion thread sentiment. Our machine learning models surface early risk signals to identify when work is stalled, resources are overloaded, and collaboration is breaking down.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>This early warning capability is like moving from weather reports to a Doppler radar. Project leaders don\u2019t just see what happened \u2013 they see what\u2019s brewing on the horizon.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-3-system-enabled-optimization-the-ai-co-pilot-for-resource-strategy\"><strong>3. System-Enabled Optimization: The AI Co-Pilot for Resource Strategy<\/strong><\/h3>\n\n\n\n<p>Once risks are visible, optimization becomes actionable.<\/p>\n\n\n\n<p>AI models in the Planview platform recommend staffing reallocations, dependency decoupling, and sequencing changes. This transforms portfolio adjustments from painful quarterly debates into continuous, data-driven refinements.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>By aligning workloads and capacity to real-time constraints, organizations can gain months of productivity without increasing headcount.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-4-scenario-planning-rehearsing-the-future\"><strong>4. Scenario Planning: Rehearsing the Future<\/strong><\/h3>\n\n\n\n<p>Life sciences portfolios are bets involving time, resources, and external factors.<\/p>\n\n\n\n<p>AI-powered simulation and optimization engines let teams test different futures:<\/p>\n\n\n\n<p>What happens if a key trial slips three months?<\/p>\n\n\n\n<p>How does an accelerated submission in Europe affect U.S. launch sequencing?<\/p>\n\n\n\n<p>By quantifying trade-offs in resource, timeline, and probability of success, scenario planning moves decision-making from gut instinct to rehearsed precision.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-5-generative-ai-conversation-as-the-new-interface\"><strong>5. Generative AI: Conversation as the New Interface<\/strong><\/h3>\n\n\n\n<p>The newest layer is conversational.<br>With <a href=\"https:\/\/www.planview.com\/ai\/\"><strong>Planview<\/strong> <strong>Anvi\u2122 Chat<\/strong><\/a>, teams can ask natural language questions directly against Planview\u2019s Connected Work Graph:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u201cWhich studies are showing declining patient enrollment?\u201d<\/li>\n\n\n\n<li>\u201cWhere do we have unassigned work tied to a Q4 objective?\u201d<\/li>\n\n\n\n<li>\u201cSummarize dependencies between our oncology assets.\u201d<\/li>\n<\/ul>\n\n\n\n<p>Generative AI turns the portfolio into a living knowledge system capable of explaining itself, teaching new team members, and drafting context-rich summaries in seconds.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-why-ai-matters-now\"><span class=\"ez-toc-section\" id=\"Why_AI_Matters_Now\"><\/span><strong>Why AI Matters Now<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Drug development has always been a data-rich, insight-poor domain. AI changes that equation.<\/p>\n<\/blockquote>\n\n\n\n<p>By bringing together structured data, unstructured context, and human judgment, we can identify patterns invisible to conventional analytics \u2013 from creeping resource burnout to shifting trial sentiment.<\/p>\n\n\n\n<p>In practical terms, this means:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Detecting risk six months earlier.<\/li>\n\n\n\n<li>Redirecting investment toward higher-probability assets.<\/li>\n\n\n\n<li>Reducing portfolio review cycles from weeks to hours.<\/li>\n\n\n\n<li>Making project retrospectives continuous rather than postmortem.<\/li>\n<\/ul>\n\n\n\n<p>When combined with human expertise, AI gives R&amp;D leaders the ability to act on foresight, not hindsight.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-lessons-from-the-basel-conversations\"><span class=\"ez-toc-section\" id=\"Lessons_from_the_Basel_Conversations\"><\/span><strong>Lessons from the Basel Conversations<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The broader conference reinforced how essential that transformation has become.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Jacqueline Poot (IDEA Pharma)<\/strong> showed how \u201cinnovation freshness\u201d separates market leaders from laggards \u2013 but warned that 2030 patent cliffs could wipe out $200B in revenue without the necessary bets on innovation in today\u2019s pipelines.<\/li>\n\n\n\n<li><strong>Mahesh Chandra (Novartis)<\/strong> argued for structured decision frameworks that embed data governance into every tollgate, aligning risk, value, and resource allocation.<\/li>\n\n\n\n<li><strong>Andrea Panariello (IBSA)<\/strong> and <strong>Silke Rodrigues (Medac)<\/strong> shared firsthand how digital portfolio tools like Planisware and ONBOARD are professionalizing PPM and creating unified transparency across global sites.<\/li>\n<\/ul>\n\n\n\n<p>All these sessions reflect the same core truth.<\/p>\n\n\n\n<p>Pharma organizations no longer suffer from a shortage of data \u2014 they suffer from <strong>disconnected data<\/strong>. AI is what reconnects it, converting noise into a navigable signal.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-the-planview-vision-from-connected-work-to-connected-intelligence\"><span class=\"ez-toc-section\" id=\"The_Planview_Vision_From_Connected_Work_to_Connected_Intelligence\"><\/span><strong>The Planview Vision: From Connected Work to Connected Intelligence<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>At Planview, our vision for life sciences PPM is simple, but transformative:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Predict instead of react:<\/strong> Use machine learning and generative AI to see risk (overloaded teams, work not ready to start) before it user-defined status fields shift from green to red.<\/li>\n\n\n\n<li><strong>Simulate instead of speculate:<\/strong> Use scenario modeling to compare possible futures, accounting for uncertainty in market size, clinical risk, payer risk, and other critical inputs.<\/li>\n\n\n\n<li><strong>Converse instead of configure:<\/strong> Let anyone, from scientist to executive, interact naturally with their data to surface insights and best-practice driven recommendations.<\/li>\n<\/ul>\n\n\n\n<p>When every part of the organization can see the same truth and act on it accordingly, the journey from pipeline to patient accelerates dramatically.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>The future of pharma project management will belong to organizations that can connect insight, execution, and adaptation in one continuous loop.<\/p>\n<\/blockquote>\n\n\n\n<p>That\u2019s what Planview\u2019s Connected Work Graph and <a href=\"https:\/\/www.planview.com\/ai\/\">Anvi\u2122 Chat<\/a> are built to deliver: the intelligence layer that turns project data into strategic advantage.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Note from Editor: This post is adapted from Dr. Rich Sonnenblick\u2019s presentation at the 30th European Biopharma Project, Program, &amp; Portfolio Management Conference in Basel. In his presentation, Dr. Sonnenblick dispelled the hype surrounding AI and agents, while sharing concrete examples of how drug development teams are saving hundreds of hours, de-risking their clinical pipelines,&#8230;<\/p>\n","protected":false},"author":242,"featured_media":25104,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"[]","footnotes":""},"categories":[9582,477],"tags":[],"class_list":["post-25102","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-vision-trends"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.8 (Yoast SEO v26.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>AI at the Inflection Point - Planview Blog<\/title>\n<meta name=\"description\" content=\"How AI is transforming drug development, enabling teams to detect risk earlier, optimize resources, and accelerate strategic decision-making.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI at the Inflection Point\" \/>\n<meta property=\"og:description\" content=\"How AI is transforming drug development, enabling teams to detect risk earlier, optimize resources, and accelerate strategic decision-making.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\" \/>\n<meta property=\"og:site_name\" content=\"Planview Blog\" \/>\n<meta property=\"article:publisher\" content=\"http:\/\/www.facebook.com\/pages\/Planview-Inc\/89422974772\" \/>\n<meta property=\"article:published_time\" content=\"2025-10-21T22:26:58+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-10-21T22:27:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/AI-at-the-Inflection-Point_Header.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"576\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Dr. Richard Sonnenblick\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Planview\" \/>\n<meta name=\"twitter:site\" content=\"@Planview\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Dr. Richard Sonnenblick\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\"},\"author\":{\"name\":\"Dr. Richard Sonnenblick\",\"@id\":\"https:\/\/blog.planview.com\/#\/schema\/person\/475112b0203e554249899b3887eeb93e\"},\"headline\":\"AI at the Inflection Point\",\"datePublished\":\"2025-10-21T22:26:58+00:00\",\"dateModified\":\"2025-10-21T22:27:00+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\"},\"wordCount\":1044,\"publisher\":{\"@id\":\"https:\/\/blog.planview.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/blog.planview.com\/wp-content\/uploads\/2025\/10\/AI-at-the-Inflection-Point_Header.jpg\",\"articleSection\":[\"Artificial Intelligence\",\"Vision and Trends\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\",\"url\":\"https:\/\/blog.planview.com\/ai-at-the-inflection-point\/\",\"name\":\"AI at the Inflection Point - 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