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» Products & Services » » Medical Affairs » Medical Affairs Excellence

Medical Affairs AI & Technology Integration: How Leading Organizations Govern, Connect, and Scale AI

Medical Affairs AI and Technology Integration

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ID: POP-420

Features:

33 Info Graphics

37 Data Graphics

920+ Metrics

10 Narratives

Pages: 81

Published: 2026

Delivery Format: Shipped


 

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  • STUDY OVERVIEW
  • BENCHMARK CLASS
  • STUDY SNAPSHOT
  • KEY FINDINGS
  • VIEW TOC AND LIST OF EXHIBITS
Medical Affairs organizations are moving AI from isolated experimentation into core workflows, but adoption alone does not create value. Many teams are still building the policies, governance, data infrastructure, and skills required to support responsible adoption. Leaders must also determine which use cases warrant investment, how tools and data should connect, and how to demonstrate measurable scientific and operational value from technology investment.

Developed by Best Practices, LLC, this benchmarking study examines how Medical Affairs organizations are assessing, adopting, and operationalizing AI and new technologies. It explores priority use cases and real-world tools, technology satisfaction, organizational risk posture, governance and human oversight, systems integration, approval processes, investment priorities, and the barriers that prevent successful pilots from reaching scale.

The research also compares a true "Innovators" segment with a "Rest of Industry" segment. Innovators are the organizations in the study that scored highest on digital maturity and treat technology as a strategic capability rather than primarily as an IT cost decision. Medical Affairs leaders can use the findings to assess their current maturity, identify governance and integration gaps, evaluate technology priorities, and build a phased roadmap for scaling AI responsibly and improving value from technology investment.

What this research helps Medical Affairs leaders do:
  • Benchmark AI adoption policies, approved use cases, review requirements, audit practices, and governance maturity.
  • Compare technology satisfaction and capability gaps across Medical Affairs functions.
  • Assess systems integration maturity, core platforms, point solutions, and data fragmentation risks.
  • Evaluate technology planning, investment, approval, escalation, and implementation processes.
  • Identify where AI pilots are active, which capabilities matter most, and where organizations report value.
  • Compare the practices of Innovators with those of the Emerging or Rest of Industry segment.
  • Build a phased roadmap for governing, connecting, and scaling Medical Affairs AI.
Industries Profiled:
Pharmaceutical; Biotech; Manufacturing; Health Care; Biopharmaceutical; Clinical Research; Laboratories; Medical Device


Companies Profiled:
Bausch Health; Biogen; Boehringer Ingelheim; Cipla; Corcept Therapeutics; CSL Limited; Ferring Pharmaceuticals; GE Healthcare; Gilead Sciences; Grifols; Immunic Therapeutics; Ipsen; Jazz Pharmaceuticals; Merck KGaA; Mesoblast; Om Pharma; Orion Pharma; Paratek Pharmaceuticals; Regeneron Pharmaceuticals; Sanofi; Santen Pharmaceutical; Vantive; Vertex Pharmaceuticals

Study Snapshot

Best Practices, LLC engaged 27 Medical Affairs executives representing 23 biopharmaceutical companies. Responses were segmented by organizational digital maturity into Innovators and the Emerging or Rest of Industry segment. The research team also conducted deep-dive interviews with select participants to capture practical insights into governance infrastructure, technology integration, platform scaling, and lessons from early AI adoption.

Key topics covered in this report include:

  • Medical Affairs AI Adoption Policy and Governance Frameworks
  • Technology Stack Assessment and Function-Level Satisfaction Benchmarks
  • Systems Integration Maturity and Technology Gaps
  • Strategic Technology Planning, Investment, and Approval Processes
  • Innovator vs. Rest of Industry Benchmarks and Lessons Learned

Key Findings

Select key insights uncovered from this report are noted below. Detailed findings are available in the full report.
  • AI Adoption Is Widespread but Remains Concentrated in Controlled Use Cases: Medical Information and Field Medical lead AI adoption across the benchmark class, but most activity remains focused on bounded, reviewable tasks. Human review is nearly universal, with 96% of organizations requiring review of all AI outputs before external use. However, only 42% define approved and prohibited use cases, and just 23% track or audit how AI tools are used. The result is a governance model that emphasizes output review more than ongoing oversight.
  • Integration Is the Biggest Technology Constraint: Sixty-four percent of organizations identify limited integration as their biggest Medical Affairs technology gap, yet only 28% consider integration very important when evaluating new technology. Just 4% report full integration within Medical Affairs, while 31% use ten or more point solutions in addition to core systems. These findings show how tool expansion can deepen fragmentation when integration is not treated as an evaluation and investment priority.
  • Governance Maturity Determines How Quickly AI Can Move Beyond Pilots: Half of the organizations studied have no formal governance framework or have one that is still in development, and only 27% have a formal framework in active use. Approval processes and staff training are the most common controls, while post-deployment monitoring and formal escalation paths remain less common. As approved AI use expands, these gaps can slow the transition from isolated pilots to scaled adoption.
Table of Contents

Sr. No.
Topic
Slide No.
I. Background InfoPg. 3
II. Executive SummaryPg. 9
III. Medical Affairs Digital Maturity: Industry Adoption and Governance PracticesPg. 17
IV. Critical Systems, Tools, and AI StreamsPg. 25
V. Governance and ApprovalsPg. 43
VI. Strategic Planning and InvestmentPg. 52
VII. Lessons from Innovators: Development and ImplementationPg. 68
VIII. AI Adoption Self-Assessment Tool for Medical Affairs LeadersPg. 71

    List of Charts & Exhibits

    I. Background Info

    • Project background and research methodology
    • Study participant demographics
    • Guide to reading this report
    • Glossary of key terms used in this report
    • Participating benchmark companies
    • Digital maturity framework

    II. Executive Summary

    • Key research findings
    • Implications and recommended actions: Five moves Medical Affairs leaders can make now
    • Risks and watch-outs: Six ways technology and AI programs stall in Medical Affairs
    • Path forward: Phased roadmap across 0 to 6, 6 to 12, and 12 to 24 months

    III. Medical Affairs Digital Maturity: Industry Adoption and Governance Practices

    • Self-assessed digital maturity of Medical Affairs organizations
    • Digital maturity and risk posture across the benchmark class, segmented by Innovators and Rest of Industry
    • Medical Affairs functions leading AI adoption, with use cases by function
    • AI governance landscape
    • AI adoption policy breakdown
    • AI governance practices
    • Section takeaways: How governance maturity influences the pace of AI adoption

    IV. Medical Affairs Technology: Critical Systems, Tools, and AI Streams

    • Average technology satisfaction by Medical Affairs functional area
    • System and tool satisfaction across all functional areas
    • Satisfaction with purpose-built and vendor-specific platforms across Medical Affairs functions
    • Satisfaction with general-purpose tools, including SharePoint, Copilot, Word, Excel, PowerPoint, and Outlook
    • Satisfaction with MSL field activity, CRM, and omnichannel capabilities
    • Satisfaction with data, insights, and analytics capabilities
    • Satisfaction with Medical Information capabilities
    • Satisfaction with Medical operations management capabilities
    • Satisfaction with grant management and sponsorship capabilities
    • Satisfaction with content development and approval capabilities
    • Satisfaction with scientific communications and publications capabilities
    • Satisfaction with congress and events planning capabilities
    • Satisfaction with training and learning management capabilities
    • Satisfaction with compliance and adverse event documentation capabilities
    • AI capability goal framework: Current pilot activity mapped against high-satisfaction, high-importance outcomes
    • AI capabilities: Pilot activity compared with rated importance, including a full view of key pilots
    • Section takeaways: How to prioritize technology improvements by function

    V. Medical Affairs Technology: Governance and Approvals

    • Formal Medical Affairs governance framework maturity across the benchmark class
    • AI governance mechanisms
    • Review and approval authority for new Medical Affairs technologies
    • AI evaluation criteria: The role of importance and integration in technology assessments
    • Technology evaluation criteria ranked by importance across the benchmark class
    • Approval timelines for an AI use on an existing system compared with a new platform
    • Escalated review: Organizations with a formal process and the triggers that activate it
    • Section takeaways: How governance structure and review processes influence approval speed

    VI. Medical Affairs Technology: Strategic Planning and Investment

    • Medical Affairs technology stack composition and approaches to planning and investment
    • Core systems and point solutions in use across Medical Affairs functions, segmented by digital maturity
    • Integration as the binding constraint: Key statistics on the Medical Affairs integration gap
    • The biggest Medical Affairs technology gap in leaders' own words
    • Technology gaps quantified
    • State of integration within Medical Affairs and across the enterprise
    • Approaches to integration: Low-friction pilots and deeper workflow builds
    • Obstacles to adopting new technology, ranked across the benchmark class
    • The biggest barrier to AI adoption reported by each organization
    • Approved AI tools, systems, and use cases in active use across Medical Affairs functions
    • Value realization from technology investment
    • Lessons for identifying and implementing new technology in Medical Affairs
    • New AI solution evaluation: Rated importance compared with actual evaluation priority
    • Technology investment priorities across the next 12 to 24 months
    • Section takeaways: Why integration constrains Medical Affairs technology strategy

    VII. Medical Affairs Technology: Development and Implementation Lessons From Innovators

    • Innovators compared with Rest of Industry: Lessons from industry leaders and innovators

    VIII. AI Adoption Self-Assessment Tool for Medical Affairs Leaders

    • AI adoption self-assessment tool: Decision-support checklist for evaluating and prioritizing Medical Affairs AI use cases

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