Perspectives on AI, Analytics, and Transformation
Selected writing on how healthcare and life sciences organizations can apply data, analytics, and AI to transform how they operate and deliver value. I focus on moving beyond experimentation to building institutional capabilities that enable sustained impact.
AI Is Not a Technology Problem — It’s an Operating Model Transformation
Most organizations treat AI as a technology initiative. In healthcare and life sciences, real value comes from transforming how institutions operate.
Exploring the FDA and EMA Principles of Good AI Practice
Is your organization ready for AI regulation? Jason Burke unpacks the FDA and EMA's Good AI Practice guidance and the three capability gaps life sciences leaders must address now.
Why AI Feels Like the Wild West
AI in life sciences feels chaotic — but it doesn't have to. Explore the 7 key tensions facing industry leaders and the principles that separate AI winners from the rest.
CROs in the Age of AI
Discover how AI is transforming the $100B CRO industry — from business model shifts to data strategy — and what clinical research leaders must do to stay competitive.
Technology Design in the Age of AI
AI is disrupting over 75 years of computer-related design. The changes reflect an amazing inflection point that both business and technology leaders need to reflect in their strategies.
Avoiding AI’s False Prophets
Many AI media pundits are guiding industry leaders astray with advice that is not grounded in what makes AI actually generate value. I offer some perspectives based on real-world experience.
AI Chain of Reasoning Access Should Be Required
AI models and LLMs that don’t provide access to chain of reasoning should not be deemed as trustworthy for life sciences and healthcare applications.
The Artificial Intelligence Trends Shaping 2025
Explore the transformative AI trends poised to redefine technology and society in 2025, from agentic AI and device integration to the evolution of web search and content creation.
Using AI Archetypes in Designing Digital Transformations in Life Sciences and Healthcare
Patterns in the intended uses of artificial intelligence (AI) increasingly reflect the many roles AI can serve in life sciences and healthcare solutions and workflows.
Eight Ways Life Sciences Leaders Can Kickstart Artificial Intelligence
Industry executives are feeling pressure to develop AI plans, and many roadmap techniques can help without creating big or risky plans.
Unlocking Data Governance for Strategic Growth
Though data governance is often a taboo topic among executives, thoughtful investments in data asset improvements can have a transformative impact on data trust and AI capabilities.
FDA IT Strategy in a World of AI
The US Food and Drug Administration’s updated IT strategy highlights the agency’s planned direction and investments while also demonstrating fundamental industry challenges ahead.
Managing Emerging AI Cybersecurity Risks
Though offering impressive capabilities, the rapid adoption of artificial intelligence capabilities within the life sciences and healthcare sectors also brings notable risks that must be managed.
Building Data-Driven Cultures Through Trust
Organizational aspirations and plans for becoming more “data driven” often do not reflect the basic reality that building a data-driven culture is a change management challenge rooted in trust.
How AI is Reinventing Medical Innovation
The health and life sciences industries are facing a paradigm shift where emerging technologies like artificial intelligence (AI) and genomic sciences are unlocking new ways to understand and treat medical conditions.
Building a Data-Driven Business Strategy
Life sciences and healthcare leaders today continue to face a conundrum: they want data-driven businesses, but they don’t trust their data or insights.