Scale AI with Confidence in Healthcare & Life Sciences
Turn AI ambition into measurable ROI, without compromising compliance
AI is no longer experimental in healthcare and life sciences. It’s operational, regulated, and under pressure to deliver real business outcomes fast. Yet most organizations are stuck between promising pilots and scalable impact.
What’s holding them back? And what separates leaders from the rest?
In this report, you’ll learn:
- How to embed governance early (“shift left”) to avoid delays
- Practical frameworks for auditability, explainability, and risk control
- Which use cases deliver measurable impact first
- How to modernize safely without disrupting regulated systems
Insights from 100+ healthcare & life sciences leaders
This report is built for life sciences leaders:
- Product & digital leaders in pharma, biotech, and medtech
- Clinical, regulatory, & data decision-makers
- Teams scaling AI in highly regulated environments
The organizations seeing real results from AI are embedding governance from day one, prioritizing measurable use cases, and tightly aligning product strategy with delivery.
Get the insights you need to move beyond experimentation and scale AI with confidence.
of product leaders feel the pressure to prove ROI on AI initiatives is increasing.
of product leaders report that their organization has adopted AI in the product development process.
of product leaders say unexpected governance issues have slowed their AI deployment.
Pressure to prove ROI is increasing & that’s a good thing
Growing pressure to prove ROI is pushing teams to anchor AI initiatives in measurable outcomes rather than rushed implementations. We are seeing organizations choose practical use cases they can measure over speculative bets. AI adoption is concentrated in research (52%), monitoring (50%), planning (46%), coding (45%), and testing (45%).
“Boards and investors aren’t asking how many releases you did this quarter, they’re asking what it delivered.”
— Sharon Lynch, Chief Executive Officer at Modus Create
Governance is the biggest blocker in AI integration
Governance remains one of the biggest challenges to scaling AI. 79% of organizations were forced to slow down their AI deployments last year due to unexpected regulatory or ethical considerations.
"AI creates new opportunities to trigger actions at speed and scale, which means oversight matters more than ever. Before you deploy, be clear about data access, human decision review, exception handling, and how you’ll evaluate and monitor the quality of AI decisions over time."
— Greg Sterndale, VP, Product Engineering Services
Leaner doesn’t mean fewer people
AI has brought unprecedented capabilities, but it has also widened one of product development’s oldest fault lines: the product strategy/delivery divide. 83% of leaders say following through on strategic elements of developing and launching new products is a barrier to success. That’s because AI is a force multiplier, and force multipliers expose weak foundations.
In our experience, product leaders already understand this dynamic, which is why more teams are restructuring by reskilling existing talent and hiring new talent than by reducing headcount.
“Expertise is what makes AI valuable. Without professionals who understand how to build, govern, and apply AI effectively, outcomes quickly become unreliable, insecure, and full of unintended consequences.”
— Jon Allegre, Chief Customer Officer at Modus Create