October 26, 2026
From industry evidence to enterprise AI strategy.
THE SIGNAL
The life sciences industry is producing an increasingly valuable body of research on artificial intelligence.
And the findings deserve attention.
NVIDIA's 2026 State of AI in Healthcare and Life Sciences reports that 70% of respondents work in organizations actively using AI.
Benchling's 2026 Biotech AI Report identifies meaningful adoption across scientific workflows, including literature review, protein analysis, and scientific reporting. Deloitte's 2026 Life Sciences Outlook presents a more sobering perspective: Only 22% of surveyed leaders reported successfully scaling AI, and just 9% reported achieving significant returns.
McKinsey's 2026 State of AI research adds a broader enterprise perspective, examining how organizations are moving beyond experimentation toward scaling and measurable value.
Different studies. Different populations. Different methodologies.
But together, they reveal something important.
AI is advancing. Organizations are investing.
Applications are becoming more sophisticated.
Yet the journey from technological capability to sustained organizational performance remains uneven.
And that raises a question worth exploring.
What are we still missing?
WHY IT MATTERS
Research plays an essential role in helping executives understand emerging technologies.
It identifies trends, measures adoption, highlights barriers, and informs investment decisions.
But enterprise leaders face a different challenge.
They must translate that knowledge into decisions about their own organizations.
Consider what an executive needs to know when developing an AI strategy.
Where should we invest?
Which capabilities should we build internally?
What should we buy? How prepared is our workforce?
Who should own AI transformation?
How should governance evolve?
Which workflows should change?
And what evidence will demonstrate that our investments are creating value?
These questions aren't simply about technology.
They're about organizational readiness, strategic priorities, operational integration, leadership, and execution.
That's where we believe additional life sciences-specific research can make a meaningful contribution.
THE CURBSIDE VIEW
At RISE, we believe the next important contribution to enterprise AI strategy won't come from any single research report.
It will come from connecting multiple forms of evidence.
We see three complementary sources of insight.
LEVEL 1 — INDUSTRY INTELLIGENCE
What is happening across the market?
Research from organizations such as NVIDIA, Benchling, Deloitte, and McKinsey helps establish a foundation. It provides evidence about adoption, investment, technology applications, operational challenges, and reported business outcomes.
LEVEL 2 — ORGANIZATIONAL INTELLIGENCE
Why are some organizations progressing more effectively than others?
This is the central opportunity behind The RISE Index™ 2027.
We're examining the conditions that influence enterprise AI adoption and transformation across life sciences.
Leadership alignment.
Governance and accountability.
Workforce readiness. Technology and data capabilities.
Operational integration.
The ability to demonstrate measurable business impact.
We also want to understand how perspectives differ across functions and between pharmaceutical and biotechnology organizations and the companies serving them.
LEVEL 3 — STRATEGIC INTELLIGENCE
What should leaders actually do?
This is where research must become practical.
Industry findings and organizational evidence can inform a strategy, but they don't automatically produce one. Leaders still need to determine which capabilities matter most, what to prioritize, how to sequence investments, and how to establish accountability.
That requires interpretation, context, and judgment.
And that's where RISE intends to contribute.
Our ambition is to connect credible external research, original organizational insights, and experienced life sciences leadership perspectives into practical guidance for enterprise AI transformation.
Not simply describing the market. Helping leaders navigate it.
THE MOVE
If you're developing your organization's 2027 AI strategy, we'd encourage you to think about five areas.
1. ESTABLISH THE EVIDENCE
Use credible industry research to understand where AI is advancing and where measurable value is emerging.
2. ASSESS ORGANIZATIONAL READINESS
Understand your organization's capabilities, limitations, and barriers before committing to another wave of technology investment.
3. CONNECT AI TO BUSINESS PRIORITIES
Identify the decisions, workflows, and business outcomes that matter most.
4. DESIGN FOR EXECUTION
Establish ownership, governance, workforce support, operational integration, and measurable success criteria.
5. BUILD A LEARNING SYSTEM
Treat AI strategy as an evolving discipline.
Reassess capabilities, measure outcomes, incorporate new evidence, and adjust priorities as the technology and organization mature.
The objective isn't to create the longest AI roadmap. It's to develop a strategy that the organization can actually execute—and improve over time.
THE RISE INDEX™ 2027
We're developing The RISE Index™ to contribute an additional layer of evidence to the enterprise AI conversation.
Our research is focused on understanding how life sciences organizations are approaching AI adoption, operational integration, organizational readiness, and measurable impact. As responses accumulate and the findings are validated, we intend to examine patterns, differences, and relationships that may help leaders better understand the conditions associated with successful transformation.
Our longer-term ambition is to connect those findings with established industry research and RISE's proprietary frameworks to help inform a more practical enterprise AI strategy.
The research is underway.
The conclusions are not predetermined. And that's precisely why participation matters.
ONE QUESTION TO TAKE WITH YOU
If you had access to every AI research report published this year, would you have enough information to know what your organization should do next?
Or would you still need to understand your organization's readiness, priorities, people, and ability to execute?
That distinction may be the missing piece.
HELP SHAPE THE RISE INDEX™ 2027
We're inviting life sciences leaders to contribute their perspectives to our enterprise AI adoption research.
The survey takes approximately 8–10 minutes.
Participate here:
https://therisegroup.ai/research/enterprise-ai-adoption-2027
Your perspective can help us develop a more practical understanding of AI transformation across life sciences.
SOURCES & FURTHER READING
NVIDIA — State of AI in Healthcare and Life Sciences (2026)
https://blogs.nvidia.com/blog/ai-in-healthcare-survey-2026/
Benchling — 2026 Biotech AI Report
https://www.benchling.com/biotech-ai-report-2026
Deloitte — 2026 Life Sciences Outlook
https://www.deloitte.com/us/en/insights/industry/health-care/life-sciences-and-health-care-industry-outlooks/2026-life-sciences-executive-outlook.html McKinsey — The State of AI in 2026: On the Road to ROI
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
RISE | GTM Strategy. Strategic Business Development. Commercial Excellence. AI Transformation.
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