Webinar: Advancing Your Quality Maturity

Discover your potential savings with our ROI Calculator

Calculate ROI now

Market Research Report

AI in Life Sciences: What the Industry Is Really Saying.

The Pulse on Adoption, Opportunities, and Impact

AI is moving quickly across life sciences, but many organizations are still working to move beyond experimentation into scalable, compliant adoption.

Presented by ComplianceQuest, this Axendia market research report captures what ~200 life sciences professionals are actually experiencing across AI adoption, AI readiness, quality operations, validation, manufacturing, and regulatory workflows.

The findings highlight a growing reality for life sciences quality leaders: AI progress depends on trusted data, connected systems, governance, and operational readiness.

Please confirm your details

By submitting this form you agree that we can store and process your personal data as per our Privacy Statement. We will never sell your personal information to any third party.

Enter Captcha

AI trends in life sciences

What You'll Learn

Inside the Report:

Where is AI adoption growing in life sciences?
What is stopping companies from scaling AI?
How are quality teams using AI today?
Why do data quality and governance matter for AI?
Where will companies invest next in AI?

Key Findings for Life Sciences Quality Leaders

AI adoption is moving from pilots to operations^*

0%

now report formal AI leadership or governance initiatives.

Data remains the biggest challenge^*

0%

of respondents cited data quality, consistency, and availability as top barriers to AI in QMS environments.

Quality is emerging as a high-value area for AI^*

0%

identified deviation and investigation management as one of the most valuable AI applications in QMS.

Organizations expect AI investment in quality to grow^*

0%

expect increased AI spending in quality.

^*Axendia Market Research: AI in Life Sciences: What the Industry Is Really Saying. The Pulse on Adoption, Opportunities, and Impact

The report provides a practical view of where the industry stands today, and what organizations need to address to scale AI responsibly.