In a recent issue of BioSpace, it was reported that 70% of pharma leaders see AI as an immediate priority — and among the Big Pharma brands, that number jumps to 85%. In that article, I echoed my observations that biopharma companies are bullish on AI investments — even those that have put most capital expenditures on hold.
This surge in AI interest isn’t just a passing trend — it’s a strategic pivot. Across the life sciences and medical device sectors, leaders are recognizing AI as a catalyst for innovation, efficiency and competitive advantage. From drug discovery to regulatory compliance, and from smart devices to workforce transformation, AI is reshaping how these industries operate.
In this article, I’ll explore the key use cases driving adoption, the workforce implications and how medical device and life science companies can bridge the talent gap to meet the moment and stay ahead.
AI Adoption: Driving Innovation Despite Budget Constraints
Despite budgetary concerns, visionary leaders are seeing the need to streamline operations and drive more value without losing the ability to innovate. And AI is the secret to achieving these objectives.
AI in Life Sciences
The BioSpace article, referencing a study by Define Ventures, reported that 85% of respondents have leveraged AI for analyzing real-world data, and the same percentage have used it for medical writing — making those the top two current use cases.
In life sciences, AI is being used to:
- Accelerate Drug Discovery and Development
- Predictive modeling for molecule behavior
- AI in clinical trial design and patient recruitment
- Faster identification of promising compounds
- Enable Precision Medicine and Genomics
- AI-driven analysis of genetic data
- Personalized treatment plans based on biomarkers
- Supporting rare disease research and orphan drug development
- Enhance Clinical Decision Support
- AI-assisted diagnostics and imaging
- Real-time patient data analysis for treatment optimization
- Integration with electronic health records (EHRs)
- Streamline Regulatory Compliance
- Automating documentation and submission processes
- AI for pharmacovigilance and adverse event detection
- Improving audit readiness and traceability
AI in Medical Devices
The use of AI has exploded among medical device companies — with over 1,200 AI/ML-enabled devices now registered with the FDA. This represents an astounding 35X increase since 2015.
Common use cases include:
- Smart and Connected Devices
- Embedded AI for real-time monitoring and feedback
- Devices that adapt to patient behavior and conditions
- Integration with mobile health apps and wearables
- Predictive Maintenance and Performance Optimization
- Detecting device malfunctions before failure
- Enhancing reliability and reducing downtime
- Data-driven insights for product improvement
- Manufacturing and Quality Control
- Defect detection and process optimization
- Robotics and automation in device assembly
- Ensuring consistency and compliance in production
- Post-Market Surveillance and User Feedback
- Improving device safety and efficacy through user data
- Remote patient monitoring and telehealth
- Real-world evidence generation for regulatory and R&D use
With such widespread adoption across the life science and medical device industries, it’s no surprise that companies are racing to invest in AI. But speed isn’t just about technology — it’s becoming a strategic differentiator.
As the article noted, clinical data and patent length used to be core differentiators for many large pharma and life science organizations, but the Inflation Reduction Act and post-market competition are starting to erode them. Now, how quickly companies discover, develop and distribute drugs is becoming just as — if not more — important.
Workforce Transformation: Meeting the Demand for AI Talent
The workforce implications of all this innovation cannot be overstated. In both industries, there is a growing need for candidates who understand both AI algorithms and clinical contexts — or more simply put, science and tech. This combination is in short supply, making recruitment highly competitive.
Life Science Hiring Trends
AI expertise is now one of the top three hiring priorities for life science and pharma leaders. Manpower’s analysis of 2,404 job types reveals that in 2025:
- 57.8% of all tracked roles are completely new
- There are 1,389 entirely new roles
- Cybersecurity engineering tops the list, with 11 related postings
At the same time, we’re predicting declining demand for:
- Data scientists
- Senior software engineers
- Software test engineers
Medical Device Hiring Trends
In this vertical, demand is rising for professionals skilled in AI compliance, validation and regulatory affairs. The explosive growth has created 19,000+ current job openings and driven a 77% increase in total job postings year-over-year, according to Manpower’s findings. This has led to staggering skill and labor shortages, with the average time to fill AI/ML Specialist positions taking four to six months.
Meanwhile, roles focused on manual tasks — such as data entry, protocol drafting, and document review — are seeing reduced demand.
Bridging the Talent Gap: Upskilling and Strategic Support
ManpowerGroup’s survey found that among healthcare and life sciences employers looking to accelerate AI adoption, employee skills gaps were a top challenge. It’s no wonder that skill gaps are a major concern given the current hiring data.
The key to closing this widening gap is reskilling or upskilling. This problem isn’t unique to life sciences and medical devices. According to the World Economic Forum’s Future of Jobs report, 60% of the global workforce will need upskilling and reskilling before 2027.
Upskilling your current employees should be job one on your priority list. Not only will you gain the skilled talent you’ll need, but you’ll improve employee retention and lower your total workforce costs. For more on the how and why of reskilling, I invite you to read The Human Resource: Is Your People Strategy Green?
Turning the workforce you have into the workforce you need isn’t easy. One answer is to fill skills gaps with contingent talent while you seek the ideal permanent hire — or while your upskilling efforts are underway. Outsourcing an upskilling program is another smart way to deliver results quickly.
How Manpower Can Help
At Manpower, we specialize in putting people to work in these specialized industry verticals.
While many of the newest roles haven’t yet appeared in job requisitions, we’re already placing talent with the skills these emerging positions demand. Here are just a few examples:
- Data Scientists
- Statisticians
- Research Scientists
- Bench Scientists
- Chemists
- Bio Techs
- Lab Techs
- Process Control Engineers
- Embedded Systems Engineers
- Design Engineers
- Robotics Techs
- Automation Techs
- Engineering Techs
Our services are tailored to the highly complex and competitive FDA-regulated industries. With proven success supporting the entire life cycle across the globe, Manpower is uniquely positioned to partner with medical device and life science companies as they innovate for the future.
Let us help you build the workforce you’ll need to meet tomorrow’s challenges. Contact us today.
About the Author
Greg Coir
Former Head of Vertical Strategy-Healthcare and Life Sciences, NA, ManpowerGroup
Greg is a healthcare staffing executive with over 25 years of experience delivering staffing and consulting solutions to life sciences and healthcare organizations across the U.S. From 2024-2026 he led the Healthcare and Life Sciences Vertical Strategy at ManpowerGroup North America. Greg holds a bachelor's degree in business management from Merrimack College and is recognized for his strategic leadership and growth-oriented approach. He is based in the Greater Boston area.