At last year’s Global Healthcare Conference, interest in AI was beginning to surge. This year, it’s reached a fever pitch.
A record one in four healthcare investment dollars is now going to companies leveraging AI. And AI is beginning to drive transaction activity in the sector, from IPOs like Tempus, an AI-enabled precision medicine leader, to M&A in medical devices, biotech, and beyond.
Still, separating the hype from near-term commercial opportunities remains a challenge for sponsors and corporates, especially in such a fast-moving space.
Jefferies Insights sat down with banking leaders in provider services and biotech to get their take on how AI is being integrated into healthcare—and where it’s still mostly noise.
Can AI Ease the Strain on Provider Services?
The provider services sector faces several challenges. Demand for healthcare is surging, but a growing labor shortage makes it harder for providers to keep up. At the same time, profit pools are shrinking amid ongoing inflation and rising labor costs.
Providers are under pressure to deliver care more efficiently—and many are turning to AI for support. A recent survey found that 75 percent of providers increased IT investments over the past year, focusing on technologies that can optimize operations and reduce clinical burden.
The question is, are AI-powered technologies ready to make an immediate impact?
Jefferies Insights posed this to Ashwin Pai, Managing Director in Healthcare Investment Banking. With nearly two decades of experience in provider services, Pai regularly supports transactions and fundraising for emerging technology leaders in the sector.
“There’s a lot of interest and activity in the provider services sector around AI,” Pai shared. “The opportunity set is broad, and many technologies are still in the early stages of testing and development. But in some areas, we’re already seeing AI tools applied to great effect.”
Providers are already piloting AI tools in clinical applications like documentation, where they’ve shown promise in easing administrative burdens on clinicians. There’s also hope that AI can support more electronic health record (EHR) functions, such as responding to patient inquiries and assisting with medical coding.
“Beyond admin, there’s incredible potential for AI in clinical decision-making,” Pai explained. “We’re already seeing AI-powered wearables introduced, giving providers much deeper insight into patients’ conditions and progress, even in remote settings. And that’s just the start—AI will soon be a key tool in medical imaging, predictive analytics, and a true clinical support partner for physicians.”
Pai also pointed to the potential of AI in areas like radiology, supporting physicians in analyzing medical imaging and making diagnoses. There is ongoing innovation around predictive AI to detect diseases like cancer and neurodegenerative disorders earlier than human diagnosis typically allows.
Transaction and fundraising activity around the integration of AI in provider services is gaining momentum, as more sponsors and strategic buyers hone in on opportunities. Pai highlighted Microsoft’s $1.5 billion investment in G42, a UAE-based AI company leading advancements in AI-powered diagnostics and digital health, as a key example.
What AI Can (and Can’t) Do for Biotech
Few sectors have sparked as much excitement around AI as biotech. The potential for AI to revolutionize drug discovery—streamlining a notoriously long and costly process—carries significant clinical and financial promise.
However, in these discussions, hype is often mistaken for near-term potential. That’s why Jefferies Insights spoke with Dr. Gil Bar-Nahum, EMEA Head of Biotechnology, who brings two decades of experience in biotechnology and holds a PhD in biochemistry from New York University.
“There’s no doubt that AI’s potential in biotech is exciting. Machine learning can help us better understand drug efficacy and optimize clinical trials—and that’s just the beginning,” Bar-Nahum shared. “But if you’re asking whether AI can make an impact on my five-year, $200 million clinical trial today? We haven’t seen it yet. So the hype has tempered a bit.”
The biggest hurdle for early-stage biotech companies is fundraising. Drug discovery costs hundreds of millions of dollars—and the field is inherently high risk. Clinical trials for new drugs have a historical success rate of just 7.9 percent. The time horizon for biotech investments is also uniquely long, with regulatory approval and commercialization taking years, even for successful breakthroughs.
This created a tough market in recent years, as biotech grappled with high interest rates. Earlier this year, equity capital markets began to reopen, fueled by pent-up demand and expectations of an easing cycle. Financing is beginning to trickle through again for development-stage biotech ventures.
“The biggest near-term opportunity for AI is making clinical trials more efficient,” Bar-Nahum explained. “Preclinical biotech companies burn through cash, and in a risk-off environment, that makes things tough. Where AI can cut costs and streamline operations, it can make a big impact in R&D—like streamlining clinical data and analyzing patient populations.”
Some of these opportunities are already being realized, such as a collaboration between Keio University, Mitsubishi Tanabe Pharma Corporation, and Boston-based Neuro Discovery Lab. Researchers are using machine learning in a knowledge graph approach, analyzing potential relationships between disease and biological function in large quantities of patient data. The team reports significant gains in efficiency.
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Opportunities to apply AI in healthcare are exciting and diverse, varying widely by sector. In some cases, there are near-term opportunities for AI-powered technologies to make healthcare more predictive, efficient, and impactful. In others, meaningful applications are still a long way off.
Still, one thing is clear: no matter their role, everyone in healthcare is thinking about it.
For more insights on AI’s near- and long-term potential in healthcare, follow Jefferies’ 2024 Global Healthcare Conference in London.
