Adapt or Die: What CROs Must Do To Stay Relevant

I’ve never been one to sugarcoat things, so let me say it plainly: the contract research industry is undergoing a seismic shift—and not all CROs will make it through. As someone who spent 16 years working at CROs, it pains me to say it, especially as I see former colleagues and friends face layoffs. But as the saying goes, “When the going gets tough, the tough get going.” The question is—who’s willing to evolve, and who will cling to the old ways and fade out?

Fifteen years ago, I was a Clinical Data Coordinator at a large CRO. My tasks included manually cleaning data, cross-checking listings, and updating trackers. Even then, when electronic data capture (EDC) was new, I could see the writing on the wall. The work I was doing was important but repetitive, and ripe for automation.

But fast-forward to 2022, notably the introduction of ChatGPT and other LLMs, and the pace of digital disruption has accelerated beyond anything I ever imagined. In just the last two years, we’re not talking about marginal technological improvements—we’re witnessing a transformation that strikes at the very foundation of how the world, let alone how CROs operate.

The Tech Effect We’re Not Talking Enough About

CRO layoffs, sinking stock prices, and vanishing market share have become regular headlines in the Life Science Industry. People are shocked, frustrated, and scared—understandably so. You’ll hear a dozen reasons for the CRO shake-up: corporate restructuring, economic & political headwinds, biotech investment slowdowns, a sponsor shift toward FSP models…And while those all carry some truth, I believe there’s a deeper, more transformative force at play: technology.

More specifically, generative AI and data orchestration platforms are dismantling traditional labor-based CRO business models. These technologies don’t just support end-to-end trial execution, they perform it. And they do it with unmatched precision, speed, and scalability.

Tasks that once required teams of data managers, programmers, and medical reviewers—things like transforming raw data to standard models, developing data check plans, programming data checks, querying discrepancies, and performing eligibility reviews—can now be handled by trained AI agents. Not in theory. In practice. Today. Yes, Humans-in-the-Loop (HITL) oversight and critical judgement must still be applied, but the number of people involved is far less.

The Economics No Longer Work

CROs have long relied on revenue models built around FTEs and billable hours. But if AI Agents reduce human effort by 50%, 60%, even 90% in certain workflows, what happens to those bid grids? The legacy pricing structure collapses under its own weight.

Sponsors, understandably, aren’t willing to pay the same amount for work that’s now partially—or fully—automated. And they’re not going to tolerate inefficiency and siloed data, when faster, smarter alternatives exist. To stay viable, CROs need to rethink not just how they deliver services—but how they price, package, and position their value in an AI-driven world.

So Where Do CROs Go from Here?

Let’s be clear: CRO organizations can still be successful, but they must re-invent themselves. Here are few possible paths to consider:

1. Become a Tech-Led CRO Provider

Invest in platforms. Acquire innovation. Partner with AI leaders. By embedding leading-edge technology into your operating model, your brand evolves – from a typical service leader into an innovation company. Making tech the cornerstone of your services not only reduces your cost-to-serve but also unlocks new revenue streams—like SaaS licensing—that extend beyond headcount-based revenue. Think of it as moving from “Services Provider” to “Tech + Services Provider.” This allows CROs to shift from people-based pricing to outcome-based delivery powered by advanced technology.

2. Shift from Full-Service Outsourcing (FSO) to a FSP Model

Large pharma companies are increasingly adopting AI-powered platforms to bring more work in-house—giving them the flexibility and data access they want. Yet many still will require specialized partners for targeted service areas and rare diseases. Small and Mid-sized CROs, especially niche players, that pivot to a Functional Service Provider (FSP) model have a real opportunity to thrive in this space. They can focus on delivering expert, specialized support without incurring the full cost of tech ownership.

To maximize value in this new model, CROs must also invest in their people. Upskilling staff to support AI-driven workflows will be essential. Sponsors will expect service personnel to provide clinical expertise and technical oversight. Emerging new roles like AI Model Stewards, Clinical AI Analysts, and AI Governance Leads will become vital to ensure compliant use of AI in clinical research. By investing in developing this kind of talent now, CROs will be valued as trusted implementation partners in an AI-powered trial ecosystem.

3. Bet on Agentic AI as the New FSP Model

By 2030 (maybe sooner), I believe we’ll see a new outsourcing paradigm emerge: Agentic AI Outsourcing. A model where autonomous AI agents handle much of the operational lift, guided by orchestrator agents and governed by human oversight. This won’t be a small evolution of today’s FSP model—it will be a reinvention. A shift from resourcing bodies to deploying intelligence. And those who begin building toward it now won’t just keep pace—they’ll define the future of clinical development.

Closing Thoughts: Adaptability Isn’t Optional

As Charles Darwin famously said, “It is not the strongest of the species that survives, but the one most adaptable to change.” That quote has never been more relevant to CROs than it is today.

Traditional CROs, built around people and processes, are being challenged by platforms and code. CRO leaders must stop treating AI as a future disruptor. It’s already here. And for CROs, the choice is stark: evolve into tech-enabled, value-driven service partners—or risk being left behind.