Have you heard that AI is the wonder cure that will fix all that ails clinical trial recruitment? I bet you have, especially if you’ve attended any industry conferences this year. That was certainly my experience.

As a technologist who is developing an integrated platform for clinical trial recruitment, I’m open to emerging technologies (including AI) and the potential they hold. I guess I expected to hear about it, but I wasn’t expecting AI to be the most prominent topic I heard about — from both vendors and attendees. And there was something about the tone of the conversation that didn’t sit well with me.

Much of what I heard amounted to a kind of vague optimism that presents AI as a cure-all for challenges that have long plagued our industry, and I think the true benefits of what AI can do are easily lost in such broad strokes, which are often inaccurate as well.

In this blog, I intend to clarify the conversation about AI in clinical trial recruiting by addressing three key points: what AI is at a basic level, what it can do, and what it can’t do.

Let’s start by establishing a realistic definition of AI as it relates to our industry.

AI is a tool.

IBM defines AI as “technology that enables computers and machines to simulate human intelligence and problem-solving capabilities.” Along this line of thinking, I see AI as a tool — a uniquely capable tool, but a tool nonetheless. It’s useful to demystify AI by characterizing it this way because, like a hammer for a carpenter or a cast iron skillet for a chef, the tool’s utility is limited to the skill of the hands wielding it.

AI is not magic. And in the case of clinical trial recruitment, its usefulness is determined by the skill level and domain expertise of the humans using it. In the right hands, AI can be extremely helpful for several key activities in the patient recruitment process.

AI excels at certain tasks, under ideal circumstances.

At this point in its development, AI’s most beneficial use case is augmenting human performance at certain tasks, such as pattern and image recognition, data analysis and visualization, and automation of repetitive tasks. In clinical trial recruitment, AI can be useful for decision support — helping humans process massive amounts of data very quickly to make faster, more informed decisions.

In each of these examples, however, it’s crucial to note that AI’s utility is based on high-quality inputs in the form of data and the underlying skills and processes used to gather and organize that data.

For example, AI can help a clinical researcher quickly process and analyze data from thousands of potential patients — but it will generate useless recommendations if the quality of the data is poor. Without stable and efficient processes for lead identification, data collection, and cleaning, any AI that’s used will actually be useless.

In practice, this means that while an AI application can be the cherry on top of a mature, highly productive recruitment engine, it will be far less useful to an organization that is lacking any of the fundamental elements necessary for successful patient recruitment.

AI cannot replace human know-how and critical soft skills.

AI in its current state simply can’t replace the value of human experience and intellect. Stanford University’s Artificial Intelligence Index Report 2024 makes a useful comparison between human and AI capabilities:

“AI has surpassed human performance on several benchmarks, including some in image classification, visual reasoning, and English understanding. Yet it trails behind on more complex tasks like competition-level mathematics, visual commonsense reasoning, and planning.”

In the context of clinical research, building an effective recruitment engine certainly qualifies as a complex task. If an organization lacks critical skill sets and effective processes and workflows for patient recruitment, AI can’t help them “fake it until they make it.”

AI also falls short when it comes to the crucial human element of recruitment — actually talking with patients, listening to their concerns, informing them about options, and helping the patients with the most to gain from a given trial see the benefit of participating.

Regardless of the sophistication of the tools (AI or otherwise) being used to generate a list of names, every successful recruitment operation is staffed by talented people with the people skills and domain expertise needed to help patients cross over from prospects to referrals.

Despite the Gold Rush mentality swirling around the promise of AI, clinical research sites and organizations should first focus on bringing in or cultivating the right expertise, building a solid sales and marketing organization, and formalizing processes to be the foundation of patient recruitment efforts before thinking about making an investment in any particular technology or AI tool.

It’s not all sizzle.

While the level of hype around AI in clinical research is certainly overdone these days, there is good reason for optimism around the potential these technologies hold for giving researchers more time to focus on the most compelling problems instead of having to sort through the mundane.

The most interesting dynamic I see emerging is one of a complementary relationship where AI helps researchers by giving them more bandwidth to tackle the most complex challenges. But for now, the fundamentals of patient recruiting will be much greater factors in a site’s success or failure than any particular AI tool.

So where should sites start when they’re ready to up their patient recruitment game?

Build a sustainable patient recruitment engine.

One of the persistent challenges faced by the clinical research organizations, sites, and site networks we serve is that they lack domain expertise in marketing and sales within the clinical context. Building these skill sets takes time and is expensive, and our customers often struggle with acquiring the expertise they need.

My best advice is to start by getting really good at the simple stuff — marketing, sales, and authentically connecting with patients — before investing in shiny new technologies that will not help you build the fundamental skills needed to succeed. C6 | Site Solutions specializes in helping clinical research sites build these core capabilities from the ground up.

We help each site, site network, and CRO we partner with accomplish the following:

• Cultivate domain expertise in sales and marketing in the clinical context
• Build and implement the foundational processes needed to capitalize on the incredible potential of AI
• Ensure long-term economic viability by identifying and managing toward an ideal patient acquisition cost (PAC)

Our customers also gain access to our purpose-built recruitment platform with built-in automation and AI to help them maximize the ROI from their new recruitment engine.

Contact us if you would like to learn more about our approach to patient recruitment. We would love to learn more about your research.