Your sites are ignoring your AI tools
Here's the real reason why... and how to fix it to accelerate recruitment.
HT4LL-20250622
Hey there,
We're investing millions in AI to revolutionize our clinical trials, but the people on the ground—the ones actually running the studies—are barely using the tools we provide.
This isn't just a tech issue; it's a strategic threat. As an R&D executive, your biggest challenges are slow recruitment, ballooning budgets, and ever-tightening timelines. You're counting on technology to be the solution, but there's a massive disconnect between our high-level strategy and the day-to-day reality at the clinical site. The painful truth is that sites aren’t resistant to technology; they're resistant to technology that adds to their already crushing workload without providing an immediate, tangible benefit.
So today, we’re going to break down how to bridge this gap and turn your tech investments into a real competitive advantage. We’ll cover:
Why your current AI strategy is failing to engage your sites.
Proven models for reaching vast, untapped patient populations.
A 3-step framework to actually accelerate trial recruitment.
If you’re a leader trying to innovate past the traditional, slow-moving trial model to deliver results faster, then here are the resources you need to dig into to make it happen:
Weekly Resource List:
5 Ways AI Is Changing Clinical Research — And How To Embrace It (6 min read)
Summary: This piece from Clinical Leader provides a fantastic overview of how AI is already impacting trial processes. It moves beyond theory and details the immediate, practical applications in patient recruitment, protocol design, and site selection.
Key Takeaway for You: AI isn't a future promise; it's a present-day tool. The article shows that using AI to scan EHRs can identify eligible patients with up to 96% accuracy, directly addressing a primary bottleneck in trial enrollment. This is about augmenting your teams, not replacing them.
Are Sites Even Using AI? How Sponsors Can Support Uptake (5 min read)
Summary: A critical, on-the-ground perspective that explains the disconnect between sponsor-level AI enthusiasm and site-level adoption. It highlights that sites are overwhelmed and skeptical of tools that don't offer clear time savings.
Key Takeaway for You: The "killer app" for sites is anything that reduces administrative burden. Sponsors and CROs hold the keys to adoption and must invest "downstream" by funding and providing site-facing tools as part of the trial budget, rather than expecting sites to figure it out themselves.
Community-Based Trials: Bringing Clinical Research Close to Home (4 min read)
Summary: STAT News details Eli Lilly's successful strategy for moving trials out of major medical hubs and into local communities. It’s a blueprint for making participation feasible for the vast majority of patients who live more than 25 miles from traditional research centers.
Key Takeaway for You: Geography is a primary barrier to recruitment. By leveraging local clinics for routine trial activities (labs, imaging), you can dramatically expand your patient pool. This model is proven, inspectable, and requires robust central oversight—but the payoff in patient access is enormous.
Physician Survey on AI in Health Care (5 min read)
Summary: The American Medical Association (AMA) reveals findings from a survey on how physicians are actually using AI. Adoption has skyrocketed from 38% to 66% in just one year, driven almost entirely by the desire to reduce administrative work.
Key Takeaway for You: Physicians are telling us exactly what they want from technology. The #1 requested feature in an AI tool is a functional feedback loop, followed by data privacy and seamless workflow integration. This is a clear roadmap for deploying technology that investigators will actually use.
Remote Digital Tools for Preclinical Alzheimer's (7 min read)
Summary: This Nature review covers the maturation of remote digital tools for assessing cognition, highlighting their feasibility and reliability. It shows how these tools can detect subtle changes that traditional in-clinic tests miss.
Key Takeaway for You: For indications like Alzheimer's, digital tools paired with blood-based biomarkers can revolutionize pre-screening. This combination streamlines the identification of eligible participants, significantly reducing screen failure rates and trial costs before a patient ever steps foot in a clinic.
3 Steps To Accelerate Recruitment, Even If Your Sites Are Skeptical
To actually see an ROI from your tech investments and hit your recruitment targets, you need a handful of things. It’s time to stop pushing generic technology and start solving the real-world problems that are holding your trials back.
Here’s how to reframe your approach.
1. Target the Site's #1 Problem: Administrative Burden
The first thing you need is an AI strategy that is laser-focused on reducing the administrative workload at your clinical sites.
Your teams might be excited about using AI for predictive modeling or protocol optimization, but to a site coordinator buried in paperwork, those benefits are abstract and invisible. The AMA survey is crystal clear: physicians are adopting AI at a breathtaking pace, but only for tools that automate documentation and reduce their administrative tasks. For sites, the most valuable AI application is one that gives them back time. AI-powered patient identification that scans EMRs to create a list of potential participants does just that, saving coordinators countless hours of manual chart review.
Your Actionable Step: Audit the technology you deploy in your trials. Is it designed to make the sponsor’s life easier, or the site’s? Mandate that your trial budgets include funding for site-facing tools that demonstrably automate administrative work.
2. Bring the Trial to the Patient's Community
Next, you need to expand your thinking from "decentralized trials" to "community-based trials." The distinction is crucial.
The single greatest barrier to patient recruitment is geography. The traditional model, which expects patients to travel to a major urban medical center, automatically excludes the vast majority of the population. As Eli Lilly’s success shows, a proven solution is to bring the trial to the patient. This means partnering with local doctors and community clinics to handle routine trial activities like labs, infusions, or imaging, all under the supervision of the central PI. This isn't just a nice idea; it's an inspectable, scalable blueprint that fundamentally expands your recruitment pool by meeting patients where they already are.
Your Actionable Step: Task your feasibility teams with mapping patient populations against community healthcare infrastructure, not just large research institutions. Launch a pilot study that leverages local providers for non-specialized tasks and measure the direct impact on patient recruitment and retention.
3. Build a Feedback Loop for Everything You Deploy
Finally, you need a non-negotiable requirement for a robust, visible feedback mechanism for every single piece of technology you ask a site to use.
According to physicians, the single most important attribute of an AI tool isn't a flashy feature—it's a working feedback loop. Site staff need to know that if a tool is buggy, confusing, or simply doesn't fit their workflow, they can report it and trust that someone will listen and fix it. Without this trust, your expensive, cutting-edge technology quickly becomes ignored "shelfware." A feedback loop transforms complaints into free, high-value user experience research that allows you to improve your tools and processes.
Your Actionable Step: Make a simple, effective feedback and support system a mandatory clause in your contracts with all clinical tech vendors. Review site feedback metrics with your clinical operations leaders quarterly. This isn’t about logging complaints; it’s about fostering partnership and ensuring the tools you pay for deliver real value.
PS...If you're enjoying Healthtech for Lifescience Leaders, please consider referring this edition to a friend.
And whenever you are ready, schedule time to get leadership coaching or mentoring support.