Healthcare is facing a delicate balancing act; systems are striving to elevate care, sustain their workforces, and stay financially viable — all at once. That reality is reshaping what progress looks like inside hospitals and health systems.
Efficiency has become a guiding principle. According to Wolters Kluwer’s 2025 Future Ready Healthcare Survey, 77% of healthcare professionals identify operational efficiency as a top priority and 76% are equally focused on reducing clinician burnout. Another 80% cite optimized workflows within and across departments as a leading organizational goal.
Increasingly, AI is emerging as the catalyst to achieve these aims when applied with intention, rigor and a clear understanding of where it can create real value.
To explore how AI can improve clinical workflows, Becker’s Healthcare spoke with Bill Flannery, PhD, vice president of advanced technology development at Wolters Kluwer. Dr. Flannery leads the company’s AI Center of Excellence and has spent nearly three decades advancing AI and machine learning across multiple industries, including healthcare.
Embedding AI where it matters most
For Dr. Flannery, AI’s value isn’t in flashy applications or automation for its own sake. It lies in helping clinicians work more effectively and sustainably, grounded in evidence, validated by experts and embedded in everyday workflows.
While AI can help reduce tedious, time-consuming tasks that weigh on clinicians, its application shouldn’t force them to learn new systems or disrupt established routines. “AI should work in the background whenever possible,” Dr. Flannery said. “You want it to require little to no effort for clinicians to start adopting it.”
That integration is already evident in areas like ambient documentation, message drafting and clinical decision support. When clinicians can access the latest evidence-based guidance at the point of care, or when an AI tool can pre-populate documentation in real time, the impact goes beyond efficiency. It improves communication, strengthens trust between clinicians and patients, and helps care teams focus on meaningful clinical interactions.
“Do you want the burned-out doctor, or the one who’s had a much more reasonable day?” Dr. Flannery said. “Ultimately, these tools should reduce burden and improve clinicians’ quality of life, leading to better patient outcomes. “
Designing for trust — collaboration at the core
While the potential of AI is vast, success depends on one critical factor: trust. And building that trust, according to Dr. Flannery, starts with including clinicians in the design and development process.
“As a technologist, I need to understand the user,” he said. “You have to include clinicians in designing and developing any AI-driven workflow. That’s how you develop and build trust in that system.”
At Wolters Kluwer, this collaboration goes beyond design. Each tool is rigorously validated through clinician input and real-time feedback. Users can flag issues in just a few clicks — or even by voice, through mobile integration — and that feedback is triaged daily by clinical experts. Critical notes are escalated to senior clinicians, Dr. Flannery said.
This rapid-response loop is meant to solve individual issues and help refine the system continuously. As Dr. Flannery described it, every piece of feedback becomes new test data, driving a process of continuous improvement that keeps AI aligned with the realities of clinical practice.
‘Grounding’ AI with trusted, clinical evidence
Dr. Flannery emphasized that the most responsible and effective clinical AI solutions are rooted in evidence. While large language models have advanced rapidly, he said they still require clinical context and expert oversight to ensure their output reflects real-world care.
To bridge that gap, Wolters Kluwer grounds its AI systems in trusted, evidence-based information — combining proven clinical content with relevant, localized data like antibiotic resistance patterns and hospital guidelines. “A key strategy today is using trusted information to ground how an AI system works and presents insights,” Dr. Flannery said.
This philosophy is exemplified in UpToDate Expert AI, a new offering designed to deliver precise, clinically validated answers — from simple queries to complex diagnostic questions — directly within the care workflow. The tool leverages the same trusted content that has guided physicians for decades, now enhanced by generative capabilities that speed access to insights while maintaining strict guardrails.
Built with clinicians and for clinicians, the solution provides nudges that guide reasoning without taking over decision-making. Dr. Flannery offered an example: in a differential diagnosis scenario, it can surface likely considerations and pathways while prompting the clinician to apply their own expertise and judgment.
Even as the technology advances, Dr. Flannery is clear that AI is meant to augment, not replace, clinicians. “It doesn’t replace them, their clinical reasoning or judgment in the case,” he said.
Continuous validation in a rapidly evolving field
Healthcare evolves quickly — and so must AI. Dr. Flannery underscored validation as a critical, ongoing effort, and something that Wolters Kluwer continues to invest in and refine.
“Being able to leverage feedback, use it and drive continuous improvement is essential, not only as we’re developing and designing that solution, but after it’s out there because things change in an environment and you want to make sure you can adjust to that,” he said.
The company’s approach combines automated testing, clinician review and user feedback to ensure AI outputs remain accurate and clinically sound, as well as aligned with current standards of care. For generative AI, which can be harder to measure than rule-based systems, this continuous loop of validation and learning is especially important.
Preparing healthcare leaders for the next chapter
Looking ahead, Dr. Flannery believes the next 12 months will be pivotal for AI adoption in healthcare — not just in technology development but in cultural readiness.
“The key question for leaders now is: how do we prepare hospitals and clinicians for adoption?” he said. “Education is essential to help people understand what AI really is, what it’s not and how it’s meant to support them.”
He also emphasized the importance of involving clinicians early in the adoption process to build ownership and trust. That engagement often serves as organic education — a valuable opportunity for time- and resource-strapped systems and clinicians. As leaders include clinicians in the process of applying AI, they naturally learn what it can and can’t do, which can be even more effective than a standalone training program.
For Dr. Flannery, the future and value of AI in healthcare lies in empowering human expertise. When technology is rooted in evidence, continuously validated and designed around the clinician’s workflow, it becomes not just a tool but a catalyst for lasting transformation.
“The goal is to mitigate the burden on them so they can drive better patient outcomes at the end of the day,” he said. “The message is not to replace them, but to support them.”
Explore how UpToDate Expert AI is redefining evidence-based decision support for clinical workflows.
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