DESAI: We have many examples of time-consuming, “paraclinical” work that is required by providers and nurses. This includes things like complex scheduling, prior authorization/pre-certification, portal messaging, data review/synthesis, and beyond. It’s clear to me that if we can roll out meaningful AI/automation to aid with these tasks, it will reduce the burden of paraclinical work, allow providers to spend more direct time with patients, improve well-being and reduce burnout. The clearest signal of this has been ambient scribes that, in national studies, have significantly reduced burnout. I’ve worked as a professional informaticist for over 20 years, and this is the first time I’ve seen a single digital intervention have that kind of impact. As these tools get smarter and more integrated into clinical workflows, I’m optimistic we’ll see more successes like these. The operational benefits (revenue cycle as a key example) are also significant.
HILL: What excites me most is the increasing alignment between clinicians, health systems and developers around responsible, real-world AI adoption. We’re moving beyond pilots and hype toward the practical use of tools that improve quality, reduce burden on clinicians, and expand access to care — especially in under-resourced settings like community health centers. AI has a real potential to meaningfully support care teams, but only if it’s implemented with trust, transparency and clinical expertise. Seeing that consensus form across the CHAI community and broader healthcare ecosystem is incredibly exciting.
POON: We are excited about the power of AI to transform every aspect of clinical care and operations. We are currently exploring the use of AI-assisted computer vision to help us prevent falls and pressure injuries in the inpatient setting. Our nursing staff are excited to leverage this technology to reimagine the care model in the hospital environment. We are also actively piloting agentic AI technology that we have developed internally to reduce the burden of detailed chart review for patient referral, discharge summary preparation and clinical registry data abstraction. Early results have been very promising. In the administrative space, we have seen successes in the revenue cycle area, where AI has demonstrated significant benefits in streamlining the labor-intensive tasks of prior authorization, chart reviews for documentation improvement and coding.
ROEDER: I’m excited about the opportunities it brings to help innovate and push things forward. For underserved healthcare providers it brings the opportunity of hopefully being able to provide high-quality service with reduced overhead and expenses. This would allow these places to continue to keep their doors open for their communities.
EXPLORE: Revolutionize prior authorizations with AI.
HEALTHTECH: What about AI use in healthcare still concerns you?
ARCHULETA: What still concerns me is governance, not the technology itself, and how it’s implemented, monitored, secured and trusted. AI must never become a black box that people blindly follow. It needs transparency, validation and clinical oversight to prevent bias and ensure accuracy. I’m also deeply focused on cybersecurity, because AI increases complexity and expands the attack surface in an industry that is already a prime target. The right approach is simple: AI must be held to the same standard as medicine — safe, accountable and continuously monitored.
BARRERA: My primary concern is maintaining regulatory-compliant audit trails when AI makes decisions affecting patient care or data access. In this realm, we need to demonstrate not just what the AI decided, but why, and in ways that satisfy HIPAA, Criminal Justice Information Services and other relevant requirements. Each AI system integrated can present a new attack surface, and I’m concerned about adversarial attacks on healthcare. These attacks include prompt injection vulnerabilities in clinical chatbots, and the risk of AI systems being manipulated to make harmful decisions during the critical window when security frameworks for healthcare AI are still maturing.
DELOVSKA-TRAJKOVA: What concerns me is that there are many AI-powered platforms, apps and services potentially working against each other. This creates a risk that nobody has warned us about and we may not be able to effectively recognize or monitor. Think of deepfake fears, which in healthcare creates a much riskier dimension.
