AI and digital health tools are advancing at breakneck speed, yet adoption and outcomes often lag behind investment. While hospitals and health systems race to deploy chatbots, predictive analytics and remote monitoring, many solutions remain incremental rather than transformative.
A comprehensive survey published in the Journal of the American Medical Informatics Association found that while health systems are piloting or deploying a wide range of AI use cases, success and implementation depth vary dramatically across clinical and operational domains, with many tools still immature or not integrated into care delivery workflows. The result: technology that generates data but fails to meaningfully change care delivery.
Members of the Senior Executive Healthcare Think Tank—a curated group of leaders spanning patient experience, workforce strategy, equity, quality, policy and health technology—see a different path forward. Drawing on deep expertise across AI, EHRs, diagnostics, telehealth and care-at-home models, they argue that the next wave of impact will come not from more dashboards, but from smarter, more adaptive and more human-centered systems. Below, they identify underrepresented areas of innovation that hold disproportionate promise for improving outcomes and reducing burden for clinicians.
Real-Time, Adaptive Therapies: Moving From Monitoring to Action
Andrew Baker-Campbell, Head of Health Tech at TTP plc, believes healthcare innovation has focused too heavily on observation rather than intervention.
“AI in healthcare is advancing fast, but most tools still monitor rather than improve care in real time,” Baker-Campbell says. “The biggest missed opportunity is technology that can act automatically on data.”
He points to closed-loop neuromodulation as a powerful but underutilized example. These systems continuously sense physiological signals, interpret them and adjust therapy instantly—reducing side effects while tailoring care to a patient’s needs throughout the day.
However, the barriers are substantial.
“Physiological data is messy, patient responses vary and regulators demand strong evidence before allowing autonomous decisions,” Baker-Campbell says.
Though the field remains early, the promise is clear.
“Real-time, adaptive interventions could become a major leap in patient care once the science and engineering mature,” Baker-Campbell says.
“Many platforms overlook the unique needs of diverse populations, which limits adoption and meaningful impact.”
Culturally Intelligent AI: Designing for Trust, Access and Equity
For Feri Naseh, Founder and CEO of MeTime Healing LLC, one of the most overlooked areas in digital health is cultural intelligence.
“While AI and digital health tools are proliferating, culturally sensitive, personalized virtual care remains underrepresented,” Naseh says. “Many platforms overlook the unique needs of diverse populations, which limits adoption and meaningful impact.”
At MeTime Healing, Naseh is addressing this gap through the Culturally Aware AI Roadmap for All (CARA), which uses AI to match users with culturally aligned care providers, personalize wellness plans and offer preventative mental health support.
“By integrating cultural awareness into digital health, we can improve engagement, outcomes and overall satisfaction for both patients and providers,” Naseh says. “This is a huge opportunity.”
“We’re now at the precipice of another significant shift via the emergence of virtual agents, which bring visual embodiment to voice technologies.”
Virtual Caregivers and the Engagement Crisis in Healthcare
Mark Francis, Chief Product Officer at Electronic Caregiver, Inc., sees patient engagement as one of healthcare’s most persistent—and solvable—problems.
“Around ten years ago, Amazon introduced Alexa, which served as a catalyst for voice-first interfaces,” Francis says. “We’re now at the precipice of another significant shift via the emergence of virtual agents, which bring visual embodiment to voice technologies.”
Electronic Caregiver’s AI-driven virtual caregiver, Addison, is designed to provide companionship, reminders and care support for patients receiving care at home.
“Such virtual caregivers represent a sea change in patient engagement and care plan adherence,” Francis says.
According to the U.S. surgeon general, loneliness carries health risks comparable to smoking 15 cigarettes per day. Yet many digital health tools struggle with sustained engagement.
“While smart meters and health apps have been used to reach patients, daily utilization remains under 30%,” Francis says. “By contrast, a pilot with rural patients in Alaska showed 97% daily utilization of Addison and 88% adherence to care plans.”
Such high engagement is critical to driving outcomes in healthcare, he adds.
“Today’s wearables generate vast amounts of data, but most are in proprietary formats designed for wellness rather than clinical decision-making.”
Wearable Data Standardization: Turning Signals Into Prevention
Harikrishnan Muthukrishnan, Principal IT Developer at BCBS FLORIDA, argues that wearables have outpaced the systems meant to use them.
“One critical gap is the standardization of wearable data for meaningful health monitoring and prevention,” Muthukrishnan says. “Today’s wearables generate vast amounts of data, but most are in proprietary formats designed for wellness rather than clinical decision-making.”
He points to fragmented standards, unclear accountability, integration challenges, equity and bias concerns and data overload as some of the major obstacles.
“The real barrier to using wearable data for prevention isn’t technology,” Muthukrishnan says. “It’s data standard, quality, trust, governance and how responsibly we integrate that data into real clinical workflows.”
Preventing emergencies is less a device problem and more a system problem, he warns.
Calls to Action for Healthcare Innovators
- Design technologies that act, not just observe. Real-time, adaptive systems can dramatically improve outcomes when built with rigorous evidence and safety in mind.
- Embed cultural intelligence into digital care. Platforms that reflect patients’ lived experiences will see higher trust, engagement and adherence.
- Solve engagement before scaling innovation. Virtual caregivers and embodied AI can drive daily interaction where apps and dashboards fail.
- Standardize wearable data for clinical use. Prevention requires interoperable, trusted data that fits naturally into provider workflows.
The Next Frontier of Healthcare Impact
The next wave of healthcare innovation will not be defined by novelty, but by relevance. As Think Tank members make clear, the most promising opportunities lie in adaptive therapies, culturally intelligent AI, deeply engaging virtual care and system-level integration of wearable data.
For providers and health system leaders, the challenge is to invest beyond hype and toward solutions that reflect how care is actually delivered and experienced. Those who do will not only see better outcomes, but build the trust and resilience healthcare needs for the decade ahead.
