Industry Corner: Scaling digital health: From telemedicine to AI-driven care

Writer: Mirella Franzese

Industry corner is a monthly series on what company leaders believe are the most important best practices in their sector or organization to ensure growth and sustainable success.

November 2025 —  America’s healthcare systems are overburdened. Professional shortages, rising costs, federal funding cuts, the rise of chronic diseases, and an aging population have all strained the industry. As a result, hospitals and health providers are shifting towards digitalized and AI-powered care models to alleviate the burden as automation offers core advantages in treatment efficiency and effectiveness.

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“The global health landscape is on the cusp of a significant transformation, driven by the rapid integration of digital technologies and artificial intelligence (AI),” said Andy Moose, head of health and wellness at the World Economic Forum, in a white paper examining the future of AI-enabled health. “In healthcare, medtech, and pharma, an inflection point has been reached: the choice now lies between transforming systems or continuing down the road of incremental improvement. As this transformation unfolds, it is crucial for addressing the urgency for real, impactful change rather than small, marginal advances.”

According to IBM, AI-driven diagnostics can improve health outcomes by 40% and reduce treatment costs by up to 50%. Similarly, the World Health Organization (WHO) estimates that spending an additional $0.24 per patient per year on digital health interventions could save more than two million lives from non-communicable diseases over the next decade.

The Next Phase of Digital Health

The pandemic accelerated the adoption of telemedicine, but healthcare’s digital phase has now evolved beyond virtual care, which has struggled to scale. This evolution marks an industry-wide shift from basic telehealth toward integrated digital ecosystems linking electronic health records (EHRs), mobile apps, AI algorithms, and workflow automation. In fact, the majority of healthcare leaders (96%) say they are “ready and resourced” to use digital health, according to a newly-released survey report by the MIT Technology Review.

However, most organizations are integrating these tools for operational and administrative efficiency, but grappling with clinical adoption due to regulatory and ethical uncertainties.

“Compared to other industries, healthcare exhibits digital maturity and disruption below the global average, indicating that these sectors have yet to make full use of digital technologies to create significant value,” Moose added. “It is not yet clear whether AI will drive transformation or continue down the current path, with a sole focus on marginal efficiency. So far, many AI developments have been experimental…most of which have yet to be implemented at scale.”

Despite challenges, clinical implementation is slowly gaining momentum. In fact, AI has already been successfully applied to multiple practices within the medical field. For instance, AI agents and assistants are supporting patient triage through advanced monitoring devices. Ambient voice technology is also being leveraged to document physician and patient conversations, allowing clinicians to focus more on patient interaction, according to AdventHealth’s West Florida Division President and CEO David Ottati, who recently spoke with Invest:. In another example, AI also provides capabilities that are considered “rare” for emergency medicine, according to James Fishkin, medical director of Sollis Health, a concierge urgent care provider. As Fishkin noted to Invest:, artificial intelligence enables them to perform advanced procedures that are typically only hospital-based, such as paracentesis and thoracentesis.

The benefits of AI adoption are clear. With the implementation of digital solutions, health systems can scale infrastructure at length and improve patient and data security. Even as labor shortages and rising costs continue to pressure hospitals, digital tools offer both operational relief and measurable improvements in clinical care — ones that are bridging social divides and health gaps.

Smarter Diagnostics and Filling in Care Gaps

According to healthcare experts, AI and medical imaging are being increasingly employed in radiology, dermatology, ophthalmology, pathology, and clinical triage, among other areas, for smarter diagnostics. These tools essentially help physicians interpret scans, identify anomalies, and predict disease progression faster and more accurately, as Ottati notes. Even more importantly, AI-enabled diagnostics expands access to healthcare, making detection easier for remote or underserved patients who are unable to visit physicians in person. 

For instance, Triangulate Labs, a Boca Raton-based technology company, is leveraging AI-powered total body photography (TBP) through its mobile app, Skinmap, to detect skin cancer early when it’s 99% curable, according to CEO and Founder Bill Hall. The Skinmap app captures 300 high-quality images in 60 seconds, while AI maps them onto a 3D body model, comparing prior and current scans to highlight changes. For Hall, this technology isn’t just critical for supporting dermatologists’ accuracy, but also for filling in gaps in access. 

“Of the 110 million high-risk Americans, only 12 million see a dermatologist annually, leaving nearly 100 million without access. Skinmap aims to bridge this gap by extending dermatologists’ reach to primary care providers, specialists, and remote patients, helping filter high-risk cases for early intervention,” Hall told Invest: reporters. 

Beyond dermatology, digital health is being used to help address critical gaps in women’s health, according to a 2025 Boston Consulting Group (BCG) report. In general, women live 25% more of their lives in poor health compared to men, but traditional medical ‘hardware’ fails to consider sex-based differences in treatment. Femtech innovations are therefore expected to transform mechanisms of health, tailoring care towards the female experience, as per BCG. 

For health systems, closing these divides means cutting down costs and operational burdens. AI tools like Skinmap essentially replace existing detection solutions (such as booths) that are economically impractical, and substitute mobile apps, which disrupt clinic workflows. 

So by leveraging these devices at scale, hospitals stand to gain more precise diagnostics and reduced clinician burnout — all of which enhance patient outcomes, mitigate revenue loss, and bolster operational resilience.

Addressing Risks: Ethics, Privacy & Regulation

For most healthcare providers, implementation isn’t the biggest roadblock for broader AI use — it’s regulation and ethics. With greater use of AI and automation comes heightened attention to ethics, data governance, and compliance, as Ben Horner,  managing director and partner at Boston Consulting Group, noted in a WEF report. 

“AI in health faces dual challenges. First, the inherently sensitive nature of health, where the protection of individuals is paramount, leads to a highly risk-averse environment. Second, societal skepticism towards AI, as highlighted by consumer sentiment surveys, presents a hurdle,” said Horner. 

Regulation is critical for security and trust. An American Medical Association (AMA) survey of nearly 1,200 doctors from 2023 to 2024 found that 47% of physicians consider increased oversight as the number one regulatory action needed to increase their confidence in AI tools. They also rated increased feedback, data privacy assurances, seamless workflow integration, and adequate training and education as essentials to scale AI implementation.   

“There remain unresolved physician concerns with the design of health AI and the potential of flawed AI-enabled tools to put privacy at risk, integrate poorly with EHR systems, offer incorrect conclusions or recommendations, and introduce new liability concerns,” explained AMA’s immediate past president Jesse M. Ehrenfeld, MD, MPH, in a report. 

However, healthcare organizations are responding by building in-house AI governance frameworks and transparency protocols to align innovation with both patient and physician trust.  One example is the Healthcare New Jersey Innovation Institute, which is developing its own internal AI governance and compliance tools. 

“We created a governance toolkit that consolidates guidance from providers and associations to help organizations safely deploy AI solutions,” said Jennifer D’Angelo, COO and EVP of Healthcare New Jersey Innovation Institute, in an interview with Invest:. “Internally, we’ve (also) developed a proprietary tool similar to ChatGPT, tailored specifically for NJII. This allows us to manage its learning process in a controlled environment, ensuring data privacy and compliance.”

Future Outlook: Intelligent Care Ecosystems

With greater regulatory frameworks and ethical protections in place, the hospital of the future will not just be connected, but also intelligent. Institutions that balance innovation with ethics and governance will define the next generation of patient-centric care. However, scaling digital transformation in the healthcare sector will require significant training and preparation, according to D’Angelo. 

“As healthcare shifts from manual to digital processes, these programs are crucial. The more we integrate technical solutions, the more we need to invest in training. That includes AI literacy, compliance, security, and privacy. Especially in healthcare, we must be vigilant, maintaining HIPAA (Health Insurance Portability and Accountability Act) compliance and minimizing risk. To do that effectively, we need to ensure our workforce is well-trained,” D’Agenlo told Invest:.

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