Ming-Chien Chyu, PhD, PE, Founding President, Healthcare Engineering Alliance Society (HEALS), and professor at Texas Tech University. gettyHealthcare systems around the world face a common challenge: the shortage of healthcare professionals to meet growing demand, especially in rural and underserved communities. In rural America, a simple doctor’s appointment can turn into an all-day ordeal. A patient driving two hours to see a primary care physician might learn they need a specialist exam requiring another three-month wait and a 150-mile trip to the nearest tertiary medical center.This isn’t an isolated scenario. More than 60 million Americans (about one in five residents) live in rural communities, and being underserved is a reality for many.​​​Artificial intelligence (AI) offers a promising solution by multiplying clinicians’ impact. AI can interpret medical images, predict clinical risks, automate documentation, support decision-making and reduce administrative burdens, among many other applications. Emerging agentic AI may further extend healthcare capacity by coordinating referrals, monitoring chronic conditions and helping patients navigate complex care systems.The most important question facing healthcare AI today may not be how intelligent these systems become but whether they can expand access to care. While advanced AI applications are increasingly deployed in major medical centers, millions of people in underserved communities still struggle to obtain timely, quality healthcare.The next chapter of healthcare AI should be defined not only by better algorithms but also by its ability to serve as a workforce multiplier in extending the reach of healthcare professionals to populations that healthcare has historically struggled to serve.The Geography Gap In Modern HealthcareDespite decades of technological breakthroughs, healthcare access in the United States remains starkly uneven.First, the medical provider shortage in rural America is severe. Rural areas average just 13 physicians per 10,000 residents, less than half the density of metropolitan centers. “Only 9.3% of physicians currently practice in small-town or rural settings,” leaving millions of residents with severely restricted access to care.Beyond general practitioner density, vast regions face absolute care deserts. Nearly half of all U.S. counties lack a single practicing cardiologist, forcing rural patients to travel an average of 87 miles round-trip for essential diagnostic care.Over 700 rural hospitals across the nation are also currently at risk of closing due to financial losses, forcing patients to travel further for emergency and specialty care. Compounding these shortages is an aging population, rising rates of chronic conditions like hypertension and diabetes and a burnout rate that continues to drive clinicians out of medicine.From Facility-Centered To Population-Centered CareWhile healthcare innovation has largely focused on improving care within hospitals and clinics, AI creates an opportunity to shift from a facility-centered model of care to a population-centered model that extends healthcare expertise beyond traditional settings to underserved communities.In practice, an AI-assisted diagnostic tool can let a rural nurse screen for specialized conditions locally. If flagged, AI-enhanced telemedicine can connect them with a specialist, eliminating travel.Meanwhile, generative AI can handle routine documentation and navigation, freeing clinicians to focus on patients. Between visits, remote monitoring is able to stream patient biomarkers to algorithms that spot early warning signs before a crisis occurs.Together, these technologies do not replace clinical judgment. They weave a safety net, shifting care from episodic encounters to continuous support and transforming overstretched local clinics into proactive care centers.​The Implementation Bottlenecks That ExistThe primary barrier to equitable healthcare AI isn’t algorithm performance; it is real-world implementation.Many rural communities still lack reliable broadband, while small hospitals often struggle to afford digital infrastructure, cybersecurity and workforce training. AI models trained primarily on data from large urban hospitals may also perform less well in rural or underserved populations, underscoring the need for diverse, representative datasets.Trust presents another challenge. Clinicians need AI systems that are accurate, transparent and clinically reliable. Patients need confidence that AI will strengthen rather than replace the human relationships that remain central to healthcare.In addition, policymakers must address critical issues involving privacy, cybersecurity, reimbursement, governance and accountability. Without thoughtful implementation, even the most promising technologies may struggle to achieve meaningful impact.​Building An Inclusive AI FutureTo turn AI from a luxury item for flagship medical centers into an access tool for underserved populations requires more than technological innovation.First, digital infrastructure must be treated as essential healthcare infrastructure. In an increasingly connected healthcare environment, broadband access and cloud capabilities are no longer a luxury. They are prerequisites for equitable care.Second, healthcare organizations should prioritize AI applications that address pressing operational and access challenges, including workforce shortages, chronic disease management, specialist access and administrative burden.Third, developers must design AI systems for the populations they intend to serve. Diverse datasets, transparent evaluation and continuous monitoring are essential to ensure that AI benefits all communities rather than reinforcing existing disparities.Finally, healthcare professionals and patients need AI literacy. The technologies most likely to succeed will be those that people understand, trust and can confidently incorporate into everyday healthcare decisions.From AI Innovation To Healthcare InclusionI believe the future of AI in healthcare will be defined by how far healthcare expertise can reach.​ By serving as a workforce multiplier rather than a human substitute, AI can help extend expertise, support overburdened clinicians and bring quality care within reach of communities that have long been underserved.​​Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?