Artificial intelligence (AI) has become one of the most debated technologies in healthcare. Concerns surrounding privacy, cybersecurity, accuracy, bias, transparency, and appropriate oversight are valid and require thoughtful safeguards. However, as healthcare systems face unprecedented challenges, it is equally important to recognize another risk: the risk of failing to responsibly embrace technology that can help transform healthcare delivery.
From Reactive to Proactive Care
The most important role of AI in healthcare is not replacing physicians, clinicians, or human expertise. Its greatest opportunity is to help healthcare professionals work better, not simply work more. By transforming increasingly complex information into meaningful insights, AI can help reduce administrative burden, support clinical decision-making, and allow providers to focus more time and attention on what they do best: caring for patients. More importantly, AI has the potential to help healthcare shift from a reactive model — where care begins after symptoms worsen or disease progresses — toward a proactive model that identifies meaningful changes earlier, supports prevention, and helps individuals maintain better health outcomes.
Rising Costs and Workforce Strain
This distinction is especially important as healthcare systems face growing challenges. Healthcare costs continue to rise, while providers are managing increasing patient demand, workforce shortages, and burnout. According to the Business Group on Health's 2026 Employer Health Care Strategy Survey, employers continue to anticipate significant increases in healthcare costs, creating challenges for organizations attempting to maintain affordable benefits while managing workforce health needs. CMS has also reported continued growth in Medicare spending, including increases in Medicare Part B premiums.
The solution cannot simply be asking healthcare professionals to do more with fewer resources. The future requires tools that enhance the ability of providers to deliver more personalized, efficient, and effective care while helping identify risk earlier and support proactive health management.
A Tool, Not a Replacement
The healthcare workforce is facing a convergence of challenges: an aging population requiring more care, increasing chronic disease burden, rising costs, and provider shortages. A healthcare system built primarily around responding after illness or disability occurs will become increasingly difficult to sustain. AI should not be viewed as a replacement for healthcare professionals, but as a tool that allows clinicians to leverage technology's ability to analyze information while preserving the judgment, experience, and human connection that define quality healthcare.
The future of healthcare requires a fundamental shift: moving from a reactive model, where care begins after disease or disability develops, toward a proactive model focused on maintaining health, identifying risk earlier, and improving quality of life.
The Evolution of Digital Health
Digital health has already demonstrated the potential of this transformation. Telehealth expanded rapidly during the COVID-19 pandemic by reducing barriers to care and allowing more healthcare services to be delivered remotely. However, digital health has evolved far beyond video visits. Today, it includes connected devices, wearable technology, biometric monitoring, artificial intelligence, and data-driven platforms that are changing how healthcare is delivered, managed, and paid for.
The next evolution of digital health is not simply collecting more information. It is understanding what that information means.
AI as an Intelligent Assistant
AI has the potential to interpret complex streams of healthcare data and identify patterns that may not be apparent through traditional assessments. The opportunity is not for AI to independently determine a diagnosis or replace clinical judgment. Rather, AI can serve as an intelligent assistant — helping healthcare professionals recognize meaningful changes earlier, understand individual health trajectories, and make more personalized decisions that move healthcare from reacting to problems toward preventing decline.
Movement as a Health Indicator
This opportunity is particularly important in areas such as musculoskeletal health. Musculoskeletal disorders are among the largest contributors to pain, disability, healthcare usage, and lost productivity in the United States, with annual costs estimated in the hundreds of billions of dollars. These conditions are frequently associated with additional health challenges, including obesity, diabetes, cardiovascular disease, arthritis, frailty, and falls.
Movement is one of the most important indicators of health, independence, and quality of life, yet it remains one of the least continuously measured aspects of healthcare.
Imagine a healthcare system where AI does not simply react when someone develops pain, disability, or functional decline, but helps interpret changes in physiological and movement patterns earlier.
For example, understanding movement requires far more than knowing whether someone is active. It requires understanding how the body functions. How does a muscle activate? Is there altered coordination? Is one muscle compensating for another? Is there reduced range of motion, weakness, spasm, or changes in movement quality?
This is where the combination of AI, biometric data, and wearable technology creates new possibilities.
The Foundation: Quality Data and Oversight
Artificial intelligence is a broad category of technologies designed to perform tasks that traditionally require human intelligence, including recognizing patterns, analyzing information, and generating insights. Machine learning (ML), a subset of AI, enables computer systems to learn from data rather than relying only on explicit programming.
However, the value of AI depends on the quality and relevance of the information used to train these systems. In healthcare, meaningful AI requires carefully selected data, appropriate clinical context, and responsible oversight.
One of the most important approaches within machine learning is supervised learning, where algorithms are trained using structured data to identify patterns and improve performance. In healthcare, this means understanding the biological and functional characteristics that truly matter.
A system designed to understand human movement must account for the complexity of the body itself — including muscle activation, biomechanics, coordination, and individual variability.
A Partnership Between Human and Artificial Intelligence
The future of AI in healthcare should not be defined by replacing human expertise. It should be defined by enhancing it.
For insurers, employers, healthcare systems, and patients, the opportunity is a transition from reactive healthcare risk management toward proactive health intelligence.
The question is no longer whether AI will influence healthcare. It already is.
The question is whether we will use it responsibly — with appropriate safeguards, clinical oversight, and a focus on improving outcomes.
The greatest opportunity may be creating a partnership between human intelligence and artificial intelligence: combining clinical experience, compassion, and judgment with technology's ability to analyze complex information at scale.
Healthcare does not need less human involvement. It needs better tools to help humans deliver better care.
