U.S. Digital Health Market Projected to Hit $713 B by 2035 as AI Fuels Rapid Expansion

Why It Matters

The projected $713 billion market size signals a seismic shift in how care is delivered, financed and experienced in the United States. For investors, the forecast validates continued capital allocation to AI‑driven health‑tech startups, telehealth platforms and wearable manufacturers. For policymakers, the data underscores the urgency of establishing interoperable standards that can unlock AI’s full potential while safeguarding patient privacy. For clinicians and patients, the trend promises faster, more personalized care, but only if the underlying data can flow freely across systems. If the data silos persist, the industry could face a paradox: massive spending on AI tools that cannot access the data they need to generate value. Resolving this tension will be critical to realizing the cost‑containment and outcome‑improvement promises that have driven the forecast’s optimism.

Key Takeaways

• U.S. digital health market valued at $117.15 billion in 2025, projected to reach $713.36 billion by 2035.
• Forecasted CAGR of 19.8% from 2026‑2035, driven by AI, telehealth, wearables and digital therapeutics.
• AI is transitioning from pilot projects to core infrastructure, automating documentation and decision‑making.
• Fragmented EHR silos create a data liquidity crisis, limiting AI effectiveness and continuity of care.
• Interoperability standards are identified as the key lever to unlock the market’s full potential.

Pulse Analysis

The Nova One Advisor forecast is more than a headline number; it maps a structural transformation of the U.S. health system. Historically, health‑tech adoption has been incremental, constrained by legacy IT and reimbursement models. The current 19.8% CAGR reflects a confluence of three forces: (1) AI’s maturation into a production‑grade layer, (2) the pandemic‑accelerated acceptance of telehealth, and (3) the proliferation of consumer wearables that generate continuous health data. Together, they create a feedback loop where richer data fuels better AI, which in turn drives deeper data capture.

However, the forecast also surfaces a classic network‑effect dilemma. The value of AI tools scales with the breadth and depth of data they can ingest. Proprietary EHRs act as gatekeepers, fragmenting the network and diluting the AI’s learning pool. Companies that invest early in open‑API ecosystems—such as those leveraging FHIR standards or blockchain‑based consent frameworks—will likely become the de‑facto platforms that aggregate the data needed for next‑generation AI. This could reshape competitive dynamics, pushing traditional EHR giants into a partnership or acquisition mode.

From an investment perspective, the market’s size alone does not guarantee returns. Capital will gravitate toward firms that solve the interoperability puzzle, either through technology (e.g., data‑exchange layers) or through policy advocacy that accelerates standard adoption. In the next 12‑18 months, we can expect a wave of M&A activity targeting data‑integration capabilities, as larger health‑tech conglomerates seek to cement their positions in the emerging AI‑first care model. The forecast’s optimism hinges on that very integration; without it, the projected $713 billion could remain a theoretical ceiling rather than an attainable reality.