AI in care delivery, virtual care, and health equity

AI in Care Delivery, Virtual Care, and Health Equity in 2026

The integration of artificial intelligence (AI) into healthcare continues to accelerate in 2026, transforming how care is delivered, optimizing virtual health services, and addressing longstanding issues of health equity. This evolution is driven by sector-specific innovations, expanding infrastructure, and a growing emphasis on creating inclusive, trustworthy AI systems.

Deployment of AI and Digital Platforms Across Health Systems

Healthcare is at the forefront of AI-driven transformation. Major initiatives are enhancing interoperability, enabling seamless data exchange, and supporting personalized medicine:

• Interoperable Data Ecosystems:
  Efforts like Mount Sinai’s selection of Clear exemplify building interoperable identity platforms that unify patient data across institutions. Such systems facilitate real-time analytics, improve diagnostics, and streamline clinical workflows, leading to better patient outcomes.

• Scaling Digital Pathology and Diagnostics:
  Companies like Labcorp and PathAI have expanded their AI-enabled digital pathology platforms nationwide, increasing diagnostic accuracy and speed. These tools support early disease detection and precision medicine, vital for complex conditions such as cancer.

• AI-Enabled Preventive Care:
  Health providers are leveraging AI to shift toward proactive, personalized health management. For example, Hims & Hers is expanding AI-driven preventive services, including multi-cancer screening and menopause management, helping patients manage health risks before symptoms arise.

• Innovations in Clinical AI Tools:
  The advent of models like MediX-R1, an open-ended medical reinforcement learning system, demonstrates progress in long-term reasoning and adaptive clinical decision-making—paving the way for more reliable, context-aware AI in care.

Virtual Care and Digital Health Equity

Designing digital health solutions that are accessible and equitable remains a priority. Initiatives focus on embedding language diversity, cultural relevance, and inclusive design:

• Embedding Equity into Virtual Care:
  Articles such as "Designing Digital Health for Every Language" highlight efforts to embed health equity into virtual care platforms, ensuring that underserved populations receive appropriate and accessible services. Addressing digital health disparities involves understanding multi-level determinants and tailoring solutions accordingly.

• Ensuring Digital Health Equity:
  Research synthesizing digital health equity determinants emphasizes engaging diverse end users, reducing barriers, and creating inclusive platforms that serve all communities effectively.

Regulation and Trustworthiness of AI in Care

As AI becomes integral to high-stakes health environments, ensuring safety, transparency, and regulatory compliance is critical:

• Safety and Validation:
  Incidents like glitches during AI-assisted surgeries have underscored the need for rigorous validation protocols and standardized oversight. Continuous monitoring and validation are essential to prevent harm and maintain trust.

• Policy and Liability:
  Regulatory initiatives, such as California’s AI accountability efforts, aim to establish transparency standards and user rights, fostering public trust and responsible deployment.

• Cybersecurity in AI Systems:
  With the increasing sophistication of AI, cybersecurity remains vital. Companies like Cogent Security are developing autonomous threat detection tools to safeguard sensitive health data and AI systems against cyber threats.

Emerging Startups and Infrastructure Supporting AI in Healthcare

The growth of AI-native health startups and investments in hardware and infrastructure underpin these advancements:

• Innovative Startups:
  New entrants like SpendRule aim to address healthcare spending inefficiencies, while others focus on developing domain-specific AI tools for finance, insurance, and clinical decision support.

• Regional AI Ecosystems:
  Sovereign LLMs from startups like Sarvam AI emphasize regional control over data, addressing privacy concerns and fostering localized innovation. Strategic partnerships, such as Tata’s collaboration with OpenAI, position regions like India as emerging AI hubs.

• Hardware and Infrastructure Investments:
  Major chip manufacturers like Google and Meta are developing custom AI hardware, while data center expansions—such as Reliance Industries’ plans for high-capacity AI data centers—support large-scale AI deployment. These investments are crucial for enabling the computational power required for sophisticated healthcare AI applications.

Future Outlook

In 2026, AI is increasingly embedded in healthcare delivery, virtual care, and efforts to promote health equity. While technological progress is rapid, the journey toward safe, trustworthy, and inclusive AI requires ongoing collaboration among industry, policymakers, and civil society. As Sundar Pichai noted at the India AI Impact Summit, "Trustworthy AI—centered on explainability, ethical standards, and robust regulation—is essential for societal progress." Achieving this balance will determine whether AI fulfills its promise to improve lives, reduce disparities, and transform healthcare into a more equitable and effective system for all.