Healthcare AI Spending Expected to Reach $37B Globally by 2026, Focusing on Admin Tasks

Investments in Healthcare AI are forecasted to reach $37 billion globally in 2026, with 85% of healthcare organizations planning to increase their AI budgets. Investments are primarily concentrated in clinical workflows, administrative tasks, and workflow optimization. However, these use cases don’t address the critical decision of choosing the right healthcare provider, a significant blind spot in the current AI landscape.

Provider-level quality measurement, which can significantly influence patient outcomes and costs, has considerably matured. The challenge is to effectively deploy this information at the point of patient decision-making, ensuring they choose the best provider for their specific needs.

Healthcare AI’s blind spot

The choice of provider sets the trajectory for a patient’s entire care experience, influencing approximately 80% of the healthcare dollar. Despite this, the crucial decision of provider selection remains largely untouched by the influx of AI in healthcare. According to the PwC’s 2025 US Healthcare Consumer Insights Survey, around 53% of consumers are already using or interested in AI-powered care navigation tools to recommend the best provider.

Variation at the provider level

Notably, there is significant variance in physician quality and adherence to evidence-based guidelines. For instance, two orthopedic surgeons may recommend entirely different courses of action for the same condition, impacting patient outcomes and costs. Embold Health’s measurement methodology found that surgical rates can differ by over 30 times between conservative and aggressive providers for the same condition.

AI at the point of decision

Quality measurement doesn’t influence outcomes unless it reaches the patient at the point of choosing a provider. AI can help bridge this gap by delivering clinically validated data through a personalized, conversational experience at the point of decision. McKinsey’s 2025 Consumer Health Insights Survey found that users of AI-enabled healthcare tools reported a satisfaction rate of 54%.

What the industry should demand

The AI used for provider selection should be built upon clinical evidence rather than traditional factors like proximity or reputation. The foundation should include clinically validated provider quality data and risk-adjusted evaluations for patient complexity. Ensuring the clinical validation of the AI tool is crucial to its success and could prove instrumental in improving patient outcomes and reducing costs.