Artificial intelligence in healthcare has moved past notetaking and insurance chatbots into tools that could reshape how providers diagnose and treat patients, according to Muna Tuna, a partner at Ernst and Young and EY US Market Access leader. The shift matters because healthcare AI investment exceeded $250 billion globally by 2024, and Wall Street expects returns that efficiency tools alone cannot deliver.
"Adoption of AI is getting faster and faster. We can really drive high value through the end-to-end processes in the healthcare continuum," Tuna said, citing a wave of healthcare-centric AI tools released in early 2026.
From efficiency to clinical reasoning
Earlier AI tools such as notetakers and chatbots improved workflow but did not alter how patients interact with the healthcare system or how payors and providers deliver care. "That doesn't deliver on Wall Street's expectations," Tuna said.
Newer offerings target clinical work directly. These include tools for generating diagnostic hypotheses and integrating clinical practice guidelines into AI-powered, evidence-based decision support. Unlike static systems built on fixed queries, these models support active reasoning and incorporate new input continuously.
Providers are also using AI to text patients and optimize treatment approaches, Tuna said, such as spotting subtle signs of disease progression and evaluating therapeutic options for individual patients. "AI is becoming a very important component of this," she said, while cautioning that "there will always be a human in the loop in healthcare." AI should not replace pharmacists or providers, she said, but it can help personalize care beyond what was previously possible.
What changes for manufacturers
Pharmaceutical manufacturers face a different kind of shift. They must articulate product value to clinical and economic decision-makers, operational leaders, and healthcare professionals - audiences with divergent priorities. "In pharma, there is a saying: 'You see a health system, you've seen one health system.' The things they respond to, the value propositions that resonate for them are all very different," Tuna said.
AI tools can surface these varied points of resonance, allowing manufacturers to tailor their marketing accordingly. For teams working in this space, resources on AI for Healthcare provide context on how these capabilities are developing across the industry. Sales and market access professionals may also find value in the AI for Pharmaceutical Sales Representatives learning path, which addresses the practical skills needed as manufacturers adopt these tools.
Why this matters for healthcare professionals
The tools arriving in 2026 are not efficiency add-ons. They are designed to participate in clinical reasoning and treatment decisions, which means healthcare professionals will need to evaluate AI outputs critically rather than simply adopt them. Understanding what these systems can and cannot do - and where human judgment remains essential - is becoming a core job skill, not an optional one.
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