Study and market forecast point to expanding use of generative AI in healthcare

Generative AI could process enormous medical datasets far faster than traditional computer science teams, and the global generative AI in healthcare market reached US$ 2.92 billion in 2024 and is expected to reach US$ 30.68 billion by 2033, growing at a CAGR of 35.1% during the forecast period 2025-2033. Researchers tested whether generative AI could handle complex medical datasets as well as human experts, while market growth is driven by increasing adoption of advanced AI technologies to enhance clinical decision-making, drug discovery, medical imaging, and patient engagement.

In an early real world test of artificial intelligence in health research, scientists at UC San Francisco and Wayne State University discovered that generative AI could process enormous medical datasets far faster than traditional computer science teams and in some cases produce even stronger results. To compare performance directly, researchers assigned identical tasks to different groups. Some teams relied entirely on human expertise, while others used scientists working with AI tools. The challenge was to predict preterm birth using data from more than 1,000 pregnant women.

The system generated functioning computer code in minutes, something that would normally take experienced programmers several hours or even days. Only 4 of the 8 AI chatbots produced usable code. Because of this speed, the junior researchers were able to complete their experiments, verify their findings, and submit their results to a journal within a few months. The study was published in Cell Reports Medicine on Feb. 17.

Researchers compiled microbiome data from about 1,200 pregnant women whose outcomes were tracked across nine separate studies. More than 100 teams worldwide participated in a global crowdsourcing competition called DREAM, developing machine learning models designed to detect patterns linked to preterm birth. Most groups completed their work within the three month competition window, yet it took nearly two years to consolidate the findings and publish them.

The AI systems analyzed vaginal microbiome data to identify signs of preterm birth and examined blood or placental samples to estimate pregnancy stage. Generative AI enables the creation of synthetic medical data, personalized treatment plans, automated clinical documentation, and predictive analytics, improving efficiency and accuracy across healthcare systems.

Growth is also driven by rising investments from healthcare providers, pharmaceutical companies, and technology firms, along with advancements in machine learning, natural language processing and cloud-based healthcare platforms. The growing focus on precision medicine, operational efficiency, and cost reduction is further fueling global growth. Major global players in the market include IBM, Google LLC, Microsoft, OpenAI, NVIDIA Corporation, Oracle, Johnson & Johnson Services, Inc., NioyaTech, and Saxon.

The market is witnessing strong adoption of generative AI for automating clinical documentation and administrative tasks. Microsoft expanded its generative AI healthcare solutions through Nuance, introducing advanced clinical documentation and ambient AI tools. Google Cloud introduced generative AI tools for healthcare data analysis, medical imaging insights, and clinical workflow optimization. Tempus AI advanced research in generative AI for precision medicine, including genomic data analysis and personalized treatment recommendations.