“Healthcare systems are also adopting platforms such as Belong.Life, which uses specialized LLMs to streamline patient onboarding, deliver personalized education and support, and automate documentation”.
A radiologist receives a priority alert. An AI model has identified a subtle pulmonary embolism that would have otherwise gone undetected in the immediate review queue. In a neighboring department, a resident uses AI-guided ultrasound for real-time cardiac assessment at bedside. Meanwhile, intelligent automation handles patient intake, fielding inquiries and updating medical records seamlessly. Forty miles away, a mother monitors her high-risk pregnancy from the comfort of her living room using AI-powered tools guided by an OB-GYN at the hospital.
These are not a vision of the future but current examples of AI’s evolution from experimental technology to essential clinical infrastructure. And we are only at the beginning.
The AI Healthcare Landscape
Healthcare has experienced a significant surge in artificial intelligence adoption over the past five years, reshaping everything from diagnostic imaging and surgical precision to patient engagement and therapeutic discovery. AI now influences virtually every healthcare domain.
More than 4,500 AI-healthcare ventures currently operate across the United States, attracting $14 billion in investment during 2024 alone and accounting for 58 percent of total digital health funding. Academic research mirrors this momentum, with AI healthcare studies rising from 5,885 in 2020 to 28,180 in 2024.
AI’s transformative power is far from fully realized. As algorithmic sophistication improves and applications expand, we must shift from exploring what AI can do to maximizing its practical value. If the first chapter of AI in healthcare focused on invention, the next must focus on implementation.
Despite thousands of promising solutions and substantial investment, AI’s influence on daily clinical practice remains limited. Healthcare institutions are filled with pilot programs that rarely evolve into meaningful, sustainable change. Given constrained budgets and already stressed healthcare infrastructure, the promise of AI too often fails to become tangible progress.
From Development to Deployment
Realizing AI’s full potential requires healthcare leaders to rebalance priorities…
