There is not a provider in the U.S. –– from independent practitioners to large-scale hospital systems –– that isn’t thinking at some level about the future of AI in healthcare. Unfortunately, despite years of promise, we’ve only made the smallest of relative steps towards what AI could potentially do for both providers and patients. Cost, complex integration, and resistance from the healthcare workforce are some factors that have limited AI’s reach and slowed its adoption across the industry. But what if we’ve been thinking about AI all wrong?
In this phase of technology development and adoption, AI has primarily been a tool for automating note-taking and documentation. But this perspective only scratches the surface of its potential.
Generative AI, applied thoughtfully, can work hand in hand with scribing to enhance decision-making, personalize patient care, optimize treatment plans, serve as a reminder for providers, and help streamline complex administrative tasks. Looking toward 2025, the future of AI in healthcare must shift to a vision of seamless AI integration as the foundation of modern clinical practice. And it starts with the patient intake process.
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Optimizing the intake process
We are missing a vital opportunity to truly understand our patients before they enter the exam room. Every patient intake experience should be a gateway to deeper understanding and personalized care, yet too often, it’s the opposite.
For example, if a patient schedules an appointment for migraines, but is rushed when filling out intake forms at the office, the provider won’t be fully aware of how migraines impact the patient’s daily life – recent missed workdays, a family history of migraines, sensitivities to specific triggers, etc. The conversation in the exam room would start over with the basics, missing valuable context, leading to a frustrating experience and redundancy for everyone involved.
Imagine instead an intelligent intake voice. At the click of a button, the voice begins walking patients through the process of gathering and synthesizing patient history. Along the way, the AI flags potential symptoms, and asks specific questions based on the answers given. This data then seamlessly flows into an AI-powered scribing system, recording the consultation, adding real-time clinical context, and integrating the narrative into the EHR. The provider enters the room already informed, avoids redundant questions, and is able to focus on collaborative problem-solving with the patient. At the end of the visit, everything is in a single file, ready to streamline future care.
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Intake and scribing are two sides of the same coin: intake sets the stage by gathering patient insights, and scribing ensures that those insights — and the resulting clinical decisions — are captured and actionable throughout the care journey. Without this type of integration, AI risks remaining a collection of disconnected tools — efficient at automating individual tasks but failing to transform the patient experience.
We’re missing the actual value of AI if we only see it as a digital clipboard or a fancy voice-to-text tool. The future of AI relies on combining processes like patient intake and scribing, so that providers can shift from reactive to proactive care. Instead of chasing fragmented data, clinicians gain a cohesive view of the patient’s health, enabling better decision-making and stronger patient relationships. By rethinking AI in this integrated context, we can create a smarter, more human healthcare system.
The current impact (or lack thereof) of AI
In the last year, the healthcare industry has slowly started waking up to the multitude of AI options available. Scribing has been an easy entry point for many organizations, but we have struggled as an industry to fully integrate AI solutions into clinical workflows and electronic health records (EHRs). While AI-powered scribing offers an immediate solution to ease documentation burdens, it’s clear that it alone isn’t enough to meet the broader needs of providers.
As the market for AI tools continues to grow, there’s a noticeable shift in how healthcare leaders are approaching these technologies. There’s a renewed emphasis on ROI — executives are increasingly asking, “What are we really getting out of this?” This focus on financial outcomes has become a driving force behind adoption, as decision-makers seek to justify AI solutions to their teams.
To succeed with AI, health systems must prioritize solutions that are looking forward, developing AI processes around tasks like patient intake and scribing that can then be fully integrated into what providers are already doing. Ultimately, ecosystems, not point solutions, will be the answer to how AI can impact both patient outcomes and the bottom line.
The path forward
The momentum behind AI-driven healthcare solutions is undeniable, and 2025 may be the year we start seeing some constellational shifts. Patient intake and scribing integration is just the beginning. As I have pointed out, zeroing in on essential processes, but then thinking about the ways they can be integrated into the complete care plan without causing more work for doctors or administrators, is how we will put the pieces of practical AI together. Vendors are hearing the demand for this and responding with simpler, more accessible options that meet providers where they are.
Equally crucial will be developing easy integration. AI tools are only as effective as their ability to fit naturally into existing workflows. As a result, “plug-and-play” models are on the rise, designed to alleviate administrative strain and reduce friction for overstretched IT departments. With this shift, we might finally see healthcare systems become more adaptable, able to experiment, pivot, and learn faster from AI implementations without compromising patient data or clinical integrity.
Finally, proving ROI will remain essential. Many AI applications have yet to clearly demonstrate their value. However, solutions like AI-powered patient intake offer a tangible ROI by streamlining administrative tasks, reducing errors, and improving care quality. As these types of solutions become more integrated, they will demonstrate clear cost savings and better outcomes, making a strong case for wider AI adoption.
In a recent survey of health system executives, 88% said that AI would have a high potential impact, but only 20% plan to make investments in the next two years (McKinsey & Company). Data quality and trained talent – to implement and run systems – are the biggest hurdles to adoption. The question isn’t what AI is capable of, but how we can empower it to make healthcare more human, efficient, and effective for all, while providing an ROI that transcends all areas of the industry.
Photo by Flickr user agilemtkg1
As an internal medicine physician, Josh Reischer worked at Iora Health, seeing patients 65+ and enjoying it. He found himself working extra hours to complete a multitude of necessary paperwork. He saw an opportunity to increase office efficiency while improving the care he could deliver. A year earlier he befriended Aaron Rau at YC Startup School while they were working on separate projects. He expressed frustration to Aaron, a veteran entrepreneur and software developer, who reconfigured another platform he had built based on Josh’s suggestions. Within a week, Health Note was born. Thirty days later, they had their first paying customer.
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