This article, written by Meena Mallipeddi, first appeared in Forbes.
The headlines surrounding AI in healthcare are nothing short of miraculous. We are captivated by the “moonshots”—algorithms that can help detect stage-one lung cancer, AI that can predict cardiac arrest before it happens, and personalized genomic sequencing. These clinical breakthroughs are vital, but they can overshadow a more immediate and practical use of AI: helping hospitals operate more efficiently today.
Solutions that use AI to help care teams find the right information faster, coordinate with the right people sooner, reduce administrative burden and make better use of limited clinical capacity at the point of care are already moving the needle on both clinical efficiency and the bottom line.
For hospital leaders and healthcare innovators, here are five questions to ask when evaluating AI solutions designed to improve hospital operations.
1. Does it help staff find information faster?
Hospitals already collect enormous amounts of patient information. The challenge is making that information useful in the moment.
AI should help care teams quickly understand what matters most at the point of care. That could mean summarizing recent changes in a patient’s condition, surfacing abnormal trends, organizing relevant medications or test results or helping a clinician see what has happened since the last handoff.
Clinicians should not have to search through long records, disconnected notes and multiple systems to understand the patient in front of them. Practical AI can reduce that burden and help teams act with better information in real time.
2. Does it reduce paperwork?
Documentation is one of the clearest areas where AI can help. Care teams spend significant time writing notes, summarizing visits, preparing handoffs and completing required documentation.
AI can help draft notes, summarize encounters, prepare handoff summaries and organize documentation so clinicians are not starting from a blank screen.
The goal is to give clinicians a better starting point, so they can spend less time documenting and more time practicing medicine.
3. Does it improve billing accuracy?
Documentation also affects the business side of hospital care. Hospitals need to be paid accurately for the work they do, and that starts with a complete and accurate record.
AI can help identify missing information before a record is finalized, flag documentation gaps and support coding workflows closer to the point of care, rather than after the fact.
Physicians should not have to become billing experts. Practical AI should help make documentation more complete in real time without adding more administrative work later.
4. Does it show leaders where work is slowing down?
Hospitals are complex operations. Leaders often know delays are happening, but it can be difficult to see exactly where work is slowing down or why.
AI can help identify patterns across daily operations: which requests take too long, where handoffs break down, which services have the most variation and where delays affect patient flow.
Hospitals cannot improve what they cannot see. Practical AI should give leaders more real-time, specific information so they can address operational issues faster.
5. Does it expand access to needed services?
Many hospitals, especially community and regional hospitals, cannot employ every type of specialist locally. Even large health systems may have uneven specialist access across different locations.
AI can help make scarce expertise easier to deploy. It can route requests based on specialty, urgency, availability, workload, location and hospital rules. It can prioritize urgent needs, escalate requests when the first person is unavailable, prepare case summaries, organize relevant information before a specialist reviews a patient and support the documentation that follows.
When specialists and care teams can work more efficiently across locations, hospitals can extend services to more patients, reduce unnecessary delays and keep more care close to home.
The Risk Of Adopting AI Before The Hospital Is Ready
Many of us in health tech are working hard to build AI tools that help hospitals operate better. But technology alone is not enough. A promising AI tool can still fail if the hospital is not ready for it. Instead of saving time, it can leave clinicians second-guessing the output or doing extra work.
That does not mean hospitals should wait for perfect conditions. It means leaders should be honest about what needs to be in place before AI becomes part of the daily routine. The goal is to make sure these tools reduce friction for care teams instead of adding to it.
The Practical Test For AI
I am excited about what AI can bring to healthcare. It will likely help clinicians diagnose, treat, predict risk and personalize care in ways that can transform what is possible for patients.
But working with hospitals every day has shaped how I think about AI’s potential. When tools create a more efficient care environment—reducing manual work, making better use of limited resources and supporting better decisions at the point of care—hospitals can keep care moving and sustain the essential services patients depend on.
For hospital leaders and AI innovators alike, this is the practical test: Does this tool help care teams deliver care more effectively in real time?
If the answer is yes, it may be worth a closer look.
Meena Mallipeddi
Meena Mallipeddi is the Co-founder and CEO of AmplifyMD, where she champions the transformative potential of virtual care to improve access to specialty care and health outcomes, particularly in underserved communities. She was recently named one of Becker’s Healthcare’s Great Leaders in Healthcare and to Inc. Magazine’s Female Founders 500 list, and was recognized by The Healthcare Technology Report as a Top Healthcare Technology CEO.
