By Mike Coen, Chief Product & Technology Officer, TeleTracking Technologies
LinkedIn: Michael Coen
LinkedIn: TeleTracking
Over the past decade, health systems have invested heavily in digital tools and analytics to enhance visibility and decision-making. Yet, for all the dashboards and real-time data, one fundamental hurdle remains: transforming insight into actions. That’s where artificial intelligence (AI) has the potential to completely revolutionize the industry, making healthcare operations an integral part of the care process.
AI’s promise isn’t limited to diagnostics or clinical decision support, it’s also about streamlining everyday operations, like task management, patient placement, and throughput. I envision a near future where AI doesn’t just provide suggestions but orchestrates hospital workflows with a level of precision that reduces waste, improves outcomes, and eases the burden on our already stretched workforce.
Automating the Invisible Burden
One of the most pressing operational inefficiencies lies in task management, especially for support staff in departments like environmental services (EVS) and patient transport. Today, these teams often rely on centralized dispatch systems. Assignments are given one at a time, and staff often return to a home location before receiving the next task. That kind of back-and-forth creates delays, underutilizes people, and ultimately slows down patient care.
AI should be able to assign the next best task based on real-time variables like location, urgency, and availability. There’s no reason someone should be walking across a hospital just to get their next assignment when we already have the data to keep them productive in the field.
If healthcare organizations use AI to dynamically allocate those tasks, they can dramatically increase efficiency. It’s not just about doing more, it’s about doing the right things, in the right order, with less friction.
Streamlining Patient Flow
Another major area where AI can have impact is patient placement. Right now, assigning a patient to a bed often involves a string of phone calls, manual reviews, and ultimately, the staff making a decision based on the information they have – be it sometimes incomplete or inaccurate. That process can and should be automated.
Imagine a referral comes in, and instead of someone manually coordinating it, an AI agent evaluates clinical criteria, facility capacity, and provider availability, and then assigns the best bed in real time. That whole workflow could be handled autonomously.
Beyond placement, AI can also support discharge optimization. It can help nurses and care teams focus on the next best patient to discharge based on organizational priorities. This kind of intelligent orchestration doesn’t just create space, it delivers value to the entire system.
The Agentic AI Frontier
The future potential of agentic AI is especially exciting. Imagine digital “clones” of care providers that take routine tasks off their plate. These agents could manage documentation, locate equipment, or even coordinate with transport, allowing clinicians to focus on what they do best – caring for patients.
Picture a nurse who doesn’t need to search for a piece of equipment or chase down paperwork. Instead, they ask their AI agent and it just gets done. That’s not science fiction. That’s within reach and being built today.
Agentic AI goes beyond static algorithms. It can make decisions, navigate dependencies across departments, and coordinate actions in real time. Whether it’s discharge planning, transport scheduling, or resource allocation, this technology is fundamentally reshaping hospital operations behind the scenes.
Adoption Barriers: Cultural and Technical
Of course, the road to adoption isn’t without challenges. However, from what the healthcare industry has seen, operational AI – the kind focused on logistics – is easier for teams to embrace than clinical AI, which is riskier. There’s just more comfort in letting AI suggest the next transport task than in letting it create, or even recommend, a treatment plan.
There are also valid concerns about data accuracy, security, and fears of job displacement. But AI should not be seen as a replacement – instead, it’s an enabler; a way to reduce repetitive manual tasks and elevate the human’s capacity to care. People are still in control of the decision-making. They just have the help they need to do it more efficiently. Think of it as just another tool, not the toolbox itself.
Looking Ahead
When people ask me what the single biggest bottleneck in hospital operations is, I always say: getting the right patient in the right bed at the right time. But we can’t solve that without understanding both ingress and egress, knowing who’s coming in the door and making a room available by moving the right patient out at the right time.
Ultimately, the problem isn’t that there isn’t enough data in healthcare – it’s that organizations aren’t turning that data into an actionable task fast enough. With AI, we have a way to move from reactive to proactive, from overwhelmed to optimized.
The technology is ready – and by embracing it, hospitals can unlock new levels of operational efficiency that benefit clinicians, patients, and the bottom line.