ViVE 2025 brought together healthcare technology leaders from across North America in Nashville for three days of conversation about where the industry is headed. The weather was rough — it kept some attendees away — but the discussions that did happen were substantive and revealing.
For Penguin, ViVE is valuable not just as a conference but as a real-time reading of where hospital decision-makers are in their thinking. What are they actually worried about? What problems are they trying to solve right now? What technology are they ready to buy and what are they still skeptical about?
Here is what stood out.
The RTLS Conversation Has Matured
Real-Time Location Systems are no longer a new concept in healthcare. Most mid-sized and large hospital systems have at least evaluated RTLS — and a growing number have deployed it in some form. What has changed is the depth of the conversation.
Three years ago the typical ViVE conversation about RTLS in healthcare started with the basics — what is it, how does it work, what does it cost. At ViVE 2025, those conversations were largely gone. The people we spoke with already understood the technology. They were asking second-generation questions: how do we get more value out of what we have already deployed? How do we move from location data to operational decisions? How do we connect RTLS to the systems our clinical teams actually use?
This is a meaningful shift. It means the market for basic asset tracking is maturing and the opportunity for more sophisticated applications — workflow optimization, staff safety analytics, predictive maintenance — is opening up. Hospitals that deployed RTLS for equipment tracking are now asking what else that infrastructure can do.
From Tracking to Intelligence
The phrase that came up repeatedly in conversations was “location intelligence” — the idea that knowing where something is matters less than understanding what that location data means for operations. A hospital that tracks IV pumps knows where its equipment is. A hospital that analyzes IV pump movement patterns knows which units are hoarding, which are understaffed, and where the next shortage will happen before it does.
That is the direction the market is moving. PenTrack is built around exactly this model — not just real-time location, but operational intelligence derived from location patterns over time.
AI in Healthcare: The Shift from Hype to Practical Questions
Artificial intelligence was present at every conversation at ViVE 2025 — but the tone was different from previous years. The broad, futuristic narratives about AI transforming healthcare have given way to something more grounded: hospital leaders asking where AI is actually delivering value today, not in theory.
The question we heard most often was not “what can AI do?” It was “show me where it is working in a real hospital right now.”
Where AI Delivers Real Value in Hospitals
The applications generating genuine interest — as opposed to general curiosity — were narrow and specific. Predictive maintenance scheduling. Automated anomaly detection in equipment utilization. Pattern recognition in staff movement data that surfaces workload imbalances before they affect patient care.
These are not headline-grabbing AI applications. They are unglamorous, operationally specific uses of machine learning that save time and reduce errors in ways that clinical staff can actually feel. That is precisely what hospital buyers are responding to right now.
Penguin’s approach to AI sits in this space. Our location engine uses AI-enhanced positioning algorithms to deliver sub-room accuracy — not as a product feature but as the foundation that makes every downstream application more reliable.
Trust Is Still the Barrier
The consistent theme across AI conversations at ViVE was trust. Hospital leaders are not skeptical of AI in principle — they are skeptical of AI outputs they cannot explain to clinical staff or validate against their own operational experience. Systems that surface recommendations without showing their reasoning, or that require staff to act on alerts they do not understand, face significant adoption resistance regardless of their technical accuracy.
The AI tools that are gaining traction are the ones that augment human judgment rather than replace it — giving clinicians and administrators better information, not automated decisions they are expected to implement without question.
Workforce Support Is the Underrated Use Case
Healthcare staffing remains one of the most acute operational challenges in the industry. Every hospital system at ViVE was dealing with some version of it — burnout, turnover, recruitment costs, and the downstream effects on patient care quality and throughput.
What surprised us was how often RTLS came up in workforce conversations — not as a monitoring or surveillance tool, but as a support mechanism. The use case generating the most genuine interest was using location data to understand workload distribution: which nurses are covering the most ground, which units are consistently understaffed at specific times, which staff members are spending the most time on non-clinical tasks like equipment searches.
This framing — RTLS as a tool for supporting staff rather than monitoring them — matters enormously for adoption. Clinical staff are far more receptive to location technology when they understand it as something that reduces their burden rather than tracks their movements.
Workforce safety and PenSafe staff duress alerting fit directly into this framing. A nurse who can press a button and have security respond to their exact location in seconds is not being monitored — they are being protected. That distinction drives adoption in a way that surveillance framing never does.
Hospital Wayfinding: Still Underestimated, Still Important
One of the most grounded conversations at ViVE was about something deceptively simple: helping people find their way around hospitals.
Large hospital campuses are genuinely difficult to navigate. Patients miss appointments. Families get lost and arrive at clinical interactions already stressed. Staff spend meaningful time directing visitors instead of delivering care. The cumulative operational cost of poor wayfinding — in time, in patient satisfaction scores, in staff frustration — is significant and largely invisible because it never appears as a line item.
What is changing is that hospital leadership is starting to connect wayfinding directly to patient experience metrics that matter to their accreditation and reimbursement. A patient who arrives at their appointment on time and without stress is more likely to rate their overall experience positively — and that rating affects outcomes that hospitals are measured on.
PenNav addresses this directly. Turn-by-turn indoor navigation that works on a visitor’s existing mobile device — no app download, no new hardware — gives hospitals a patient experience improvement that is both affordable and immediately measurable.
For all the complexity in healthcare technology, sometimes the highest-value improvement is the one that helps someone find Room 412 without asking four different people. The ROI on wayfinding is underestimated precisely because the problem is so familiar that it feels unsolvable.
The Integration Problem Has Not Gone Away
If there was one consistent frustration across every technology conversation at ViVE 2025, it was integration. Hospital technology ecosystems are complex, fragmented, and expensive to connect. Every new system — no matter how valuable — adds to the integration burden on IT teams that are already stretched.
The hospitals generating the most interest in RTLS adoption were those looking for platforms that connect to existing infrastructure rather than require parallel deployments. The question was consistently: can this run on our existing Cisco Meraki network? Can it connect to our nurse call system? Does it integrate with our EMR?
Penguin’s platform is built around this reality. Our Cisco Meraki integration means hospitals that have already invested in Meraki networking can layer location intelligence on top of that investment without a separate infrastructure project. The sensor network is already there — Penguin turns it into a location intelligence platform.
This is not a minor technical point. For hospital IT teams evaluating RTLS, “runs on your existing network” is the difference between a six-month procurement process and a conversation that moves forward.
The Takeaway from ViVE 2025
The healthcare technology market in 2025 is past the early-adopter phase on most of the technologies that were experimental five years ago. RTLS is established. AI is moving from pilots to production. Digital wayfinding is becoming a patient experience expectation rather than a differentiator.
What that means for hospital buyers is that the evaluation criteria have shifted. The question is no longer whether a technology works. It is whether it works in your environment, connects to your existing systems, generates ROI you can demonstrate to your CFO, and does not add to your IT team’s burden.
Those are the conversations Penguin is built for. We work with hospitals that are serious about operational efficiency and patient safety — not hospitals buying technology to check a box. If you were at ViVE and want to continue the conversation, or if you are evaluating RTLS for your hospital, we would welcome the opportunity to show you how our platform works in a real hospital environment.
Penguin Location Services delivers AI-powered location intelligence through PenNav (indoor navigation), PenTrack (asset tracking and workflow), and PenSafe (staff safety and patient monitoring) on a single BLE 5.1 infrastructure. Learn more at penguinin.com/healthcare or request a demo at penguinin.com/contact.
Frequently Asked Questions
Q: What is ViVE and why does it matter for healthcare technology?
ViVE is one of the largest annual healthcare technology conferences in North America, bringing together hospital executives, technology vendors, and clinical leaders to discuss operational challenges and emerging solutions. It matters because the conversations at ViVE reflect where hospital decision-makers are in their actual buying and implementation cycles — not where vendors wish they were. Conference attendance and the depth of conversations around specific topics are reliable indicators of where the market is heading in the following 12 to 18 months.
Q: How is AI being used in hospitals right now?
The AI applications generating genuine adoption in hospitals in 2025 are narrow, operationally specific, and focused on augmenting human judgment rather than replacing it. Predictive maintenance scheduling for medical equipment, anomaly detection in asset utilization patterns, workload distribution analysis for nursing staff, and pattern recognition in patient flow data are the areas where hospitals are seeing measurable returns. Broad, generalized AI platforms that promise to transform entire workflows are generating skepticism — hospitals want to see demonstrated value in specific, bounded use cases before committing to wider deployment.
Q: What is the connection between RTLS and AI in healthcare?
RTLS generates the continuous, real-time location data that AI algorithms need to identify patterns and surface operational insights. Without accurate, reliable location data, AI models cannot accurately predict equipment shortages, identify workflow bottlenecks, or flag safety risks before they materialize. The quality of the location data directly determines the quality of the AI output — which is why the accuracy of the underlying RTLS infrastructure matters more than the sophistication of the AI layer built on top of it. Penguin’s BLE 5.1 platform is designed to deliver the sub-room accuracy that makes downstream AI applications reliable rather than approximate.
Q: Why is hospital wayfinding considered an RTLS use case?
Indoor navigation for patients and visitors requires knowing where the person currently is and mapping a route to their destination — both of which depend on indoor positioning technology. In a hospital environment where GPS does not function reliably indoors, BLE-based positioning provides the real-time location data that powers turn-by-turn navigation. The same sensor infrastructure deployed for asset tracking and staff safety can support patient and visitor wayfinding without additional hardware — which is one reason hospitals with existing RTLS deployments increasingly add indoor navigation as an incremental use case rather than a separate system.
Q: How does RTLS support healthcare workforce safety?
RTLS supports workforce safety through two primary mechanisms. First, staff duress alerting — wearable badges with panic buttons that, when pressed, immediately notify security with the staff member’s exact room-level location. This gives healthcare workers a reliable way to summon help in dangerous situations without escalating the situation through overhead announcements. Second, workload analytics — using location pattern data to identify which staff members and units are consistently overloaded, enabling proactive staffing decisions rather than reactive responses to burnout and turnover. Both applications run on the same BLE sensor infrastructure, making them cost-effective additions to an existing RTLS deployment.
