AI-driven tools are enabling HTM leaders to move beyond static capital planning by using real-time asset data, predictive insights, and scenario modeling to guide purchasing and inventory decisions.
By Murphy McGraw, senior director, product management at TRIMEDX
As health systems navigate rising financial pressure and the underutilization of clinical assets, artificial intelligence (AI) is reshaping how capital decisions are made. Advances in agentic AI now make it possible to combine conversational scenario modeling with comprehensive clinical asset insights, helping organizations optimize capital planning and inventory levels.Â
Health systems should take advantage of these emerging technologies to enable smarter planning, reduced inventory spending, and demonstrable cost savings.  Â
Static Capital Planning No Longer Works
TRIMEDX has found that most medical equipment is only used 40-50% of the time. Health systems continue to over-purchase or rent assets, replace them too early, and carry underutilized inventory due to poor inventory visibility and incomplete data. Clinical assets often consume nearly a quarter of capital budgets, meaning the cost of inefficient capital planning can add up quickly.Â
Traditional capital planning approaches can often compound the problem because they rely on static processes built without accurate and complete data. Some health systems use spreadsheets and manual analysis paired with financial modeling tools—but they lack deep, device-level intelligence, real-time utilization data, and crucial clinical asset context.
In addition, healthcare environments change quickly, while traditional planning models take months, leaving even the best data outdated by the time decisions are made. This makes it difficult for leaders to confidently approve purchases, adapt plans as realities shift, or recognize when capital investments can be deferred or avoided altogether.
AI Presents a New Model for Capital Decision-Making
Agentic AI represents a meaningful departure from traditional capital planning approaches and opens a wide range of opportunities for health systems to dynamically optimize capital plans and right-size their inventories with greater precision. By combining conversational interfaces, scenario-based modeling, and deep asset-level intelligence, this technology enables leaders to directly engage with their data in real time. They can ask complex questions, explore alternatives, and move beyond the limitations of manual analysis and delayed reports.
Rather than evaluating capital decisions through a narrow lens, health systems can use AI to analyze multiple variables simultaneously, including utilization thresholds, asset age, remaining useful life, service history, cybersecurity risk, and parts availability. With this integrated view, decision-makers can generate capital planning scenarios, identify trends, compare options, validate decisions, and understand downstream implications before making investments.  Â
As a result, capital decisions are no longer driven by averages, assumptions, or incomplete snapshots of performance. Leaders can be confident their decisions are grounded in real-world asset performance and data—which supports more disciplined planning, stronger alignment with clinical need, and better use of resources.
Predictive Failure Intelligence and Supply Chain Automation Enable Smarter Decision-Making
Organizations can also make more informed operational and capital planning decisions by using AI to unify predictive failure forecasting and supply chain automation. AI-powered predictive work systems can identify degradation patterns and forecast the component or part likely to fail. When paired with multivendor intelligent parts-sourcing, AI can select the optimal supplier and secure the fastest procurement path before a device goes offline.
Traditional predictive maintenance tools are designed to flag potential equipment failures, but their value often stops there. Alerts are frequently disconnected from service workflows, supply constraints, and capital decision-making—leaving teams to step in and react only after a problem is identified.
What’s missing is the ability to move from insight to coordinated action. An AI-enabled approach closes the gap by connecting early signs of risk with broader operational, supply, and financial context. Instead of treating maintenance alerts as isolated events, AI can help health systems understand how equipment condition intersects with utilization, parts availability, and cost. Maintenance intelligence becomes a strategic input into planning and investment, not just a warning system.
A Comprehensive Dataset Is Critical
While AI is a transformative tool for healthcare technology management (HTM), it is only as good as its data. Health systems should work with a partner whose technology leverages an extensive medical device dataset and advanced analytics to benchmark performance, model scenarios, and generate accurate, asset-level recommendations. This depth of data will help leaders identify equipment that could be more useful at another facility, avoid replacing devices too early, remove or dispose of underperforming devices, and align inventory with demand.
This approach transforms capital planning from a reactive, point-in-time exercise to a proactive, continuously informed process. As clinical demand fluctuates and financial pressures intensify, capital decisions must evolve too. Agentic AI enables this flexibility by grounding capital strategy in real-world utilization and performance data—helping health systems direct resources where they create the greatest value without sacrificing safety, reliability, or the quality of patient care.
By using data-driven models informed by large-scale industry datasets, leaders can leverage AI to rapidly compare options, validate decisions, and establish plans. The result is a shift from static, manual planning to continuously informed, outcome-focused decisions that reduce waste, improve utilization, and ensure every capital dollar aligns with real clinical demand.
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About the author: With nearly 15 years of product management experience, Murphy McGraw is senior director of product management at TRIMEDX. In this role, Murphy oversees the strategic vision, long-term roadmap, and development plan for the TRIMEDX clinical asset management and clinical engineering products. Murphy has a bachelor of science in informatics from Indiana University and a Level 7 Pragmatic Marketing certification.
