A new artificial intelligence strategy unveiled by the healthcare data platform company Clearsense is aiming to help hospitals unlock the value of vast amounts of historical patient data while reducing the growing financial burden of legacy IT systems.
Announced at the global HIMSS 2026 healthcare technology conference, the strategy focuses on embedding AI throughout the lifecycle of healthcare data archiving and application retirement, turning previously unused data archives into sources of operational and clinical intelligence. The initiative reflects a broader shift within healthcare technology as providers seek to move beyond isolated AI pilots and build scalable data infrastructures capable of supporting advanced analytics, research and population health management.
Tackling the burden of legacy healthcare IT
Healthcare organisations globally are struggling with ageing technology systems that consume large portions of their IT budgets. Analysts estimate that as much as 70 per cent of health system IT spending can be devoted to maintaining legacy software and infrastructure, leaving limited resources for innovation. Clearsense’s strategy focuses on “application rationalisation”which is the process of retiring outdated software systems while preserving the patient and operational data stored within them. By using AI to accelerate this process, the company aims to help hospitals reduce operating costs and modernise their data environments simultaneously.
The company’s platform, known as 1Clearsense, acts as a healthcare data lakehouse that aggregates data from multiple clinical and administrative systems. This enables hospitals to maintain access to historical patient records even after legacy applications are decommissioned. The new AI strategy expands this approach by automating large parts of the archiving and data integration process. AI models can identify redundant applications, organise historical datasets and create structured data layers that can be used for analytics and research.
Turning archived data into intelligence
A key component of the new strategy is the transformation of historical healthcare data from passive archives into active intelligence systems.
Traditionally, when hospitals replace older IT systems such as electronic health records or laboratory software, the data stored in those platforms is archived and rarely accessed again. This often creates what industry experts describe as “data graveyards”which are large collections of valuable clinical information that remain technically preserved but practically unusable.
Clearsense’s AI-driven approach seeks to solve this problem by analysing archived datasets and making them accessible for clinical research, operational planning and population health analytics. By unlocking these data resources, hospitals could potentially identify new clinical insights, track long-term patient outcomes and improve disease surveillance.
Evidence of financial impact
The strategy builds on earlier projects in which Clearsense helped healthcare providers streamline their IT infrastructure. One major health system partnership demonstrated the potential financial benefits of large-scale application rationalisation. Through the retirement of hundreds of redundant software applications, the organisation achieved tens of millions of dollars in annual operating cost savings while maintaining secure access to patient data.
In another case study involving Trinity Health, the approach is expected to deliver more than $100 million in cumulative operating expense reductions, highlighting the potential financial impact of large-scale digital transformation initiatives. Such results are drawing increasing attention from healthcare leaders facing financial pressures related to workforce shortages, rising technology costs and growing patient demand.
Relevance for the NHS and UK healthcare
Although Clearsense’s early deployments have been concentrated in the United States, the challenges it addresses are highly relevant to the UK healthcare system. The NHS operates one of the largest and most complex healthcare IT infrastructures in the world, with many hospitals still relying on a mixture of modern electronic patient record systems and older legacy platforms. These systems can create difficulties when organisations attempt to integrate patient records across multiple providers or implement advanced data analytics.
NHS England’s digital transformation strategy emphasises the need to modernise health data infrastructure, improve interoperability and enable the use of artificial intelligence in clinical decision-making. Technologies similar to those being developed by Clearsense could help NHS organisations consolidate historical patient records while reducing the cost of maintaining outdated software systems. In particular, unlocking archived data could support population health management, clinical research and AI-driven diagnostics, areas that are increasingly central to the NHS’s long-term digital health strategy.
A broader shift in healthcare AI
The Clearsense announcement also reflects a broader evolution in healthcare AI. At conferences such as HIMSS 2026, many vendors are moving beyond generative AI tools and toward systems capable of automating complex operational workflows and data management tasks. For healthcare providers, the challenge is no longer simply adopting AI but ensuring they have the data infrastructure needed to use it effectively. As health systems accumulate ever-larger volumes of clinical data, the ability to organise, govern and analyse these datasets will become increasingly important. Clearsense’s AI strategy therefore highlights a growing recognition across the healthcare technology sector: before AI can transform patient care, hospitals must first unlock the value of the data they already possess.
