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Global Healthcare IT Investment and Trends in 2025

A recent report from KLAS Research analyzes key trends in global healthcare IT investment through 2025. The study, which interviewed 174 healthcare organizations in 39 countries and territories (excluding the United States), revealed a significant shift in investment priorities, with artificial intelligence and analytics taking center stage.
Global Healthcare IT Investment and Trends in 2025 1

1. Artificial Intelligence Becomes a Top Priority for Healthcare IT Investments

• The KLAS report identifies several key areas of healthcare IT investment:
Artificial Intelligence & Analytics: This area has emerged as a top priority, with 54% of respondents listing it as a key investment area. This surge is largely attributed to the rapid advancement of AI technology and its potential to drive clinical and administrative efficiencies. Electronic Health Records (EHR)/Digitalization: Digitalization of electronic health record (EHR) systems and broader healthcare processes remains a key focus, with 47% of organizations listing these areas as a priority. IT/Infrastructure: 30% of respondents prioritize investing in IT infrastructure, including cloud planning, system updates, and cybersecurity. Other Priorities: Other important investment areas include imaging (22%), cybersecurity (21%), interoperability (21%), and digital health (18%).

Interest in AI and analytics has increased dramatically over the past two years. In 2023, data analytics was the sixth-largest investment priority, rising to third in 2024 and now the top spot in 2025. This trend is driven by a growing awareness of AI’s potential to improve clinical and administrative workflows, with applications in areas such as documentation, radiology, and disease detection. Despite the strong interest in AI, many organizations are still in the early stages of adoption and are focused on testing solutions and establishing governance structures.

• AI and analytics adoption varies by region

Asia and Canada: These regions have the broadest focus on data analytics, with more than 70% of respondents listing it as a top investment priority. Europe and the Middle East: Organizations in these regions have a relatively narrow focus, concentrating on specific AI use cases that can improve efficiency. For example, the UK has shown strong interest in ambient voice technology, as well as other efficiency-enhancing tools in Europe. Latin America: The focus in this region is primarily on general AI strategies and business intelligence (BI) tools. Middle East and Africa: Although some organizations in Saudi Arabia and the UAE are exploring broader AI applications, BI analytics remain their primary focus.

Notably, ambient voice technology has become a highly anticipated innovation in the healthcare space. Its ability to reduce clinician documentation burdens and improve their satisfaction has made it a top investment priority for many institutions.

Global Healthcare IT Investment and Trends in 2025 2

2. Accelerating the application of cloud technology

Global cloud adoption continues to grow, driven by the need to support AI initiatives and modernize foundational systems. The focus is shifting from simply preparing for the cloud to actively adopting cloud solutions. While hybrid deployments are still prevalent, cloud technology is moving toward greater maturity. The most significant growth in cloud maturity is in Asia, Canada, and Europe, where organizations are migrating EHR and ERP systems to the cloud.

From the perspective of the market landscape, affected by factors such as data sovereignty regulations, different regions have different choices for cloud providers. For example, Microsoft Azure is the most popular or used cloud computing provider in most regions, with significant growth in Asia; Amazon AWS is gaining more and more attention, especially in Asia and Europe, where large projects are increasingly considering using the service; in addition, Google Cloud Platform (GCP) is also gaining more attention, especially in artificial intelligence, machine learning, and predictive analysis applications.

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