Artificial Intelligence-Driven Hospital Energy Optimization Market Report 2025

The artificial intelligence-driven hospital energy optimization market size has grown exponentially in recent years. It will grow from $2.01 billion in 2024 to $2.49 billion in 2025 at a compound annual growth rate (CAGR) of 23.9%. The growth during the historical period can be attributed to rising energy consumption in healthcare facilities, the development of smart cities, increasing investments in smart energy infrastructure, growing pressure to enhance hospital sustainability rankings, and the expansion of hospital automation initiatives.

The artificial intelligence-driven hospital energy optimization market size is expected to see exponential growth in the next few years. It will grow to $5.8 billion in 2029 at a compound annual growth rate (CAGR) of 23.6%. The growth during the forecast period can be attributed to increasing concerns over emerging pathogens and antimicrobial resistance, an expanding aging population, rising adoption of healthcare artificial intelligence in research, growing implementation of smart hospital infrastructure, and the increasing prevalence of chronic diseases. Key trends expected in the forecast period include advancements in AI algorithms, integration of AI with IoT sensors, innovations in machine learning models, developments in cloud computing, and progress in smart grid technology.

The rising adoption of smart hospital infrastructure is expected to drive the growth of the AI-driven hospital energy optimization market in the coming years. Smart hospital infrastructure consists of advanced digital technologies that enable efficient healthcare delivery, real-time monitoring, and automated management of hospital resources. This adoption is primarily fueled by the need to improve patient outcomes through real-time data monitoring, allowing faster diagnoses and personalized treatment, ultimately enhancing the quality and efficiency of care. Smart hospital infrastructure supports AI-driven hospital energy optimization by providing interconnected sensors and real-time data from various systems, allowing AI algorithms to analyze energy usage patterns and automatically adjust settings to reduce consumption and improve efficiency. For example, in December 2024, the Centers for Disease Control and Prevention (CDC), a US-based national public health agency, reported that 88.2% of office-based physicians were using electronic health records (EHR) systems, with 77.8% adopting certified EHR systems. As a result, the increasing implementation of smart hospital infrastructure is driving the growth of the AI-driven hospital energy optimization market.

The growing shift towards remote monitoring solutions is also expected to propel the AI-driven hospital energy optimization market. Remote monitoring solutions utilize digital tools and technologies to track patient health data outside traditional clinical settings, enabling continuous care and early intervention. This trend is gaining momentum as healthcare providers seek real-time patient insights, allowing continuous health tracking and timely interventions, thereby improving care quality and efficiency. AI-driven hospital energy management systems facilitate remote monitoring of energy usage and equipment performance, detecting inefficiencies, forecasting maintenance needs, and enabling hospitals to optimize energy consumption remotely. For instance, in December 2023, the National Health Service (NHS), a UK-based government department, reported 33.6 million app users, with monthly logins increasing by 54% over the past year, from 16.8 million to 25.8 million. Therefore, the shift toward remote monitoring solutions is fueling growth in the AI-driven hospital energy optimization market.

Key players in the AI-driven hospital energy optimization market are focusing on intelligent energy management to accelerate the deployment of energy-efficient solutions across healthcare facilities. Intelligent energy management involves using AI, cloud computing, and IoT technologies to monitor, analyze, and automatically optimize hospital energy systems, such as HVAC, for improved efficiency and reduced consumption. For example, in April 2024, True Digital Group, a Thailand-based digital transformation company, partnered with Alibaba Cloud, a China-based cloud computing provider, to launch the Climate Technology Platform. The platform leverages Alibaba Cloud’s AI-driven "Energy Expert" solution combined with cloud, IoT, and big data analytics to help businesses in Thailand identify energy efficiency challenges, reduce greenhouse gas emissions, and adopt sustainable technologies. It supports real-time energy management and predictive insights, aiming to accelerate Thailand’s green transition and reduce emissions by up to 40% by 2030, with the goal of achieving carbon neutrality by 2050. Pilot projects, such as the HVAC system at Bangkok Hospital, have already demonstrated energy consumption reductions of up to 15%.

Major players in the artificial intelligence-driven hospital energy optimization market are Enel S.p.A., General Electric Company, Veolia Environnement S.A., Schneider Electric SE, Honeywell International Inc., ABB Group, Eaton Corporation Plc, Johnson Controls International Plc, Trane Technologies Plc, Centrica Business Solutions Ltd., Rockwell Automation Inc., Ameresco Inc., ENGIE Impact, GridPoint Inc., Optimum Energy LLC, Verdigris Technologies, Enerbrain, BuildingIQ Inc., Deerns, Resync.

North America was the largest region in the artificial intelligence-driven hospital energy optimization market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence-driven hospital energy optimization market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence-driven hospital energy optimization market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sudden escalation of U.S. tariffs and the consequent trade frictions in spring 2025 are severely impacting the healthcare sector, particularly in the supply of critical medical devices, diagnostic equipment, and pharmaceuticals. Hospitals and healthcare providers are facing higher costs for imported surgical instruments, imaging equipment, and consumables such as syringes and catheters, many of which have limited domestic alternatives. These increased costs are straining healthcare budgets, leading some providers to delay equipment upgrades or pass on expenses to patients. Additionally, tariffs on raw materials and components are disrupting the production of essential drugs and devices, causing supply chain bottlenecks. In response, the industry is diversifying sourcing strategies, boosting local manufacturing where possible, and advocating for tariff exemptions on life-saving medical products.

Artificial intelligence (AI)-driven hospital energy optimization employs AI to monitor and manage energy usage within hospitals. Its goal is to improve energy efficiency, reduce costs, and minimize environmental impact while maintaining smooth hospital operations.

The primary components of AI-driven hospital energy optimization include software, hardware, and services. The software is a digital system that uses AI to continuously track, assess, and enhance hospital energy consumption. It can be deployed through on-premises or cloud-based solutions and is utilized by hospitals of various sizes, including small, medium, and large facilities. Applications include optimization of heating, ventilation, and air conditioning (HVAC) systems, lighting control, energy management, equipment monitoring, and more. Key end users include public hospitals, private hospitals, specialty hospitals, and other healthcare facilities.

The artificial intelligence-driven hospital energy optimization market research report is one of a series of new reports that provides artificial intelligence-driven hospital energy optimization market statistics, including artificial intelligence-driven hospital energy optimization industry global market size, regional shares, competitors with a artificial intelligence-driven hospital energy optimization market share, detailed artificial intelligence-driven hospital energy optimization market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence-driven hospital energy optimization industry. This artificial intelligence-driven hospital energy optimization market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The artificial intelligence-driven hospital energy optimization market consists of revenues earned by entities by providing services such as energy consumption monitoring and analysis, predictive maintenance and fault detection, and automated energy control and scheduling. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence-driven hospital energy optimization market also includes sales of energy management systems, predictive maintenance tools, and energy usage analytics dashboards. Values in this market are ‘factory gate’ values; that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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