AI in Emergency Room and Hospital Management Market Research Report - Segmented By Offerings (Hardware, Software, Services); By Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision); By End User (Hospital & Healthcare Providers, Patients, Pharmaceuticals & Biotechnology Companies, Healthcare Payers, Others); and Region - Size, Share, Growth Analysis | Forecast (2023 – 2030)

AI in Emergency Room and Hospital Management Market Size (2023 – 2030)

As per our research report, the global AI in Emergency Room and Hospital Management Market size was USD 1.9 billion in 2022 and is estimated to grow to USD 13.86  billion by 2030. This market is witnessing a healthy CAGR of 28.2% from 2023 - 2030. Increasingly large and complex data set available in the form of big data and the growing need to reduce the increasing healthcare cost drive the growth of this market.       


 AI IN EMERGENCY                                                            

Industry Overview:

Developing and implementing artificial intelligence (AI) applications in healthcare is a matter of research and management at the same time. Especially in hospitals, there are increasing expectations for the introduction of new types of AI applications to improve efficiency and effectiveness. However, experience with real AI use cases is still rare. As a first step in building and comparing such experiences, this paper presents a comparative approach from nine European hospitals and 11 different use cases, highlighting potential application areas and the benefits of hospital AI technology. indicate.

It consists of timely reviews and opinion pieces from various researchers and medical professionals. This contributes to significant improvement opportunities in the event of a pandemic crisis. B. Current status of COVID 19. Expected benefits and challenges related to data protection, privacy, or human acceptance are reported. Overall, the various use cases are core characteristics of AI applications in hospitals and require a specific approach for successful implementation in healthcare. This includes specialized solutions for hospitals related to human-computer interaction, data management, and communication in AI implementation projects. 

Advanced healthcare technology helps manage medical records and other hospital management data. B. When editing and evaluating patient data, inventory updates, replacement requests, etc. AI-enabled robots help collect, store, and relocate data for faster, more consistent access. It also helps minimize routine tasks that robots can perform faster and more accurately, such as test analysis, x-rays, CT scans, and data entry. In cardiology and radiology, with the help of AI, the data are examined according to the instructions given without human intervention. In the future, cardiologists and radiologists will only need to deal with the most complex cases where human surveillance is worthwhile.

 Digital counseling smartphone apps like Babylon Health in the UK use AI to provide medical advice based on an individual's medical history and general medical knowledge. Users report symptoms in the app. The app uses voice recognition to match symptoms against a database of illnesses. Babylon Health then provides a recommended set of actions, taking into account the user's medical history.

Startup Sensely has created Molly, a digital nurse who helps people monitor their patient's conditions and provide treatment between doctor visits. The program uses machine learning to support patients with a focus on chronic illness. Boston Children's Hospital in the United States has developed an  Amazon Alexa application that provides important health information and guidance to parents of sick children. The app answers questions about medicines and suggests whether the symptoms justify a doctor's consultation.

COVID-19 impact on AI in Emergency Room and Hospital Management Market

The healthcare AI  market has historically grown significantly due to the rapid adoption of AI and ML solutions in the healthcare sector. The outbreak of the COVID 19 pandemic proved an opportunity to demonstrate the power and sophistication of AI for the healthcare sector. During the second wave of pandemics, hospitals and clinics around the world used AI-based virtual assistants, inpatient bots, and AI-powered surgical robots to overwhelm the entire hospital operating cycle. Handled a continuous influx of deaf patients. Several countries such as the United States, Germany, France, China, India, Japan, and South Korea are funding the development of AI applications in health care, and the market is expected to grow rapidly between five and ten years.

 The main drivers of the market are unprecedentedly large and complex datasets, reducing increasing health costs, increasing computing power and reducing hardware costs, and cross-industry partnerships to drive the need for AI. Increasing numbers of collaborations and health imbalances, and workers and patients are driving the need for instant medical services. Another key driver of the current market is the adoption of this technology by several pharmaceutical and biotechnology companies around the world to speed up the COVID 19 vaccine or drug development process. The biggest obstacles to the market are the hesitation of medical professionals to adopt AI-based technology and the lack of qualified workers. The critical challenges facing  AI in the healthcare market include lack of curated healthcare data, privacy concerns, and lack of interoperability between AI solutions.

 Opportunities underlying the healthcare AI  market include increasing potential for AI-based tools for elderly care and increasing attention to the development of human-aware AI systems. The emergence of the COVID 19 pandemic, which is placing a heavy burden on healthcare infrastructure around the world, is expected to force healthcare providers, payers, and pharmaceutical companies to adopt AI technology. In the medical system after COVID-19, AI is expected to be importantly adopted in drug discovery, medical imaging, pathology, mental health, auxiliary robots, and precision medical applications.


Improved Computing Power using Hardware and Software has driven the Growth Of the Market

The increasing adoption of AI has become a new growth driver for semiconductor chip makers in recent years. GPU / CPU makers such as Nvidia, AMD, Intel, Qualcomm, Huawei, and Samsung have invested heavily in this area to develop chipsets that are compatible with AI-based technologies and solutions. In addition to CPUs and GPUs, application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) are being developed for AI applications.  Computational chipsets are one of the key parameters for processing AI algorithms. The faster the chipset, the faster it will process the data needed to build an AI system. Currently, AI chipsets are mainly used in data centers / high-end servers.

Declining Hardware Cost is another factor that is driving the growth of the Market

The cost of a few AI hardware products has significantly decreased in the past year, which further increases the adoption of AI in new applications, and thus drives the growth of the AI chipsets market. There is a huge market for AI in the future which is why suppliers, as well as sellers, are focusing on providing cheap but good products to the customers to attract them and thus driving the growth of the market.


Confusion Among Medicinal Practitioners About AI-Based Technologies is restraining the growth of the market.

There is an observed reluctance among physicians to new technologies. For example, healthcare practitioners mistakenly believe that AI will replace doctors in the coming years. Physicians and practitioners believe that skills such as empathy and persuasion are human skills, and therefore technology cannot completely rule out a physician's presence. In addition, there are concerns that patients may be unduly predisposed to these technologies and reject necessary direct treatments, which could also challenge the long-term relationship between physicians doctor and patients. Currently, many healthcare professionals doubt the ability of AI solutions to accurately diagnose a patient's condition. Therefore, it is difficult to convince vendors that AI-based solutions are cost-effective, effective, and safe solutions that bring convenience to doctors as well as good patient care.




Market Size Available

2022 - 2030

Base Year


Forecast Period

2023 - 2030



Segments Covered

By Offering, Technology, End User and Region

Various Analyses Covered

Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities

Regional Scope

North America, Europe, APAC, Latin America, Middle East & Africa

Key Companies Profiled

NVIDIA (US), Intel (US), IBM (US), Google (US), Microsoft (US), AWS (US), General Vision (US), GE Healthcare (US), Siemens Healthineers (Germany), Medtronic plc (US), Johnson & Johnson (US), and Koninklijke Philips N.V. (Netherlands)

This research report on the AI in Emergency Room and Hospital Management Market has been segmented and sub-segmented based on Offering, Technology, end-user, and region.

AI in Emergency Room and Hospital Management Market- By Offering

  • Hardware

  • Software

  • Services

Based on Offerings Section, "Services segment will witness the highest growth rate among other services during the forecast period"

 Increasing adoption of AI solutions is expected to drive the growth of the services segment, which is projected to experience the highest growth. For successful AI implementation, implementation and integration services, as well as support and maintenance are needed. Most companies that manufacture and develop AI systems and software provide online and offline support depending on the application.

The software segment will also continue to see more growth in the upcoming years as more and more software providers are also coming into the market to follow and compete with each other in the section which is why this market is seeing healthy growth.

AI in Emergency Room and Hospital Management Market – By Technology

  • Machine Learning

  • Natural Language Processing

  • Context-aware Computing

  • Computer Vision

Based on Technology, Machine learning's ability to capture and manage big data and the growing adoption of ML by hospitals, research centers, pharmaceutical companies, and other healthcare organizations to improve patient health is driving the growth of AI in the healthcare market. The growing adoption of NLP for applications such as patient data and risk analysis, lifestyle management and monitoring, and mental health is driving the growth of this technology in the market.

AI in Emergency Room and Hospital Management Market - By  End User 

  • Hospital & Healthcare Providers

  • Patients

  • Pharmaceuticals & Biotechnology Companies

  • Healthcare Payers

  • Others

Based on End-user, The hospital and provider segment is expected to account for the largest size of AI in the healthcare market in terms of end-users, during the forecast period. Some of the key factors leading to the high market share of hospital and vendor segments include a large number of AI solution applications in vendor settings; the ability of AI systems to improve care delivery, patient experience, and reduce costs; and the growing acceptance of electronic health records by healthcare organizations. In addition, AI-based tools such as speech recognition software and clinical decision support systems are helping to streamline hospital workflows, reduce costs, improve service delivery, and improve service delivery. care and improve the patient experience.

AI in Emergency Room and Hospital Management Market - By Region

  • North America

  • Europe

  • Asia-Pacific

  • Latin America

  • The Middle East and Africa

Geographically, the market is segmented into North America, Latin America, Europe, Asia-Pacific, and the Middle East & Africa region.  The North American market is expected to lead the market during the forecast period due to the increasing adoption of healthcare IT solutions, and the availability of capital to develop AI capabilities and infrastructure. Well-established healthcare floors.

Although the Asia-Pacific market is expected to emerge shortly, due to the growth in healthcare infrastructure, the growing number of AI startups, and the increasing number of AI startups. Significant in the adoption of advanced technology are some of the factors contributing to the growth of the market in the region.

Along with that, Europe is also leading in terms of ongoing clinical trials, which is also expected to contribute to the market growth in the region. Recently, about 500 clinical trials have been reported to the National Health Service (NHS). The UK is also expected to be at the forefront of research in heart disease, immunology, and related diseases of the nervous system.

AI in Emergency Room and Hospital Management Market Share by company:

Companies like

  • Intel (US)
  • IBM (US)
  • Google (US)
  • Microsoft (US)
  • AWS (US)
  • General Vision (US)
  • GE Healthcare (US)
  • Siemens Healthineers (Germany)
  • Medtronic plc (US)
  • Johnson & Johnson (US)
  • Koninklijke Philips N.V. (Netherlands) 

Philips launched two new HealthSuite solutions. HealthSuite solutions allow health systems to integrate informatics applications that can be combined and scaled up or down according to emerging needs. Philips HealthSuite solutions help health systems deliver on the quadruple aim through a connected, protected, future-ready, and cost-predictive single cloud infrastructure and Software-as-a-Service (SaaS) model.

IBM launched two-nanometer chip technology. It will increase chip performance, increase efficiency, and will help in AI and cloud applications.IBM launched advanced storage solutions designed to simplify data accessibility and availability for cloud and AI applications.

Nvidia announced the launch of A30 &A10 GPUs for enterprise servers. Nvidia launched Morpheus to enable cybersecurity providers to develop AI solutions that can instantly detect cyber breaches.


  • Product Launch - In August 2021, Philips launched two new HealthSuite solutions. HealthSuite solutions enable healthcare systems with integrated IT applications that can be combined and scaled based on emerging needs. Philips HealthSuite solutions help healthcare systems achieve their 4X Goals with a cost-predictive and connected cloud infrastructure, protected, future-ready, and the  SoftwareasaService model ( SaaS).
  • Collaboration - In May 2021, IBM launched two-nanometer chip technology. It will increase chip performance, increase efficiency, and will help in AI and cloud applications.
  • Product Integration - In April 2021,  Nvidia launched Morpheus to enable cybersecurity providers to develop AI solutions that can instantly detect cyber breaches.

Chapter 1. AI in Emergency Room and Hospital Management Market – Scope & Methodology

1.1. Market Segmentation

1.2. Assumptions

1.3. Research Methodology

1.4. Primary Sources

1.5. Secondary Sources

Chapter 2. AI in Emergency Room and Hospital Management Market – Executive Summary

2.1. Market Size & Forecast – (2023 – 2030) ($M/$Bn)

2.2. Key Trends & Insights

2.3. COVID-19 Impact Analysis

       2.3.1. Impact during 2023 - 2030

       2.3.2. Impact on Supply – Demand

Chapter 3. AI in Emergency Room and Hospital Management Market – Competition Scenario

3.1. Market Share Analysis

3.2. Product Benchmarking

3.3. Competitive Strategy & Development Scenario

3.4. Competitive Pricing Analysis

3.5. Supplier - Distributor Analysis

Chapter 4. AI in Emergency Room and Hospital Management Market Entry Scenario

4.1. Case Studies – Start-up/Thriving Companies

4.2. Regulatory Scenario - By Region

4.3 Customer Analysis

4.4. Porter's Five Force Model

       4.4.1. Bargaining Power of Suppliers

       4.4.2. Bargaining Powers of Customers

       4.4.3. Threat of New Entrants

       4.4.4. Rivalry among Existing Players

       4.4.5. Threat of Substitutes

Chapter 5. AI in Emergency Room and Hospital Management Market - Landscape

5.1. Value Chain Analysis – Key Stakeholders Impact Analysis

5.2. Market Drivers

5.3. Market Restraints/Challenges

5.4. Market Opportunities

Chapter 6. AI in Emergency Room and Hospital Management Market – By Offerings

6.1. Hardware

6.2. Software

6.3. Services

Chapter 7. AI in Emergency Room and Hospital Management Market – By Technology

7.1. Machine Learning

7.2. Natural Language Processing

7.3. Context-aware Computing

7.4. Computer Vision

Chapter 8. AI in Emergency Room and Hospital Management Market – By End User

8.1. Hospital & Healthcare Providers

8.2. Patients

8.3. Pharmaceuticals & Biotechnology Companies

8.4. Healthcare Payers

8.5. Others

Chapter 9. AI in Emergency Room and Hospital Management Market - By Region

9.1. North America

9.2. Europe

9.3. Asia-Pacific

9.4. Latin America

9.5. The Middle East

9.6. Africa

Chapter 10. AI in Emergency Room and Hospital Management Market – Company Profiles – (Overview, Product Portfolio, Financials, Developments)

10.1. NVIDIA (US)

10.2. Intel (US)

10.3. IBM (US)

10.4. Google (US)

10.5. Microsoft (US)

10.6. AWS (US)

10.7. General Vision (US)

10.8. GE Healthcare (US)

10.9. Siemens Healthineers (Germany)

10.10. Medtronic plc (US)

10.11. Johnson & Johnson (US)

10.12. Koninklijke Philips N.V. (Netherlands) 

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