The Jaide Health platform provides AI-assisted language support for routine verbal exchanges and written translations commonly used throughout the healthcare process. These include intake-related communications, discharge information, and other administrative interactions where language barriers can create delays for patients and healthcare staff. According to AMN, human interpreters will continue to be used when conversations require greater clinical accuracy, empathy, and patient-safety considerations. The acquisition is intended to address communication gaps that often arise outside physician consultations and acute-care settings.

“This is an important strategic move in AMN’s ongoing mission to improve access to care for all,” said Cary Grace, President and CEO of AMN Healthcare. “By expanding language support across more moments in the healthcare journey, we can help health systems deliver a more seamless experience for patients and care teams while continuing to rely on the critical expertise of our qualified interpreters when it matters most.”

The Jaide Health solution is already in use with clients operating across multiple healthcare environments, where it has been applied to patient communications and workflow support. AMN stated that the technology has demonstrated value in real-world healthcare settings and will now become part of its broader language services offering. As part of the transaction, the Jaide Health team will join AMN Healthcare.

“We believe we’ve built one of the strongest solutions in the market, and joining AMN Language Services lets us reach more patients through AMN’s scale and clinical-quality standards,” said Joe Corkery, MD, CEO and co-founder of Jaide Health. “AMN was our first choice because of our shared commitment to quality. Together, we can pair smart AI assistance with the high standards of AMN’s human interpreting to provide LEP patients with a voice outside of clinical encounters, which we know leads to better outcomes and experiences.”

Financial terms of the deal were not disclosed. The AMN Healthcare Acquires Jaide Health transaction expands language support capabilities across the patient journey, while the AMN Healthcare Acquires Jaide Health announcement also reinforces the continued importance of human interpreters in healthcare communications.

The decision follows findings that equated the daily time savings to roughly five weeks per staff member each year. Health Innovation and Safety Minister Preet Kaur Gill said: “Every day, doctors, nurses and other healthcare professionals spend valuable time on administrative tasks that take them away from patients.” She added: “By rolling out Microsoft Copilot across the NHS, we can reduce that burden, free up clinicians’ time and help staff focus on what they do best, caring for patients.” Rob Thompson, Chief Digital, Data and Technology Officer at NHS England, said: “The potential to save clinical staff nearly a day’s worth of admin time every fortnight could be a gamechanger for patients.” He added: “We’re making sure every pound is spent on cutting waiting times and boosting care through the Plan for Change and 10 Year Health Plan.”

The deployment will support a range of operational and administrative functions across NHS England. Ward clerks will use the technology for patient discharge processes, rota planning and bed management, while medical secretaries will apply it to meeting documentation and template creation. Administrative teams in HR, finance and procurement will also use the platform, and management groups will employ it to prepare board papers and briefings. NHS England will additionally gain access to Copilot Studio, enabling individual NHS Trusts to build customized AI agents for workflow automation, including support for helpdesk operations, complaints handling, freedom of information requests and financial processing. Agent 365 will provide governance controls to ensure those agents comply with organizational security requirements.

Microsoft UK and Ireland CEO Darren Hardman said: “By rolling out Microsoft 365 Copilot at scale, NHS teams can cut through everyday admin and spend more time where it matters most.” He added: “Bringing AI safely into the flow of healthcare will help ease pressures, improve productivity, and support better decision-making across the health service.” NHS England serves approximately 56 million people and employs around 1.4 million staff, making this one of the largest enterprise AI deployments undertaken by a healthcare organization. The structured onboarding programme will run for 12 months and is intended to support adoption across the health system while providing a large-scale example of AI implementation in public healthcare.

Under the terms of the agreement, clients operating within corporate health trusts, private medical insurance claims environments, and NHS-commissioned care settings will gain access to a comprehensive analysis of their historic claims data. The objective is to ensure these organisations are receiving genuine value for money through a rigorous examination of how resources are being deployed. Using machine learning and medical expertise, the solution retrospectively analyses medical treatment data alongside insurer-approved treatment plans to identify where waste can be minimised and resources maximised making this a meaningful advancement in healthcare claims intelligence.

Neil Atkinson, Mercer Marsh Benefits UK Strategic Healthcare Consulting Leader, underlined the urgency behind the collaboration: “Healthcare organisations are under increasing pressure to improve outcomes while managing costs and complexity. Together, Marsh and Kirontech will help clients spend their resources effectively and ensure people are being treated appropriately. This agreement means we can accelerate our strategy to positively impact societal healthcare.”

Omar Chebli, Chief Executive Officer of Kirontech, highlighted the untapped potential within organisations’ existing data: “Healthcare organisations are sitting on data that could transform how they manage risk and allocate resources, but turning that into confident, board-level decisions requires the right expertise alongside the right technology. Collaborating with Marsh means we can bring that full picture to a much wider range of organisations, faster. Together, we are giving leadership teams the clarity to act and the confidence that their money is being spent where it matters most.”

The partnership between Marsh and Kirontech positions healthcare claims intelligence as a critical lever for organisations seeking to align clinical outcomes with financial accountability ensuring that both patient welfare and institutional resources are managed with greater precision and confidence.

According to the two organisations, the healthcare AI model will integrate Mayo Clinic’s anonymised health data, medical knowledge base and patient care experience with Microsoft’s technology infrastructure. Once operational at scale, the model is expected to analyse diverse types of clinical information to support tasks such as earlier diagnosis and more personalised treatment planning.

The model is currently being deployed within Mayo Clinic’s own clinical environment, where it will be tested and refined through real-world application. The organisations have not disclosed how widely the model is being used at this stage, which specific clinical areas are involved, or when it might be made available to other healthcare providers beyond Mayo Clinic.

Ownership of the model will rest with Mayo Clinic, while Microsoft intends to make it accessible to developers and healthcare companies through Azure Foundry APIs software tools that allow external parties to connect the model directly into their own applications and services.

Gianrico Farrugia, M.D., president and CEO of Mayo Clinic, commented on the development: “We have long believed AI can help transform healthcare. Seven years ago, we launched Mayo Clinic Platform to move healthcare from a pipeline to a platform model through a safe, trusted, patient-centric de-identified data foundation designed to accelerate innovation, breakthroughs, and cures. Now, by combining our clinical expertise and data foundation with Microsoft’s engineering and AI capabilities, we are once again building something new in healthcare and bringing more of Mayo Clinic to more patients.”

Mustafa Suleyman, CEO of Microsoft AI, also spoke on the collaboration: “This is the best collaboration imaginable to help us accelerate towards that future. Mayo has unparalleled clinical expertise, de-identified clinical health data and longitudinal medical insights, and we’re thrilled to partner with their world-class physicians to build a state-of-the-art foundation model for healthcare.”

Healthcare has emerged as one of the most active frontiers for advanced artificial intelligence development, though it also presents considerable challenges. Medical AI systems must be capable of handling complex clinical data, accommodating individual patient health histories, and satisfying the most rigorous standards for safety, privacy and validation.

Under the European Union’s AI Act, AI-based software developed for medical purposes is classified as high-risk. This classification requires that such systems meet a defined set of safeguards, including risk-mitigation mechanisms, high-quality training datasets, clear communication to users, and ongoing human oversight, as outlined by the European Commission.

The growing use of AI in healthcare is reflected in broader public behaviour as well. A 2025 survey of 2,000 patients in the United Kingdom, conducted by healthcare startup Semble, found that one in four representing 24% of respondents were turning to AI tools and social media platforms such as ChatGPT and Instagram for health-related guidance. Separately, in Denmark, visits to the public health information website Patienthåndbogen dropped by 31% between January and November 2025 following the launch of Google’s AI Overview, according to the country’s national news agency Ritzau.

Healthcare AI model development is gaining momentum because the technology holds the potential to process large volumes of medical information rapidly, assist clinicians in diagnostics and complex clinical decisions, and significantly reduce the administrative burden on healthcare staff. Microsoft has described “frontier medical intelligence” as being close to realisation, positioning this partnership as a step in that direction.

Nevertheless, the application of artificial intelligence in medicine continues to raise legitimate concerns around accuracy, potential bias, data privacy and accountability. These concerns are particularly prominent given the sensitive nature of health data and the direct impact that clinical decisions can have on patient outcomes. The two organisations have not provided a detailed timeline for when the healthcare AI model will be made available to healthcare providers outside of Mayo Clinic’s own clinical setting.

Among the newly cleared capabilities is Auto Measure Abdomen, an AI-enabled feature developed to automate routine measurement tasks during examinations. Philips said the technology can help reduce variability in measurements while saving time for clinicians. The company also expanded access to Koios AI decision-support tools, which were previously available off-cart. The functionality is now integrated directly into EPIQ Elite and Affiniti systems, allowing clinicians to classify breast lesions and thyroid nodules within the ultrasound workflow. According to Philips, integration with Koios Bi-RADS enables interpretation and malignancy risk assessment in less than two seconds.

The Elevate Plus package also introduces imaging upgrades aimed at improving visualization of anatomy and blood flow. Philips said XRes Pro+ provides cleaner tissue detail and sharper anatomical boundaries, helping create more consistent images across different body types. In addition, Super Res MVI Pro enhances visualization of microvascular flow, giving clinicians greater clarity when assessing blood circulation and vascular structures. These enhancements are designed to improve image quality while supporting more efficient diagnostic workflows.

Commenting on the clearance, Jie Xue, chief business leader, Precision Diagnosis, Philips, said: “Elevate Plus underscores our commitment to advancing AI-powered ultrasound to help clinicians deliver more consistent, efficient, and confident ultrasound care to patients. By combining intelligent imaging with AI-powered workflow automation across our ultrasound platform, Elevate Plus is designed to reduce variability, streamline routine exams, and support faster, more informed clinical decisions as care teams face growing demand.”

Gretchen Sammy, ultrasound manager at Boston Medical Center, stated: “Elevate Plus is a game-changer for our ultrasound workflow. Automating key measurement tasks allows our sonographers to reduce scanning time by up to 30% without sacrificing clinical precision. During our evaluation, measurements were consistently placed exactly where we would expect them saving time while maintaining the accuracy we rely on.”

Maria Cristina Chammas, director of ultrasound at Hospital das Clínicas, School of Medicine, University of São Paulo, added that AI Ultrasound automation could help shorten scanning times, improve workflow efficiency and reduce repetitive manual tasks that contribute to sonographer fatigue while supporting more consistent clinical results.

The radiology network acquisition encompasses I-MED’s minority equity interest in Harrison.ai, a technology firm developing artificial intelligence applications for radiology, including computed tomography (CT) chest and brain scans. I-MED delivers comprehensive diagnostic imaging services across regional and metropolitan regions. As an established teleradiology provider, I-MED offers remote medical image interpretation across Australia, the US, and New Zealand. This service aids patient diagnostics in areas experiencing radiologist shortages. The core modalities include:

• Magnetic resonance imaging (MRI) and computed tomography (CT)
• Positron emission tomography (PET) and nuclear medicine
• Ultrasound and X-ray diagnostics

Jardine Matheson plans to finance this healthcare investment utilizing a combination of debt and cash reserves on its balance sheet. The transaction supports the organization’s long-term strategy for APAC healthcare investment in prominent regional enterprises. Jardine Matheson CEO Lincoln Pan stated that the company is eager to collaborate with Dr. Shrey Viranna, Clare Battellino, and the I-MED clinical team. Pan highlighted the management team’s ability to drive earnings growth and maintain innovation, specifically referencing the AI integration that supports their market position and high clinical standards. He added that the goal of this long-term investment is to develop larger, high-quality assets across their portfolio.

Excluding the Harrison.ai stake, Jardine Matheson forecasts that I-MED’s core operations will achieve an adjusted EBITDA multiple of approximately 11.5x the purchase price for the 12-month period ending June 2026. Furthermore, over the five years leading up to June 2025, the teleradiology provider reported a compound revenue increase of 11% and an adjusted EBITDA growth of 12%. The continuous demand for remote medical image interpretation contributes to supporting these consistent financial metrics.

The closing of the transaction remains subject to customary regulatory approvals and is scheduled to be finalized later in 2026. For this radiology network acquisition, Jardine Matheson retained Rothschild and Co for financial counsel. EY-Parthenon supplied tax and financial guidance, while Chapman Tripp, Linklaters, and Allens acted as legal advisors for the healthcare investment.

Artificial intelligence is increasingly being integrated into healthcare workflows to improve diagnostic accuracy, optimize treatment planning, support predictive analytics, automate administrative tasks, and accelerate drug discovery processes. Technologies including machine learning, natural language processing, computer vision, and AI-enabled decision support systems are becoming central to digital healthcare transformation strategies adopted by hospitals, pharmaceutical companies, and healthcare providers globally.

The market is being driven by rising healthcare digitization, growing volumes of clinical and patient data, increasing demand for personalized medicine, and the need for more efficient healthcare delivery systems. Healthcare organizations are also investing in AI tools to reduce operational burdens, improve workflow automation, and strengthen data-driven clinical decision-making. The growing use of generative AI in clinical documentation, patient engagement, and healthcare analytics is further contributing to market expansion.

Key Market Drivers

• Increasing adoption of AI-powered diagnostics and medical imaging technologies
• Rising demand for personalized and data-driven healthcare solutions
• Growing investments in healthcare digital transformation initiatives
• Expansion of AI applications in drug discovery and pharmaceutical R&D
• Rising focus on workflow automation and operational efficiency in hospitals

Industry Developments

Several major healthcare and technology companies have expanded AI-related initiatives during 2026 as competition intensifies across diagnostics, cloud-based healthcare systems, and pharmaceutical innovation.

In April 2026, Roche agreed to acquire PathAI to strengthen capabilities in AI-powered pathology and precision medicine. During the same month, Merck announced a multi-year collaboration with Google Cloud to integrate generative AI and cloud technologies into drug discovery and manufacturing operations.

Also in April 2026, CVS Health partnered with Google Cloud to launch an AI-enabled healthcare engagement platform focused on personalized healthcare management and integrated health data access.

In Japan, healthcare institutions accelerated deployment of AI technologies across hospital operations and patient management systems. In March 2026, Fujitsu Japan and Teikyo University Hospital initiated a joint demonstration project using AI-OCR and healthcare analytics to improve referral management and hospital efficiency. Earlier in February 2026, JCHO Osaka Hospital, Fujitsu Japan, and Fortience Consulting launched a generative AI initiative focused on discharge summaries and nursing handovers.

In April 2026, ŌURA acquired Galen AI to strengthen AI-powered health data interpretation capabilities integrating wearable insights, medication histories, and medical records into preventive healthcare applications.

In January 2026, OpenAI acquired healthcare startup Torch as part of efforts to expand development of AI-enabled healthcare technologies and medical AI applications.

Competitive Landscape

The AI in Healthcare Market remains highly competitive, with technology companies, healthcare providers, pharmaceutical firms, and digital health specialists expanding investments across diagnostics, cloud computing, automation, and clinical analytics.

Major companies operating in the market include Intel Corporation, Koninklijke Philips N.V., Microsoft, Siemens Healthcare GmbH, NVIDIA Corporation, GE Healthcare, Medtronic, Oracle, IQVIA, and Cognizant.

Future Outlook

The AI in healthcare sector is expected to continue expanding as healthcare providers and pharmaceutical companies increase adoption of automation, predictive analytics, and AI-driven clinical tools. Advancements in generative AI, cloud computing, medical imaging, and digital health infrastructure are expected to support broader integration of AI technologies across healthcare systems worldwide.

The Ooredoo Kuwait and Hadi Clinic initiative seeks to deploy smart healthcare, integrated solutions that enhance the operational efficiency of medical services while significantly improving the patient experience. By leveraging advanced technology, the partnership intends to build a robust framework for future medical service delivery.

Under the terms of the agreement, Ooredoo Kuwait, in collaboration with technology partner Huawei, will implement an extensive healthcare ICT ecosystem. This infrastructure will include next-generation networks, high-performance data centers, and cloud computing technologies. The project also encompasses advanced storage solutions, disaster recovery protocols, and comprehensive backup systems to ensure operational continuity.

This advanced digital infrastructure is expected to facilitate the transition toward a smart healthcare and hospital model. By utilizing these technologies, healthcare providers can improve the management of medical data and utilize artificial intelligence to assist in clinical decision-making processes. The integration of these systems is projected to enhance service quality and streamline hospital operations.

A primary focus of the collaboration is the strengthening of cybersecurity frameworks to ensure patient data security and maintain high standards of privacy. The Digital Healthcare Kuwait Hadi partnership emphasizes the creation of a secure digital environment that fosters trust and reliability in medical services.

Sulaiman AlHomoud, Director of B2B Marketing at Ooredoo, stated that the partnership reflects a commitment to empowering the healthcare sector through innovative digital solutions. He noted that the project supports the healthcare ecosystem with secure, scalable infrastructure that meets future demands and aligns with Kuwait Vision 2035.

Mubarak AlMailem, General Manager of Hadi Clinic, described the partnership as a strategic step toward the comprehensive development of the healthcare system. He emphasized that the cooperation will enable the hospital to deliver more accurate and personalized medical services. He further highlighted that protecting patient data remains a top priority, with advanced cybersecurity systems being implemented to ensure reliability.

Zaid AlMailem, Deputy General Manager, added that the hospital remains committed to continuous innovation, noting that the adoption of these advanced technological solutions will enhance clinical outcomes and operational efficiency across the institution.

Japan’s healthcare sector continues to face growing strain as the country’s aging population increases demand for medical services. Medical costs have risen beyond 48 trillion yen annually, while healthcare providers are dealing with staffing shortages, financial pressures, and broader sustainability concerns within the social security system. At the same time, medical data required for advanced clinical research remains insufficiently standardized and fragmented across institutions, limiting broader utilization. Fujitsu and IBM Japan said easing the administrative burden on healthcare workers and enabling more efficient use of medical data across organizations will be essential for improving care delivery. Under the collaboration, the companies will jointly promote operational efficiency initiatives while supporting medical DX measures encouraged by the Japanese government. Their sovereign cloud platform will serve as a common foundation for healthcare applications provided by both companies, enabling medical institutions to adopt cloud-based systems with stronger control over data management and security.

The companies also plan to integrate and jointly utilize their AI technologies for the healthcare industry. With consent from healthcare providers and patients, Fujitsu and IBM Japan aim to securely combine data from multiple medical institutions in Japan to improve clinical and operational workflows. Planned use cases include AI support for preparing clinical and nursing reports as well as streamlining DPC coding processes linked to medical fee claims. The collaboration is also exploring initiatives connected to drug discovery and clinical development, including identifying patients eligible for clinical trials and improving research efficiency. By expanding cooperation with university hospitals, national centers, and other medical institutions, the companies intend to validate healthcare data and AI applications before phased deployment. Medical AI will also support future patient-centric services covering appointment booking, treatment processes, and post-care follow-up.

The launch follows increasing use of artificial intelligence tools within hospital pharmacy environments. Bluesight’s 2026 research found that 24% of pharmacy leaders currently use AI every day, while 35% of diversion professionals already depend on tools such as ChatGPT and Microsoft Copilot to review controlled substance data. Prism Assistant was developed specifically for diversion monitoring workflows rather than general-purpose AI applications. The company stated that the platform functions entirely within its secure infrastructure, uses integrated ControlCheck data sources, and aligns with Google’s Secure AI Framework (SAIF). “Demand for generative AI in diversion monitoring is already here,” said Kevin MacDonald, CEO and co-founder of Bluesight. “But many teams are using tools that weren’t built for sensitive healthcare data or diversion workflows. Prism Assistant delivers the speed they need while keeping data secure and grounded in the workflows they already trust.”

Using Prism Assistant, diversion teams can request reports, graphs, and evidence-backed responses related to provider behavior and controlled substance trends in less than a minute. Bluesight said this allows staff to spend more time on higher-priority investigations, regulatory compliance activities, and diversion confirmation processes instead of manually assembling data. Twenty health systems are already deploying the assistant within ControlCheck for peer comparisons, executive reporting, and staff investigation analysis. Reported outcomes include recurring reports being completed 96% faster, pre-investigation triage reduced from three hours to around 10 minutes, and detailed variance analysis shortened from 30 minutes to under a minute. Bluesight also confirmed the Hospital AI Platform will expand into PrivacyPro later this year while the company develops agentic AI capabilities capable of handling multi-step workflows independently.