The Nursing Robots Market is forecast to grow at a CAGR of 17.5%, reaching USD 4.2 billion in 2031 from USD 1.9 billion in 2026.
The global nursing robots market comprises service robotics systems designed to assist healthcare professionals and patients across hospitals, long-term care facilities, rehabilitation centers, and home-care environments. These robots perform a wide range of functions, from material transport and medication delivery to patient monitoring, mobility assistance, and social interaction. Their primary objective is to support healthcare delivery by reducing physical workload, improving operational efficiency, and enabling clinical staff to focus on patient-facing responsibilities.
The market is evolving from hardware-centric deployments toward integrated service models that combine robotics, software, and ongoing technical support. Advances in sensing, navigation, and artificial intelligence have expanded the operational scope of nursing robots, allowing them to function safely in dynamic clinical environments. At the same time, rising healthcare costs, workforce constraints, and demographic aging are reinforcing the role of robotics as a complementary tool rather than a replacement for human caregivers.
Sustained Nursing Shortages: The primary driver for market growth is the global shortage of qualified nursing professionals. Robotics absorb routine, repetitive tasks, allowing clinical staff to focus on high-value patient care.
Demographic Aging Trends: Rapidly growing elderly populations require increased assistance with mobility and daily activities, placing a physical burden on care staff that robots are uniquely equipped to alleviate.
Digital Transformation of Healthcare: As hospitals undergo digital transformation, the proliferation of IoT devices and smart infrastructure creates a need for mobile, connected platforms that act as the physical bridge in a digital network.
Advancements in AI and Sensing: The infusion of AI into robotic platforms allows for predictive maintenance and better human-robot interaction, accelerating market trust and adoption.
Nursing Robots face challenges such as high initial capital expenditure, integration hurdles with legacy hospital infrastructure (like elevators and narrow hallways), and ethical concerns regarding the replacement of human touch in care. Smaller facilities often struggle with the technical burden of managing robotic fleets. However, significant opportunities exist as vendors transition to RaaS models, providing flexible and cloud-native solutions. Growing investments in smart city infrastructure and the expansion of "Hospital-at-Home" models increase the need for versatile robotic platforms. As healthcare becomes more decentralized, nursing robots can emerge as the core physical layer connecting home care to clinical centers, creating new revenue models for tech providers and managed service firms.
Nursing robots are composed of complex mechanical, electronic, and computational components, making their cost structure sensitive to fluctuations in global supply chains. High-performance sensors such as LIDAR units, depth cameras, and force-torque sensors contribute significantly to bill-of-materials costs. Actuators and motors, often reliant on rare earth materials, further influence pricing dynamics.
Advanced computing hardware required for real-time perception and decision-making represents another major cost factor. Specialized processors designed for AI inference, combined with redundant safety systems, increase both production and validation expenses. These costs are compounded by the need for medical-grade materials and compliance testing in healthcare environments.
To manage pricing pressures, manufacturers are increasingly adopting modular designs that allow components to be upgraded or replaced without retiring the entire system. This approach supports longer product lifecycles and reduces total cost of ownership for end-users. Pricing in the market remains premium, reflecting not only hardware complexity but also software development, regulatory compliance, and service support.
The supply chain for nursing robots is geographically distributed, reflecting the specialization of different production stages. Precision mechanical components and sensors are frequently sourced from East Asian manufacturing hubs, while system integration, software development, and clinical customization are often conducted in North America and parts of Europe.
Transportation and deployment logistics add further complexity, particularly for large robots designed for patient transfer or heavy payloads. On-site installation, calibration, and staff training are integral to successful deployment, extending the supply chain beyond manufacturing into service delivery.
Recent geopolitical and trade uncertainties have encouraged manufacturers to regionalize assembly and sourcing where possible. Local assembly not only reduces lead times but also aligns with public procurement preferences in certain markets. As robots increasingly rely on cloud-based services for updates and fleet management, cybersecurity and data governance have become critical components of the supply chain.
Jurisdiction | Key Regulation / Agency | Market Impact Analysis |
Japan | Robot Revolution Initiative / Ministry of Health, Labour and Welfare | Provides structured support and reimbursement pathways for nursing care robots, encouraging adoption in long-term care settings. |
United States | FDA – Center for Devices and Radiological Health | Requires clearance for robots performing regulated medical functions, shaping product design and deployment timelines. |
European Union | Medical Device Regulation (EU 2017/745) | Imposes rigorous clinical and data requirements, favoring established manufacturers with compliance capabilities. |
China | “Robot+” Application Action Plan | Accelerates domestic deployment and manufacturing of healthcare robots, influencing global cost structures and competition. |
September 2025: ST Engineering Aethon and Oracle partnered to deliver an integrated solution that unifies hospital inventory transport with Oracle Fusion Cloud SCM. This allows Aethon's AMRs to automatically pick up and deliver materials based on real-time digital inventory triggers.
July 2025: Diligent Robotics reached a milestone of 300,000 "last-mile" pharmacy deliveries and announced Moxi 2.0 in October 2025. The new platform, powered by NVIDIA Thor, offers 10x the compute of the original model and features an end-to-end action model for complex manipulation.
April 2024: ST Engineering Aethon launched ZenaRx, a next-generation mobile robot specifically for hospital pharmacies and laboratories. The robot features physically latched, biometric-secured doors and an 8x increase in obstacle avoidance speed compared to the legacy TUG T2 model.
Medication delivery and management represents one of the most commercially mature applications for nursing robots. Hospitals face persistent challenges related to medication errors, staff workload, and secure handling of controlled substances. Automating transport between pharmacies, storage areas, and patient floors addresses these concerns by reducing manual handling and improving traceability.
Robots deployed in this segment typically feature secure compartments, authentication mechanisms, and integration with pharmacy information systems. Their value proposition lies in consistency and reliability rather than clinical decision-making. As hospitals expand automation initiatives, medication delivery robots are increasingly viewed as infrastructure assets that support broader digital transformation efforts.
Hospitals constitute the largest end-user segment due to their scale, complexity, and continuous operational demands. Unlike home-care or research settings, hospitals require robots capable of functioning around the clock in crowded, multi-level environments. Fleet-based deployment is common, with multiple units coordinated to maximize utilization.
Return on investment in this segment is often measured through labor reallocation and operational efficiency rather than direct cost reduction. Hospitals also prioritize vendor support, system uptime, and interoperability with existing IT infrastructure. As a result, purchasing decisions tend to favor proven platforms with established service networks.
North America has become one of the most mature regions in the world for Nursing Robots due to the high cost of healthcare labor and advanced technological infrastructure. In the United States, the focus on "Smart Hospitals" and integration with EHR systems like Epic and Cerner is driving the adoption of mobile robotic platforms. Organizations in the U.S. are prioritizing robotics to manage complex staffing shortages and improve patient throughput. Canada is in a similar position regarding the adoption of automation in long-term care facilities; therefore, real-time logistics and patient-assistive robots are in high demand across the region.
The governments and enterprises of South America have begun to explore robotics as a way to modernize their healthcare systems, particularly in Brazil and Argentina. Large private hospital chains are experimenting with robotic delivery systems to assist with managing increasing patient loads in urban centers. While there is still significant work required to lower the cost barrier, a growing number of regional healthcare modernization policies will provide additional motivation for organizations to implement logistical and assistive robotic software.
The implementation of Nursing Robots has been largely accelerated in Europe primarily due to stringent worker safety regulations and the aging population in countries like Germany and Italy. The European Union’s digital strategy promotes the use of advanced robotics to ensure that healthcare staff are protected from physical strain and injuries related to patient lifting. Countries like the United Kingdom have large-scale pilot programs utilizing nursing robots to stabilize their National Health Service (NHS) and protect healthcare assets. Furthermore, the emphasis on data privacy (GDPR) means that robots in Europe are leaders in secure, privacy-preserving patient monitoring.
The Middle East and Africa region is in the early stage of adoption but shows significant growth potential. Gulf countries, particularly the UAE and Saudi Arabia, are investing heavily in "Future Hospitals" as part of national technology visions. Large-scale digital transformation initiatives are increasing the need for automated delivery and telepresence tools. In the UAE, government-led modernization programs are encouraging the adoption of advanced medical tools in new healthcare cities. As digital infrastructure expands, these regions are expected to explore nursing robots to improve service efficiency and clinical reliability.
The rapidly evolving Nursing Robot market in the Asia-Pacific region is attributed to acute demographic pressures and strong government support. Japan has taken a lead in developing standards for "Cybernic" systems and elderly care robots through policies that support aging-in-place. In China, the integration of robotics into public hospitals is enabling the management of massive patient volumes. India, Australia, and South Korea are also investing heavily in healthcare infrastructure. The rapid rise of the medical tourism sector in Thailand and India has created high demand for software-driven robotic solutions that can optimize hospital hospitality and logistics in real time.
Diligent Robotics
ST Engineering Aethon
SoftBank Robotics
Cyberdyne Inc.
Toyota Motor Corporation (Healthcare Division)
Hocoma (DIH)
Moxi (Diligent Robotics)
Pudu Robotics
Keenon Robotics
UBTECH Robotics
Diligent Robotics is recognized as a leader in hospital automation with its flagship robot, Moxi. Their platforms enable the continuous movement of medical supplies, lab samples, and PPE between departments. Moxi gathers data from the hospital environment to create a mapped view of operational flows. This allows nursing teams and floor managers to utilize the robot to balance task loads and reduce the physical exhaustion of staff. Diligent has deployed its software and hardware across multiple major U.S. health systems to support the modernization of clinical workflows.
Aethon, a division of ST Engineering, focuses on providing mobile robotic solutions for hospital logistics. Their TUG platform specializes in providing flexibility to the internal supply chain market. By using these tools, the company provides autonomous transport for medications, linens, and meals, improving the operational stability of large medical campuses. Aethon has established partnerships with hundreds of hospitals globally to develop automation programs that help customers meet operational efficiency goals and develop the infrastructure necessary for smart healthcare ecosystems.
SoftBank Robotics provides AI-driven service robots that orchestrate social interaction and logistical support in healthcare settings. Its software enables organizations to forecast service demand and optimize the movement of robotic fleets. In the context of nursing care, SoftBank’s platforms can coordinate with staff to participate in patient engagement and basic monitoring. The company participates in global healthcare modernization initiatives where advanced robotics support the integration of remote care and smarter, AI-native facility management.
| Report Metric | Details |
|---|---|
| Total Market Size in 2026 | USD 1.9 billion |
| Total Market Size in 2031 | USD 4.5 billion |
| Forecast Unit | Billion |
| Growth Rate | 17.5% |
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Segmentation | End-user, Population Split, Application, Geography |
| Geographical Segmentation | North America, South America, Europe, Middle East and Africa, Asia Pacific |
| Companies |
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