Robotics and healthcare: what does the future hold?

Robots have been a part of human history (and our collective imagination) since Ancient Greece. In Book 18 of the Iliad, Hephaestus the god of all mechanical arts was assisted by two moving female statues made from gold.

Robots also occupy a prominent place in a utopian vision of how society can be bettered through the use of more efficient mechanical versions of ourselves. As technology has advanced, the prospect that robots could carry out tasks traditionally done by humans has become less of a fantasy and more of a reality.

In healthcare specifically, the use of medical robots and the integration of artificial intelligence has accelerated rapidly in recent years, extending beyond surgical arms to include rehabilitation, diagnostics, and patient care automation.

The demand for robotics in the healthcare industry

The future of robotics in healthcare will be driven by technological advances in AI and robotics, as well as expanding clinical demands.

An aging global population, coupled with rising chronic disease prevalence and workforce shortage,s has intensified healthcare demands, reinforcing the need for automation in routine and complex tasks.

In this capacity, medical robots can support caregivers and augment healthcare workers in tasks they struggle to find time to do, particularly in environments with high patient volumes or staffing gaps. These systems help free clinical staff to focus on hands-on care and critical decision-making

Extending care beyond physical walls with telepresence robots

Telepresence robots have transitioned from early experimental units to viable solutions that enhance remote care delivery. These internet-connected mobile units allow clinicians to interact face-to-face with patients in remote or underserved locations without being physically present.

These systems help bridge healthcare access gaps and support ongoing monitoring, chronic disease check-ins, and emergency triage. Market analysts expect the telepresence robots segment to grow significantly, with projections indicating expansion to more than $320 million by 2032.

While early versions require direct clinician control, future iterations enhanced by AI could autonomously conduct preliminary evaluations, escalate care alerts, or support clinical workflows with reduced oversight.

Surgical robots and AI

A 2025 analysis of clinical studies found that AI-enhanced robotic surgical systems demonstrated meaningful clinical benefits, including shorter operative times, lower complication rates, and measurable gains in surgical precision, compared with traditional manual procedures.

Advancements include federated learning frameworks that improve robotic surgical performance while protecting patient privacy, as well as evolving platforms that adapt to intraoperative conditions in real time.

Across healthcare systems globally, there is growing investment in surgical robotics infrastructure.

In the UK, for example, the government's 10-year plans for the NHS now prioritize expanding robot-assisted procedures across specialties such as urology, orthopaedics, and ENT surgery. The stated goal is to significantly increase the share of procedures supported by robotics over the next decade, though capital costs and workforce training remain challenges.

Patient assistance, rehabilitation, and novel robotics

Robotics is no longer limited to clinical settings. Robots that support rehabilitation, promote patient mobility, and assist in daily activities (particularly for elderly or disabled patients) are entering broader markets:

• Hospitals and long-term care facilities deploy autonomous systems for medication delivery, vital signs monitoring, and safe patient transfers to improve care quality and reduce clinician burden.
• Interactive robots designed to engage with patients, respond to emotional cues, and contribute to wellbeing are an emerging area of AI and robotics focused on human-centered outcomes and workforce experience.
• Micro and nano-robotics (still largely in research phases) are being explored for direct in-body interventions, such as targeted drug delivery or infection clearance, with early animal studies showing promising precision and minimal tissue disruption.

Challenges and considerations

Ethical concerns like data privacy, algorithmic bias, and the responsible interplay of AI decision support with clinician judgment need to be addressed through governance, transparent design, and adherence to clinical standards.

Workforce-readiness is also a factor; Interoperability is rightly at the center of most integration projects, and as with any other tech, healthcare professionals will need training to collaborate effectively with robotic systems. As such, institutions must invest in infrastructure, support, and post-deployment evaluation to ensure safety and effectiveness.

As is the case with AI, cultural acceptance and patient trust are also critical to long-term adoption.

Final thoughts

Medical robots and the broader field of robotics in healthcare are becoming integral components of modern care delivery.

Organizations planning digital transformation initiatives should account for integration with robotic platforms, AI decision support, and EHR systems that enhance interoperability and secure workflows.

When considering these investments, prioritize:

• Technologies with validated clinical outcomes.
• Systems that integrate securely with existing health data infrastructure.
• Change management that includes clinician training and patient communication.