Last year, 11 robotic systems were recommended for use in specified surgical procedures on the NHS. Since then, there has been an increase in the number of robotic-assisted operations taking place at hospitals across the UK.
In many cases, these robotic systems have been developed to assist the surgeon by providing important information and guidance at critical moments during surgical procedures. They can detect the speed and manner of each movement, so if a surgical instrument starts to move too quickly or is getting close to a critical organ or blood vessel, the system can alert the surgeon in real time – for example, via visual overlays, haptic cues or audio prompts. As robotic systems become better at analysing image data in real time, monitoring progress and predicting risks, they are increasingly being used plan surgical approaches to optimise patient outcomes, whilst keeping the surgeon in control of clinical decisions.
Early generations of surgical robotics systems, such as Hugo or Da Vinci, whilst highly successful, were restricted in terms of their capabilities in providing contextual, real-time guidance beyond instrument control and visualisation. More recently, the enhancement of surgical robotic systems is progressing, through the use of AI-enabled imaging, sensing, and decision‑support functions – for example, by identifying and highlighting particular tissue types or organs in real time during surgery. In research settings, Vision-Language-Action (VLA) concepts are increasingly influencing the design of future systems – building on today’s technologies by linking what the system sees to procedural intent, so assistance can be adjusted and optimised to respond to the surgical procedure.
Crucially, however, robotic surgical systems are approved for specific surgical procedures only as surgeons’ ‘assistants’. Wholly automated robotic surgery, without a human surgeon present who has direct control of what is happening, is unlikely to be approved for use in UK hospitals anytime soon. This is mainly due to a high degree of public scepticism around entirely robotically controlled surgical procedures, which means patients would be unlikely to elect for such surgery, and because regulators and healthcare providers rightly expect clear evidence of safety, accountability and clinical benefit before changing established care models.
Instead, innovators of robotic systems for use in the operating theatre are focused on developing their capabilities further so they can provide intelligent, high-precision assistance in real time, and in more complex or demanding surgical situations. During high-risk soft-tissue surgery, such as neurosurgery, for example, advanced robotic systems can improve outcomes by guiding surgical approaches with precision, mitigating the risk of collateral damage to surrounding tissue. They can do this by analysing each surgical movement and recommending adjustments in real time if there is heightened risk or if a better outcome might be secured by taking a different approach, for instance, by highlighting proximity to vulnerable anatomy or flagging patterns or motion associated with avoidable complications. Integrated advanced diagnostic imaging systems provide useful context, guiding the surgeon to react in real time, in a way that is more likely to result in a positive patient outcome. By monitoring the patient’s vital signs in a more integrated way, such surgical assistants also allow appropriate action to be taken by the surgeon quickly and effectively where necessary.
Examples of patented innovation in this space often focus on improving intraoperative awareness and safety. For instance, there are methods for real‑time tissue classification using image data, automated identification of “no‑go” zones, and systems that fuse pre‑operative imaging with live intraoperative views to support navigation. Other patented concepts focus on detecting instrument‑tissue interaction (e.g. force/torque signatures) and using that information to provide safety prompts or stabilisation assistance.
The use case for robotic assistants is improving all the time. As well as becoming cheaper to manufacture, trial data indicates that the latest systems offer greater precision and result in better patient outcomes, compared to conventional open or laparoscopic surgery. There is reduced blood loss and patients typically benefit from faster recovery times. Recognising their usefulness, NHS England announced last year its intention to use robotic assistance in nine out of 10 keyhole surgeries by 2035.
Increased use of robotic assistants for a wider range of surgical procedures will require greater investment in training. Surgeons are highly skilled individuals, with a strong degree of aptitude, but are not trained routinely in the operation of AI or robotic systems. Several initiatives are currently underway across the UK to provide more specialist training, including the creation of the UK’s largest robotic training centre in Winnersh, near Reading, where surgeons are learning to effectively use the da Vinci Surgical System.
For innovators, the key to unlocking the commercial potential of robotic surgical assistants could lie in making them safer and easier to use, so that they can be adopted more widely and quickly. If current use examples can demonstrate their safety, efficacy and viability, this could persuade the National Institute for Health and Care Excellence (NICE) to issue positive guidance enabling NHS hospitals to routinely fund them in the future.
For innovators, commercial success is likely to hinge on making robotic surgical assistants not just effective, but deployable at scale – safe, repeatable and easy to integrate into operating‑theatre workflows. In the NHS, adoption turns on evidence of clinical benefit and cost‑effectiveness in practice, including impacts on theatre time, staffing, training burden and the risk of use error. If real‑world data shows improved outcomes without creating operational friction, this strengthens the case for NICE guidance and routine funding by local Trusts. Patented approaches that seek to address these issues include automated setup and calibration to reduce variability and avoid wasting theatre time, user‑interface improvements that lower surgeon cognitive load by prioritising context‑relevant prompts, and interpretable, auditable decision‑support displays that support clinical governance and post‑event review.
Optimising interoperability is another important area of focus for innovators of AI-powered surgical robotic systems. To become more mainstream, innovative software must function with a wide range of hardware, and vice versa. When drafting patent applications for enhanced AI-powered medical devices, such as diagnostic endoscopes for example, it is important to consider how they might be used in five or ten years’ time. For example, it might be appropriate to highlight their diagnostic potential for AI-assisted robotic lung or heart surgery in the future, or their ability to integrate with multiple imaging modalities, instrument sets, and data standards as operating theatres become more connected.
A further class of forward‑looking patented innovations focuses on modular system design. These typically include software architectures that decouple core control functions from analytical algorithms or sensing modules. This allows new capabilities to be added or upgraded without redesigning or recertifying the entire robotic system. Complementary innovations may address data handling, such as standardised pipelines that support controlled model updates, versioning, explainability and traceability across the device lifecycle. By enabling safe evolution of functionality after deployment, these approaches help hospitals to avoid proprietary lock‑in and reduce long‑term procurement risks.
With these factors in mind, when innovating in this area intellectual property (IP) strategy requires careful consideration. NICE has conditionally recommended the 11 robot-assisted surgical systems for specified indications in the NHS whilst further evidence is generated to clarify value and cost-effectiveness. We don’t yet know whether these technologies will progress to routine adoption and secure funding more widely, and there remains a considerable amount of market uncertainty in this area.
The best strategy when seeking commercial protection for software or hardware innovations directed to robot-assisted systems for use in surgical applications is to use broad terms of reference and keep options in terms of surgical applications open. There is no point in protecting specifically and only ‘for X’, if the NHS isn’t currently able to fund it or adoption might emerge first in a different clinical pathway. Innovators should consider questions such as ‘What other ways might this system be used?’ ‘What’s the inventive concept?’ and ‘How might a competitor want to use it?’ In many cases, this means anchoring the claims to the technical contribution, such as real‑time risk detection, sensor fusion, improved human‑machine interaction, or safety‑critical control logic, which are common to many clinical applications, rather than to one narrow surgical procedure.
Alternatively, depending on how ready the market is for the innovation in question, it may be appropriate to hold something back, so it could be patented at a later date if another opportunity arises or if the original intended use reaches a dead end. However, this approach requires careful management of confidentiality and disclosure risk, and it is also possible that a competitor could beat you to it by filing their innovation first, potentially locking you out.
The momentum for change is clear and advanced surgical robotics and AI-powered surgical assistants are already demonstrating their ability to collaborate with surgeons to improve patient outcomes in a wide range of surgical procedures. There is much that innovators can do now to enhance or advance their capabilities, whilst staying poised to capitalise on commercial opportunities when they arise in the future, particularly by designing for safety, usability, interoperability and a credible evidence pathway from the outset.
Samuel Bateman is a senior associate and patent attorney, and Chris Froud is a partner and patent attorney, at European IP firm, Withers & Rogers. Both specialise in advising innovative companies and developers in electronics and computing.
