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AI is set to transform the world of medical devices—but humans will remain as vital as ever. A new survey reveals medtech decision-makers’ attitudes to AI.

Medical devices are transforming healthcare delivery across the world, with wearables and implantables like heart rate monitors and smart pills enabling patients to live longer and more fulfilling lives.

Now, innovations like these are set to have an even greater impact, with the introduction of AI into devices and business processes. A new Cognizant and Microsoft study of 200 Europe and US-based medical technology decision-makers reveals that 91% are excited about what AI can do.

The promise of AI in medtech

Medtech is an industry fuelled by innovation, so it’s no surprise that so many are excited about the promise of AI. But this doesn’t mean decision-makers envisage a future where healthcare professionals are replaced by robots. Almost all (97%) agree that people will be as essential as ever, and will work as co-pilots with AI wherever it’s deployed in the value chain.

And although large language models (LLMs) are a hot topic, industry leaders don’t see AI playing a major role at the patient-clinician interface. Only 16% of respondents said it would help with the early diagnosis of patients, and just 6% believe it will improve surgery. Almost none (1%) think AI will be useful for delivery of services in areas like mental health.

Instead, they believe AI’s value lies in its ability to accelerate the product development lifecycle, enabling transformational technologies to be brought to market sooner. Areas that will benefit particularly from AI include post-market surveillance, safety and quality.

Improving effectiveness of post-market surveillance

Post-market surveillance is one of the most data- and labour-intensive phases of medical device development. Respondents were almost unanimous that AI will massively increase effectiveness in this phase, with 94% agreeing or strongly agreeing with the statement.

Benefits they cited included reducing the risk of human error, automating report generation and making the complaints process more efficient. One decision-maker noted that AI could use patient data and product usage patterns to create customised safety alerts—a useful feature as personalised and remote treatment becomes more common.

Compiling safety reports is a time-consuming aspect of post-market surveillance and one where decision-makers see valuable applications for AI, with one decision-maker pointing out that “AI can be used to generate effective and detailed reports regarding the safety concerns, potential risks and consumer response upon usage of the device”. Here, as elsewhere, AI will help to accelerate product launches as well as enhance safety for device users.

Accelerating compliance with safety regulations

Regulation is sometimes perceived as a barrier to life sciences innovation. However, the findings suggest regulations are well calibrated on the whole, providing the necessary guardrails for directed innovation. Only 17% of European respondents and 5% of US respondents said regulation “greatly hinders” innovation, with the higher European figure likely due to the need to comply with differing regulations in different countries.

Respondents believe AI can help to ease the compliance process, especially for highly-regulated devices like hip prostheses and pacemakers. Such devices promise enormous health benefits but must also meet stringent safety standards. AI can help by accelerating and widening the analysis of R&D and clinical trials data, enabling device manufacturers to understand and address safety issues earlier.

In fact, 82% of decision-makers said AI will make medical products safer due to its ability to analyse large amounts of data and stick to protocols, with one UK-based respondent noting that “AI can follow protocols and guidelines consistently, reducing the variability that can occur with human decision-making.”

Ensuring manufacturing quality

Some safety issues with medical devices may be due to manufacturing quality rather than inherent device design. Device makers need to implement strict quality control measures into manufacturing operations, and this is another area where AI holds great promise.

Overall, 92% of decision-makers were interested in using AI for quality control, including monitoring manufacturing processes to identify software defects (70% of respondents) and hardware defects (58% of respondents). One decision-maker noted that “by automating quality control processes through AI, we can ensure that every medical device meets stringent safety standards, minimizing the risk of defects or malfunctions.”

AI has a key role to play in quality control after production too. Nearly two-thirds (61%) said they were interested in using AI for predictive analytics—monitoring data from sensors embedded in medical devices to anticipate faults or breakdowns. “By integrating AI into quality control we can easily predict and solve any equipment-related problems,” said one decision-maker.

An upcoming battle for AI talent

While there’s clearly a huge appetite for integrating AI into devices and related business processes, several obstacles stand in the way.

One major barrier that emerged from the survey is a shortage of AI skills within the medical device industry. Almost all (92%) of respondents envisaged these skills being supplied by external specialists, rather than internal hiring or upskilling initiatives. When asked who could implement AI most effectively, 85% opted for an external partner over internal employees.

One reason for that may be the diversity of skills required to implement AI effectively, which includes data management expertise as well as AI expertise. Robust governance capabilities are also needed, to avoid biases that could harm patients, to ensure patient privacy, to maintain device and data security, and to keep up with new regulations like the European Union AI Act.

The road to success: a technology partner with medical domain expertise

The road to success is likely to involve close collaboration between device manufacturers and external AI specialists, with 71% saying AI expertise is now a sought-after capability in a technology partner. But that alone won’t be enough—86% of respondents said their technology partner would also need medical device domain expertise.

With developments on the horizon including smart implantables, software as a medical device (SaMD) and AI-powered imaging equipment, it’s no surprise that decision-makers are excited for the future. In the words of one respondent, finding a like-minded, appropriately-skilled partner will be essential to “developing tailored solutions that address unmet healthcare needs, leading to the development of more efficient and more effective medical devices.”

AI will help strike the balance between innovation and safety

Technology has already improved the lives of millions of patients, but our study shows it’s set to do much more. The really encouraging thing is that the introduction of AI into product development processes will help medtech companies to strike the crucial balance between rapid innovation and patient safety. This won’t just lead to safer and better products, but also promises to accelerate personalised medicine, creating a step-change in care and outcomes for providers and patients. 

Mahendra Das

Client Manager and Medtech Lead UK & Ireland, Cognizant

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Rohit Alimchandani

Head of Life Sciences, UK&I, Cognizant

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