✨ Introduction
Artificial intelligence is reshaping MedTech faster than most people imagined. It’s reshaping how medical devices are developed, approved and managed. Yet whilst the potential is huge, many companies are discovering that making AI work in practice is far from easy.
In this episode of Career Diaries by elemed, Elena speaks with Michelle Wu, co-founder and CEO of NyquistAI, one of the top 100 women in AI globally. With experience spanning Boston Consulting Group, Novartis and Silicon Valley, Michelle shares what’s really happening with AI in regulatory affairs and how leaders can navigate the changes it’s driving across the industry.
Why AI isn’t working in MedTech (yet)
MedTech organisations are not failing with AI because of the technology itself, but because of the environment around it. Around 86% of executives struggle with AI adoption for three main reasons:
- a lack of robust data infrastructure
- underestimating the time and investment required for change management
- organisational structures that do not support long-term adoption
These challenges create a clear gap between ambition and execution, with companies announcing bold AI initiatives yet struggling to translate them into measurable impact. Ultimately, the issue is as much about mindset and culture as it is about tools or technical expertise.
From hype to reality
Over the past five years, MedTech and life sciences have moved through three distinct phases of AI adoption.
2020-2022: period of excitement and experimentation
- Companies were willing to test ideas, take risks and explore the possibilities of AI.
2022-2024: partnerships with major technology providers became popular, but many of these collaborations failed to deliver meaningful returns.
- Initial enthusiasm often gave way to frustration as organisations realised that external partnerships alone could not solve deeper structural issues.
Now, 2025: the industry is entering a phase of maturity.
- The hype has started to fade, replaced by a more balanced understanding of where AI adds genuine value and where human expertise remains essential. Companies are becoming more selective, prioritising projects that are strategically aligned and operationally sustainable.
Where AI adds real value in regulatory affairs
AI is proving to be a powerful enabler in specific areas of regulatory affairs. It can identify insights from large volumes of data, improve literature and document review, and help teams analyse information more efficiently. These applications save time and allow professionals to focus on more strategic work.
However, AI still has clear limitations. It cannot write a complete submission, make strategic decisions or replace professional judgement. Its greatest strength lies in enhancing human capability, not replacing it. For regulatory teams, success depends on understanding which tasks benefit from automation and which require experience, interpretation and context.
Avoiding AI overload
With new tools emerging almost daily, many leaders are now experiencing “AI fatigue”. The constant stream of products, pitches and platforms can make it difficult to know where to start.
The best place to begin is with clarity. Before launching any AI project, organisations should ensure they have the right training data and a clear definition of what success looks like. Without these foundations, projects often become expensive experiments that fail to deliver value.
Managing expectations is also essential. Not every process needs automation, and not every AI solution will lead to measurable improvements. The goal should be to build understanding and capability step by step, rather than chasing the latest trend.
The future of regulatory affairs
AI will not replace regulatory work, but it will change its shape. Routine tasks and data-heavy activities are likely to become increasingly automated, creating space for professionals to focus on higher-value work that requires critical thinking, creativity and collaboration.
Over time, regulatory affairs is expected to move closer to the core of business decision-making. Instead of acting as the final checkpoint, regulatory professionals will become strategic partners involved earlier in development, helping to guide innovation and ensure compliance from the start.
This shift will also redefine the skills that matter most. The ability to interpret results, review AI outputs and work effectively alongside technology will become essential for the next generation of professionals.
Practical actions for RA and QA leaders
For regulatory and quality leaders, effective AI adoption starts with practical, achievable steps.
Start small. Choose one focused use case, such as regulatory intelligence or document classification, and learn from the experience.
Build confidence gradually. Share lessons learned, encourage experimentation and create momentum through small wins.
Invest in people. Develop AI literacy, encourage curiosity and ensure teams understand both the potential and limitations of the tools they use.
These simple actions can create lasting change when applied consistently. AI transformation is not a single project but an ongoing process of learning and improvement.
Looking ahead
AI is already changing the day-to-day reality of regulatory work. It’s also influencing how organisations think about their people, their processes and the way they operate. For those willing to experiment and adapt, it offers a genuine opportunity to deliver better outcomes with fewer resources.
The future of regulatory affairs will depend on professionals who can combine human expertise with technological insight. AI may not replace regulatory professionals, but those who know how to use it effectively will shape the next chapter of the industry.
For anyone looking to understand the real impact of AI on regulatory affairs and how to futureproof their skills, this episode of Career Diaries by elemed is well worth a listen.
