How AI Is Changing Leadership in Regulated Industries
A note from me (Adam):
A few months ago, I wrote an article on leadership called Overcoming Inertia and Maintaining Momentum: Quality-Regulatory Strategy and Leadership.
You can find the article here - https://theotherconsultants.substack.com/p/overcoming-inertia-and-maintaining
Fast forward a few weeks after this, and I decided to reach out to someone who’s day to day is maintaining momentum, to give some further insight into this challenge.
Introducing, Michael Konings - Senior Director - Global Head of Regulatory Affairs - IGT Systems for Philips.
Michael and I have known each other for a while now, and whilst we are both at different sides of the spectrum in terms of our day to day roles (Michael being involved more in Leadership, and myself entrenched in technical details with no escape it seems), we both are extremely aligned in that maintaining momentum can be challenging in an every moving landscape.
Furthermore, we are both extremely interested in the role that Artificial Intelligence can play within gaining and maintaining momentum. Michael has kindly agreed to write a small piece for our network on his take.
We have attempted this piece to go out from the usual of “use AI to automate and make things faster, and as a result reduce the headcount”. Enjoy! And thanks Michael for taking the time.
1. The Shift from Information Control to Intelligence Orchestration
For many years leadership was strongly connected to access to information. Leaders often had more data, more overview, and therefore also more control over decision making. With the rise of AI this model is changing very quickly. Information itself is becoming available everywhere and AI can process huge amounts of data much faster than humans can do manually.
This changes the role of leadership. The value is no longer only in collecting information, but much more in connecting insights, setting priorities, and making sure organizations use intelligence in the right way. Leaders increasingly need to orchestrate how human expertise and AI-generated insights work together.
In MedTech and other regulated industries this becomes even more important. AI can support analysis, identify trends, or accelerate documentation activities, but organizations still need human oversight to ensure quality, patient safety, and regulatory compliance. Leadership therefore becomes more focused on coordination, alignment, and responsible decision making instead of pure control over information flows.
2. Why Leadership Must Evolve in the Age of AI
AI is not only introducing new technologies into organizations. It is also changing how organizations work, collaborate, and take decisions. Many repetitive or administrative activities can already be supported or partially automated by AI systems. This means employees and leaders will spend less time on transactional work and more time on AI outcome validation, strategic and cross-functional activities.
Because of this, leadership models that were successful in the past may not be sufficient anymore. Organizations need leaders that are comfortable working in environments with continuous technological changes, faster decision cycles, and increasing complexity.
At the same time AI also creates new risks. Fast output does not automatically mean correct output. Leaders therefore need to understand both the possibilities and the limitations of AI-supported decision making. Especially in healthcare and MedTech, speed can never replace responsibility.
The future leader must therefore combine technology understanding with human capabilities such as judgment, communication, ethical thinking, and the ability to align different stakeholders around difficult decisions.
3. Human Judgment as the New Strategic Differentiator
As AI systems become more capable in generating analysis, summaries, predictions, and recommendations, the differentiating factor for organizations will increase toward human judgment. AI may support decisions, but it cannot fully understand organizational context, long-term consequences, or societal impact in the same way humans can.
This becomes highly visible in regulated environments where decisions often include trade-offs between innovation, compliance, patient safety, business priorities, and ethics. These are areas where human judgment remains essential.
Organizations that only focus on automation may improve short-term efficiency, but organizations that combine AI capabilities with strong human decision making will create more sustainable value. The role of leadership is therefore not only to implement AI, but also to ensure that critical thinking and accountability remain central in the organization.
In this environment, experience, interdisciplinary thinking, and the ability to challenge AI-generated conclusions become increasingly important leadership capabilities.
4. Leading in a World Where AI Accelerates but Humans Remain Accountable
One of the biggest changes AI introduces is speed. Activities that previously required days or weeks can sometimes now be performed within hours or minutes. This creates opportunities to accelerate innovation, improve responsiveness, and reduce administrative burden.
However, accountability does not move at the same speed as automation. In healthcare, regulatory, and quality environments, organizations and individuals remain responsible for the final outcome regardless of how much AI was involved in the process.
This creates a new leadership challenge. Leaders must stimulate innovation and efficiency while at the same time ensuring appropriate governance and oversight. AI should support humans, not replace organizational accountability structures.
For this reason organizations need clear frameworks on where AI can be used, where human review remains mandatory, and how responsibilities are documented. Leaders play an important role in creating trust around these processes. Without trust, even strong AI capabilities will not be successfully adopted inside organizations.
5. Building Organizations Where Humans and AI Augment Each Other
The future organization is likely not fully human-driven and also not fully AI-driven. The strongest organizations will probably be those that successfully combine the strengths of both.
AI is very strong in scaling information processing, identifying patterns, supporting documentation, and accelerating repetitive activities. Humans remain stronger in empathy, ethical reasoning, contextual understanding, relationship management, and complex judgment.
Organizations therefore need to redesign workflows around this collaboration model. Instead of asking how AI can replace humans, the better question is how AI can increase the effectiveness of people and allow teams to focus more on higher value activities.
This also requires changes in organizational culture. Employees should not experience AI as a threat only, but also as a tool that can support their work and development. Leaders have an important responsibility in guiding this transition carefully and realistically.
Successful implementation will depend not only on technology investments, but also on transparency, communication, training, and organizational trust.
6. The New Role of Leaders in Regulated Innovation
Innovation in regulated industries has always required balancing speed with control. With AI this balance becomes even more sensitive because technological development is moving faster than many existing regulatory frameworks.
Leaders therefore need to operate in an environment where not all rules are fully established yet. This requires organizations to become more proactive in engaging with regulators, standardization bodies, and external stakeholders.
In MedTech especially, leadership is increasingly connected to shaping responsible innovation instead of only responding to regulations after they are published. Organizations that actively participate in these discussions may help define future expectations instead of only reacting to them later.
This also means leaders need stronger cross-functional collaboration between Regulatory Affairs, Quality, Clinical, R&D, Software, Data Science, and Commercial functions. AI-related innovation can no longer be managed effectively inside isolated organizational silos.
The leadership challenge is therefore not only technological adoption, but also building governance models that allow innovation and compliance to evolve together.
7. Developing the Next Generation of AI-Enabled Leaders
Future leadership development will likely look different from traditional leadership models. Technical expertise alone will not be enough, but purely managerial capabilities may also become insufficient.
Organizations will need leaders who understand technology sufficiently to ask the right questions, while also being able to lead people through uncertainty and continuous transformation.
This means future leadership programs should include stronger focus on AI literacy, cross-functional collaboration, ethics, change management, and strategic thinking. Leaders do not need to become AI engineers, but they do need enough understanding to make informed decisions and challenge assumptions when needed.
Another important aspect is learning agility. Because AI technologies evolve rapidly, organizations cannot rely only on static expertise models anymore. Continuous learning becomes part of leadership itself.
Mentorship and knowledge transfer will also remain critical. Experienced leaders bring organizational context and judgment that AI systems cannot replicate. Combining this experience with newer digital capabilities from younger generations may create stronger and more balanced leadership teams.
Conclusion: Leadership Adapting as the Human Operating System Around AI
AI will become deeply integrated into many organizational activities during the coming years. It will influence decision making, operational processes, product development, customer interactions, and regulatory activities.
But despite these changes, organizations will still depend on human leadership to create alignment, accountability, trust, and direction. AI can generate information and recommendations, but it cannot fully replace human responsibility or organizational judgment.
Because of this, leadership may actually become more important in highly AI-enabled organizations, not less. The role of leadership shifts from controlling activities toward guiding systems, connecting people, managing risks, and ensuring technology is used responsibly.
Especially in regulated industries such as MedTech, the combination of innovation, compliance, ethics, and patient safety requires strong human oversight. Organizations that succeed will likely not be those with only the most advanced AI, but those that best combine AI capabilities with responsible and adaptive leadership.
In this sense leadership becomes the human operating system around AI. As important as it is for leaders to understand the capability of AI, it is equally as important for them to understand its limitations, while also understanding the capability of the humans within their teams.