Life sciences exist to do something extraordinary. Their applied solutions seek to understand biology and improve health and the quality of life for humans, animals, and plants. That is not a small mission; at its core, it is deeply human. It is the kind of mission that draws in people who care passionately, who work with precision, who spend decades over the course of long careers because the work is interesting, important, and complex. This makes the current state of HCP burnout all the more worth examining honestly. The conversation about healthcare professional burnout has been going on for years, and what I have learned firsthand is that the solution keeps returning to the same destination: the individual. More resilience training. Another employee assistance program line. A new mindfulness pilot, free yoga classes. The implicit message, dressed in the language of support, is that the person carrying the load simply needs to carry it better.
Why the current approach falls short
A 2023 national study of more than 43,000 healthcare workers across 206 organizations found an overall burnout rate of nearly fifty percent. Not a fringe population. Not one specialty. Half the workforce. Burnout in healthcare is not a personal failing that happens to be widespread. It is a signal, information, and it registers in the body. The research shows us that sustained occupational stress produces measurable dysfunction in the autonomic nervous system, disrupts the hormonal systems that regulate cortisol and sleep, and generates systemic inflammation. Over time, the physiological consequences include cardiovascular disease and measurable changes to brain structure and function, the kind of changes chronic stress produces in any system pushed past its capacity for too long. This is not a metaphor or a cliche. The body keeps the score.
Resilience training, at its best, helps individuals absorb what they cannot change. That matters, but it is not sufficient. Asking someone to become more resilient inside a system that has not changed is a way of absorbing the cost of the system dysfunction without addressing it. Year after year, the research on burnout, moral injury, and workforce attrition in healthcare says the same thing: the conditions are the cause. The
individual is not. And when the conditions do not change, the cost eventually reaches the patient: in the errors that accumulate when judgment is depleted, in the care that does not happen when the person who would have given it has left the field.
Life sciences sit at an unusual intersection. Clinical care, scientific development, regulatory decision-making, and commercial operations all converge here. The sector’s reason for existing, to understand biology and improve quality of life, is inseparable from the question of what happens to the humans doing that work. Staying on the sidelines of this conversation is not a neutral choice. It is an agreement.
Same flower, different soil
I have had two distinct experiences over my 30-year career in life sciences; we will call one of the experiences quietly extractive. It was not dramatic. It was slower than that. It was the accumulated experience of reading the room and deciding, again, that this was not the moment to push back and stop performing. That the risk was too high, the players too invested in the go-along-get-along, the culture too fixed to absorb a different perspective, and frankly, what would it matter? This is the way we do things here. I was not alone in this. I was one of a multitude of people making the same calculation every week, in organizations across the industry.
The second experience was more generative; I had a seventeen-year tenure at one organization, returning three separate times, because the work and the people were worth coming back to. This system, although not perfect, had a higher threshold for its workforce to challenge the status quo and, in many ways, showed me the meaning of generative leadership and generative work. To be candid, to truly impact change in
highly mechanized systems takes courage, a deep well of conviction, and enough passion to bring your vision to those with influence. It also takes the ability to hold paradox, find harmony, and attempt to create a fresh order within systems that are dysfunctional.
The organizations that extract human contribution without inquiry or investment in the conditions that make it possible for humans to thrive are not just asking too much. They are losing the thing they need most: calibrated, engaged, purposeful human judgment at the center of every good decision.
Generative and extractive leadership
There are two postures available to any leader at any moment. The first is extractive: it draws from the people around it, uses what it needs, and replaces resources only when the deficit becomes a crisis. The second is generative: it creates conditions in which the people doing the work can think clearly, contribute fully, are fully aligned with their purpose, and can sustain that over time. Most leaders are capable of both. Most
organizational cultures reward one and rarely acknowledge the other. The incentive structure is ordered toward the former.
A generative leader notices when a team member is approaching their limit before the limit is reached. They design decision-making processes that distribute cognitive load rather than concentrate it. They hold space for disagreement and debate because it is important to till the soil of ideas, because the quality of our decisions depends on holding more than one perspective.
The practical difference is not soft. Generative leadership cultures retain people. They make better decisions under pressure. They catch the errors that extractive cultures let through because no one felt safe to make the call and have a challenging conversation.
The AI inflection point
Life sciences are moving toward integrating artificial intelligence at speed, and the pace of adoption is outrunning the pace of the conversations that need to happen alongside it. The question of how AI changes clinical judgment, workforce design, and organizational accountability is on the table right now, whether any given organization is ready to engage with it.
There are several roads to take when met with a disrupting factor such as AI; for the purposes of this article, let us look at two options. One is to use AI to accelerate the extraction: run leaner, faster, and with fewer human checkpoints. Some workflows will do well, and others will not. The ones that do not thrive will bury employees under mountains of data that cause overwhelm and decision anxiety, and only later will organizations notice that discernment and confidence have eroded and human judgment has shifted to over-reliance on AI output.
The other is to use AI to amplify the distinctly human capabilities that bring genuine value to an organization and purpose to employees. Use the model to amplify emotional intelligence to hold a patient in genuine presence, the moral agency to flag what the data is missing, the somatic wisdom of a seasoned clinician reading a situation before the numbers confirm it. This means expertise is still needed. Yes, knowledge is easier to access, but translating that knowledge into meaningful, innovative work is deeply human.
The choice that defines the next decade in life sciences is not which AI tools to deploy. It is whether the humans inside these organizations will have access to the training they themselves need to meet this moment, bringing the inner human skills of discernment, judgment, and constructive skepticism to the table at the same pace as the technology, so that AI serves the work rather than replacing the judgment the work requires.
What strong leadership looks like, and it is measurable
Five constructs matter in this moment. The first is calibration: how accurately leaders understand their own capabilities, limits, and blind spots, AI has the tendency to blur these lines. The second is orientation toward AI, specifically whether leaders can hold a position of constructive skepticism, neither resisting the technology reflexively nor deferring to it uncritically. The third is emotional regulation under the kind of sustained load that healthcare environments generate consistently. The fourth is moral agency: how actively a leader exercises independent ethical judgment when organizational incentives and patient interests diverge. The fifth is purpose alignment, the clarity of connection between daily work and their personal purpose and mission.
These skills are the bedrock of generative leadership when working with AI. They are measurable, developable, and present in the daily behavior of every leader in every organization. When they are strong, the culture can navigate pressure without losing people if they can point to these skills and communicate and demonstrate them effectively. When they are weak, or the answer is simply use more AI and get on board, the system transfers the cost to the workforce, and eventually to the patient.
What can an individual do to create change
None of what follows changes the system by itself. But individual leaders asking better questions is how systemic change actually starts.
No single leader changes the architecture of a broken system alone. It takes a coalition, a group of passionate people to bring transformative ideas into action. There are actions each of us can take in the near term that matter. When working with AI, take note of your personal decision patterns and those of your team. Ask where cognitive load is concentrating, is the pace and amount of data overwhelming or job-enhancing, do they feel pressure to meet the speed of compute with their cognitive abilities? When bottlenecks are discussed, take notice in your team: if there is resignation or apathy, this may be a signal of burnout. Discuss a path forward. Design at least one process this quarter to refine a system that empowers your team and distributes that load more deliberately.
Engage the AI question as a leadership question, not a technology question. The decisions about where human judgment is required and where AI can serve it are leadership decisions. They should be made by people who understand both the capability and the cost.
Give your people something worth staying for. Not just the yoga class. The real thing: the sense that their expertise is honored, that their voice has a place, that their agency is put to good use, and that the work they are doing connects to something that deeply matters.
Not every leader needs to be a change agent, but it does require enough of us to ask quality questions that lead to innovative solutions and systemic change.
The system is speaking. The question is whether the organizations with the most to offer, and the most at stake, are listening.
Author Bio
Gretchen Terry-Leonard is Co-founder and Chief Strategy and Impact Officer of the Center for Deeply Human Leadership and the author of Your Second Prime.
