As life sciences accelerates its use of AI systems that can recommend, prioritise and act, the biggest barrier isn’t technology. It’s culture.
Picture systems that can act faster than your people, in organisations that don’t yet fully trust them to act at all.
That’s where things get interesting and messy.
Culture doesn’t shift because leaders announce it will. It shifts when behaviour changes. What people actually do, especially under pressure, matters far more than what organisations say they value.
As AI evolves from passive tools into systems that can initiate recommendations and actions on their own, the cultural implications shift dramatically. What was once exploratory is becoming operational. Investment is increasing, pilots are scaling, and AI is being embedded into everyday activity.
“Meet your digital co-worker” just became a reality.
The life sciences industry is chasing $100 billion a year in new AI-led growth opportunities. MIT Technology Review Insights writes that “Agentic AI promises the next phase of transformation – from AI tool to AI coworker.” Their study found that 73 percent of pharma leaders are planning, piloting or deploying agentic AI initiatives, with adoption set to surge in the next 12 to 18 months.
The scale of this shift is unlike anything before, yet the softer, slower side of transformation isn’t keeping pace. Too many organisations are getting AI ready while quietly sidestepping the harder work of becoming culture ready.
If teams aren’t empowered, and trust, accountability and confidence in judgement are already fragile, introducing AI doesn’t create capability. It creates displacement.
Decisions quietly shift away from humans. Judgement is deferred rather than exercised. Accountability blurs, not because people don’t care, but because it’s no longer clear who is meant to decide. “The system flagged it” becomes a shield rather than an explanation.
In life sciences, where progress depends on informed challenge, human judgement, and the confidence to pause when something doesn’t feel right, that shift comes at a cost. Patient safety, ethics, and regulatory responsibility don’t disappear because a system can act faster. If anything, the cost of leaving assumptions unchallenged increases business risk.
Before scaling AI, leaders need to get clear on things that are too often left vague. Who is expected to exercise judgement when the stakes are high? Who has the authority to pause or challenge a recommendation when data and experience don’t align? And what actually happens when someone pushes back – on a system, or on a senior leader?
This isn’t technical work. It’s human work. It’s how leaders behave under pressure, how teams handle disagreement, and whether accountability is genuinely owned – or quietly avoided. Without that clarity, AI will certainly accelerate activity, but it won’t move the organisation forward.
Here’s the uncomfortable truth. AI won’t transform your culture. It will simply mirror and magnify it.
In high-trust environments, AI sharpens thinking and accelerates learning. In low-trust ones, it hardens dependency, erodes confidence, and creates more risk.
The real question isn’t whether organisations are ready for AI. It’s whether leadership is ready to confront what’s been avoided for years – trust, decision rights, and who is truly accountable when it matters most.
AI doesn’t disrupt culture. It exposes it.
1. Make psychological safety a strategic imperative in AI assisted work.
Leaders need to model curiosity and vulnerability through open demonstrations of these behaviours to cultivate psychological safety and a Growth Mindset culture. They also need to first link arms with the other leaders in the system, department or business unit, and develop their collective vision and narrative founded on trust and cohesion on a personal and emotional level. This needs to be addressed by design.
2. Codify your team’s behaviours under pressure.
Be explicit about expected behaviours when data, timelines and intuition collide. Agree in advance when teams should pause, who must be convened, how assumptions are pressure-tested, and how rationale is documented – so judgement doesn’t default to hierarchy or deference to the system.
3. Measure culture readiness alongside AI readiness.
Alongside AI capability, track whether teams are actually able to challenge, decide and escalate effectively. Look at decision clarity, frequency of constructive challenge, quality of escalation, and post-decision learning – especially when outcomes are uncertain or uncomfortable.
In the end, the question isn’t what AI can do for your organisation’s growth. It’s whether your culture can match its speed with equal depth of trust and accountability, unlocking the huge potential AI is designed to deliver and truly turbocharging organisational progress.
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Specialists in the human side of change, we partner with leading life science organisations to deliver deep change and cultural transformation.