The story below is an illustrative composite, bringing together patterns increasingly visible in organisations navigating rapid AI-enabled change.
Let me tell you the story of a fast-growing technology company that became known for doing what many organisations were only beginning to imagine.
They did not simply experiment with artificial intelligence. They embedded it across the business. Customer support became increasingly automated. Data analysis was almost instantaneous. Processes that once took days could be completed in minutes.
On paper, they were winning. Costs were falling. Productivity was rising. Growth was accelerating.
But something quieter was happening beneath the surface.
The energy in meetings began to dip. Brainstorming became more transactional. The creative spark that had once made the company distinctive started to disappear.
Then came the resignations. Several highly valued people left in quick succession. They were not simply moving for better titles or higher salaries. What they described was a loss of meaning: a growing uncertainty about where human contribution still mattered.
The leadership team realised they had become very good at making work faster, but had paid far less attention to making it meaningful.
Discovering the hidden story
The answer was not in the performance dashboards or financial statements alone. It was in the experience of the people doing the work.
They began looking more carefully at the conditions that support sustainable human performance: purpose, connection, psychological safety, meaning and the experience of being able to contribute.
What emerged was uncomfortable. People were becoming less willing to speak up. Some roles had been broken into increasingly automated fragments. Employees could see efficiency improving while becoming less certain about their own relevance to the system.
The technology was doing what it had been designed to do. The question was whether the organisation had redesigned work with equal care for the humans within it.
A people-first reset
The leadership team made a deliberate choice: not to step away from AI, but to rethink the relationship between technology, work and people.
Wellbeing became part of how work was designed rather than an employee benefit sitting alongside it. The organisation began to:
- embed wellbeing into operational routines and leadership conversations;
- develop internal champions who could help teams surface emerging risks and opportunities;
- equip people leaders to lead with empathy, judgement and clarity as well as efficiency; and
- make the human consequences of work design part of leadership accountability.
The underlying principle was simple:
Human centricity + accountability = performance that can be sustained.
Culture was no longer treated as an initiative. It became something expressed through everyday choices about roles, priorities, leadership and decision-making.
Reigniting the human contribution
Roles were re-examined. AI continued to take on repetitive and process-heavy tasks, while greater attention was given to the work that depends on human judgement, creativity, relationships and strategic thinking.
Teams were encouraged to challenge assumptions again. It became safer to ask: What are we doing, why are we doing it, and where does human judgement add value?
Leadership also began to shift. Rather than seeing their role primarily as directing work, leaders increasingly had to create the conditions in which people could make sense of change, contribute intelligently and adapt together.
Over time, the organisation began to see stronger psychological safety, more stable retention and a return of the energy that had been disappearing from collaborative work.
Looking back - and forward
The important change was not a new tool or a single intervention. It was the organisation's willingness to look honestly at what its pursuit of efficiency was producing.
The people supporting the work did not “fix” the company. They helped the leadership team see the system more clearly. Once that happened, the organisation could make different choices about how technology, people and performance fitted together.
That is often the real work: helping an organisation understand what is happening beneath the visible results, so that it can act before short-term gains become long-term organisational costs.
Why this matters
Wellbeing is still too often treated as something separate from the design and management of work. Yet the conditions in which people work directly influence mental health, engagement, judgement, collaboration and performance.
The World Health Organization's guidance on mental health at work explicitly includes organisational interventions and manager capability, reinforcing the importance of addressing the conditions of work rather than relying only on individual wellbeing initiatives.
In Europe, sustainability reporting frameworks have also brought workforce topics such as working conditions, health and safety, skills and work-life balance more firmly into organisational accountability where they are material.
AI makes this conversation more urgent, not less. Technology can scale analysis, automate processes and accelerate decisions. But organisations still depend on humans to exercise judgement, create meaning, build trust, lead through ambiguity and care about consequences.
The organisations most likely to thrive will not simply be those that automate the most. They will be those that become more deliberate about where human contribution matters - and design work accordingly.
So perhaps the more useful question is not whether your organisation is using enough AI. It is whether you are building an organisation in which humans can still do their best work.
Dr Anna-Rosa le Roux is an organisational psychologist and strategic organisational advisor. Through WorkLife Digital, she works with leaders on organisational diagnosis, leadership, culture and sustainable performance.
WHO: Guidelines on mental health at work →