Don’t Wait for the Fallout: Building Human-Centred AI Collaboration
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January 23, 2026
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We are about to enter a time when AI is becoming a coworker rather than a knowledge base or supplementary tool. AI promises speed, deeper insights and new levels of efficiency for a lot of organisations.
But the scale is shifting. Those who harness AI most successfully are also the ones most likely to be exhausted, with a staggering 88% of high-AI-productivity users report symptoms of burnout and twice as likely to consider quitting compared with their peers.1
At the same time, many of these top performers report deeper disconnect, with: 67% trusting AI more than their colleague, and 64% say they have a better relationship with AI than with their teammates.
In plain terms, the human cost of productivity is mounting. The scales of work are tilting toward output and away from trust, connection and wellbeing. If organisations treat AI merely as an efficiency upgrade without redesigning how work is done, the consequences may be more than temporary fatigue.
The good news is that it is not too late to rebalance. Even companies who are only now beginning their AI rollout can act early to avoid the pitfalls that others are already facing. Implementation with the human in mind, not as an afterthought, will be the decisive factor in whether AI strengthens or strains an organisation in the years ahead.
The Hidden Costs of the Efficiency Revolution
AI has the power to accelerate workflows and automate complex tasks. Yet beneath the promise of progress lies a quiet accumulation of strain. Productivity gains often come with human trade-offs and without cultural and structural adaptation, those trade-offs can become long-term risks.
- Work intensification is one of the most visible effects. As AI extends what’s possible, it also raises expectations. Employees feel pressure to deliver more, faster and better, often without new boundaries or support systems.
- Social bonds within teams weaken. As collaboration shifts toward digital interfaces and AI tools, informal conversations and shared rituals fade. The sense of belonging that anchors teams begins to erode.
- Reductions in communication When “you can always ask AI,” spontaneous questions between colleagues decline. Learning becomes more isolated and critical thinking diminishes.
- Knowledge gaps around how AI truly works can erode psychological safety. Without understanding its logic and limits, employees may feel insecure about their own judgment, either over-relying on systems or rejecting them entirely. This uncertainty makes people less likely to speak up, ask questions or admit mistakes, all of which are core behaviors in a psychologically safe environment.
Each of these factors adds weight to one side of the scale. The benefits of productivity begin to be offset by burnout, disengagement and cultural decline. The balance tilts and over time, the organisation bears the cost.
Acting Early to Stay in Balance
Crucially, now is the moment to act, as many companies are still in early stages of AI deployment or are piloting use cases. This is a window of opportunity to design AI adoption responsibly from the start, before unhealthy patterns, tool overload or trust gaps set in. It is far easier to prevent imbalance than to restore it later.
The goal is not “man versus machine,” but human with machine, working in synergy and staying in equilibrium.
Five Levers for a Balanced Human - AI Collaboration
Achieving balance requires intention. From our work with clients across industries, we see five areas where organisations can act today to ensure the benefits of AI are not contrary to the wellbeing, clarity and engagement of their people.
Structures and Work Processes
Organisational structures and work processes need to be reimagined to clarify how humans and AI complement each other. Instead of automating for efficiency alone, companies should define clear roles and responsibilities in which technology supports, not replaces, human judgment. Co-working models, “human-in-the-Loop” setups and use-case matrices can help anchor this collaboration, ensuring that oversight and accountability remain human-led.
Team Culture and Collaboration
Equally important is team culture and collaboration. As AI becomes a member of the team, trust and belonging must evolve with it. Leaders can foster this by introducing rituals that normalise collaboration with digital tools — for example, peer-learning sessions where colleagues share practical use cases or onboarding formats that demystify AI. At the same time, it’s crucial to create intentional moments for human connection that reinforce a sense of team, even without AI’s presence. Activities that put colleagues back in focus, such as team retrospectives or informal check-ins, help maintain strong interpersonal bonds. Together, these practices build collective confidence.
Leadership and Direction
Leadership and direction act as the connective tissue between ambition and responsibility. Leaders shape the tone of AI transformation as they give clarity, unravel uncertainty and set boundaries for ethical and effective use. Leadership labs that use AI simulations, updated decision-making principles, and enablement toolkits can all help in guiding teams through change with confidence.
Wellbeing and Resilience
At the same time, wellbeing and resilience must not be overlooked. AI can alleviate workloads, but if implemented poorly, it risks increasing pressure and mental fatigue. Designing focus time around AI-assisted workflows, identifying “AI for relief” use cases and integrating micro-routines for mindful tech use are tangible ways to ensure that digital transformation supports, rather than drains, human energy.
Communication and Change Management
Communication and change management tie everything together. Every rollout is a story and how that story is told determines how it’s received. It’s not just about showcasing everyday AI use, it’s about clearly communicating the vision. What does human–machine interaction look like for us, and why is it valuable? Leaders should bring in advocates who model this behaviour and create spaces for open dialogue, including transparent discussion of potential risks and concrete solutions.
Each of these levers redistributes weight on the organisational scale, helping companies stabilise before the imbalance becomes visible in burnout rates or disengagement scores.
Restoring and Keeping the Balance
AI is reshaping work faster than most organisations can adapt, yet the future of this shift is not fixed. Companies that take deliberate, human-centred action now can shape how the use of AI feels to their employees, not just how it functions for them.
The most forward-looking organisations will not treat AI as a one-time rollout but as an ongoing redefinition of how we work and collaborate. When that happens, the scales can level again. On one side we have productivity, innovation and speed and on the other wellbeing, learning and meaning. Together, they create the true promise of AI-powered work – a workplace where productivity is sustainable and people are committed and engaged.
Footnotes:
1: “Upwork Research Reveals New Insights Into the AI-Human Work Dynamic,” Upwork (July 9, 2025)
Published
January 23, 2026
Key Contacts
Senior Managing Director