Earlier this month Meta announced that it is building an AI version of its CEO Mark Zuckerberg. His digital twin is being trained on his tone, mannerisms and thinking on company strategy, with the aim of interacting with employees and helping them feel more connected to the CEO.
Shortly after, reports emerged that Meta is planning to cut some 10 percent of its workforce.
The juxtaposition - automating connection while reducing headcount - is hard to ignore.
But Meta is not alone. Gartner has identified digital “twins” as a major trend for 2026. The CEOs of Klarna and Zoom have been using avatars to communicate with staff since last year and UBS is deploying AI versions of its analysts.
Organisations are capturing expertise, codifying it and scaling it, all in the name of productivity, efficiency, knowledge retention.
And all the while employees increasingly ask themselves: where does this leave me?
The people dimension of AI adoption is as critical as any question about what AI can do, but one that feels relatively overlooked.
Research from Deloitte shows that most companies are focusing on implementation rather than capability. The majority concentrate training on basic AI awareness rather than rethinking roles, workflows or career paths. Only a minority of employees have received any meaningful training.
A separate Deloitte study found that organisations taking a tech-focused approach are 1.6 times more likely to fail to realise returns on their AI investments compared to those taking a human-centric approach.
This matters because the work that remains with humans is becoming more demanding rather than simpler.
Using AI effectively is not just about generating outputs. As routine tasks are automated, the job people are left with is focused on judgment, exception handling and oversight. That means knowing when outputs are wrong, incomplete or biased, recognising what has been missed, and making decisions in situations the model cannot fully understand.
That requires a different level of capability: critical thinking, domain expertise, and the ability to question rather than accept.
To be effective, organisations need that capability broadly. Yet data from a joint FT–Focaldata study shows the opposite and AI expertise is being concentrated at the top. Higher earners and more experienced workers are adopting AI tools far more quickly than others. More than 60% of top earners report using AI daily, compared with a small minority of lower earners. There is also a persistent gender gap in usage.
This uneven approach to AI adoption reinforces inequality at a time when AI's limitations - its blind spots and embedded bias - make diverse human judgment more critical, not less.
Organisations are adopting AI at scale, but adaptation at pace is lacking.
This is something that requires deliberate and sustained effort. Rethinking roles and redesigning workflows is only part of that.
Building the judgment, self-awareness and critical thinking needed to operate in more complex environments is equally critical, because competitive advantage will come from how effectively people can work where AI reaches its limits.
If adaptation doesn't match adoption, the risk is not just uneven outcomes or widening inequality. It is that organisations may have the tools to succeed but lack the people with the right skills to deliver that value from them.
News
Meta Creating AI Mark Zuckerberg so staff can talk to the boss - The Guardian
A new digital twin is being trained on his thinking and communication
Meta workforce reduction reports - BBC News
Up to 10% of global workforce to go
High Earners Race Ahead on AI — Financial Times
A workplace divide widens
White House study says DEI hurts productivity — Wall Street Journal
Productivity falls with race-based hiring says study
Gender pay gap narrows at glacial pace — People Management
More than generation needed to eradicate inequality
Prepare for new gender equality reporting requirements — HR Magazine
Voluntary action plans required from April 2026
Comment
The AI CEO chatbot era is coming — Financial Times
It won’t absolve leaders from the tough tasks
Is DEI dead in US workplaces? IBM's settlement raises new questions — HCA Magazine
Corporate America faces a test of leadership on DEI
HR's role in an agentic future — McKinsey
The role for HR in shaping the transformation journey ahead
Insight
Digital "twins" as a major trend for 2026 — HR Magazine
A closer look at the trend for clones of workers
CEOs using avatars to communicate with staff — Raconteur
Deep dive into the trend for virtual leaders
Organisations capturing expertise — InformationWeek
A look at the opportunities and shortcomings of AI leaders
The State of AI in Enterprise — Deloitte
How business are approaching AI adoption
2026 Human Capital Trends — Deloitte
How and where people fit into an AI future
Careless People by Sarah Wynn-Williams - The Guardian
A first hand account of leadership at Meta