There’s a quiet rewrite happening in offices around the world, and as usual, it’s starting in the US but we’re not going to be immune to it in the UK. As whenever our cousins across the pond catch the flu, we at the very least end up with a cold.
But this is unlikely to be a loud, sci-fi kind of change where robots roll in and take over. It’s smaller, subtle right now. But social media trends are beginning to pick up on it – and it’s the subtle automation of the middle management role.
Starting light with removing the menial task no-one enjoys like scheduling engines to optimise rotas. Performance dashboards to flag who’s underperforming. Decision models recommending headcount moves.
Tools which, for years have supported manager decision making, in the hands of AI, can be woven together to begin to replace them.
This isn’t panic territory, but it is worth paying attention. Many managerial tasks are already automatable. The result probably won’t be a single “AI takeover” moment, but something slower – a steady shift toward blended teams, new oversight roles, and a re-think of what we mean by leadership.
The current landscape
Two things set the scene.
First, the UK jobs market still looks alive. According to Reed’s September 2025 Job Market Review, 111,920 jobs were posted in September, an 18% month-on-month rise, with strong growth in IT, education and transport. That suggests confidence is holding, at least for now.
Second, the World Economic Forum’s Future of Jobs Report 2025 points out that AI and information-processing technologies are among the most transformative forces shaping global employment through 2030. Employers aren’t necessarily cutting jobs outright, but they are redesigning them.
Put those two together and you get a mixed picture: hiring is up, but so is automation. The middle space between the two is where management is being quietly rewritten.
What “automation of management” really means
Middle management has always been a strange hybrid of logistics, performance review, people management and admin. The automation creeping in isn’t about a robot in a suit; it’s about software taking over the repeatable bits.
- Scheduling and rotas: algorithms now handle availability, skill mixes and legal limits faster than any spreadsheet ever could.
- Performance tracking: dashboards collect and interpret metrics, then nudge employees directly.
- Decision modelling: algorithms can filter candidates for promotion or redundancy based on patterns in historical data.
- First-line feedback: AI chatbots can coach, guide and even deliver performance feedback in standardised language.
These systems don’t just support managers; they start to act as managers. The McKinsey State of AI 2025 report shows many organisations are redesigning workflows entirely, using AI to take over routine decision-making while leaving humans with oversight and ethical calls.
The Amazon wake-up call
If this still sounds hypothetical, look at Amazon’s October 2025 announcement. The company confirmed thousands of corporate job cuts, tying much of it to “efficiency gains” from AI and automation across logistics and corporate functions.
That moment landed hard because it showed that AI isn’t just coming for warehouse jobs. It’s creeping into the office. Amazon’s framing made it clear that some of the functions being automated were once the territory of mid-level managers and analysts – people who used to translate numbers into action.
When a major global employer signals that management itself can be “streamlined”, other corporates take note.
Which parts of management are most at risk
The evidence coming out of business schools and consultancies lines up on a few key points:
- Routine cognitive work is the most exposed. Harvard Business Review warns that replacing entry-level and routine cognitive roles with AI risks eroding the entire talent pipeline, because those jobs are where tomorrow’s leaders learn judgment.
- Workflow redesign is spreading fast. McKinsey’s latest survey finds that large firms leading AI adoption are already cutting time spent on “low-value” managerial tasks, shifting human effort toward oversight and culture.
- Skills are being redistributed. The WEF report predicts that within five years, analytical and technical tasks will shrink while demand for AI governance, creative thinking and emotional intelligence will rise.
In other words, middle management isn’t vanishing overnight. It’s morphing into something else – less about tracking, more about interpreting.
Why this shift feels different
There’s a psychological side to this that’s easy to overlook.
- Career pathways. Entry-level and middle management roles are the bridge to senior leadership. If those shrink or change shape, progression routes become murkier.
- Trust and discretion. Managers don’t just enforce metrics; they handle nuance, conflict and context. An algorithm can’t (yet) hold a difficult conversation or repair a broken team dynamic.
- Fairness and bias. AI systems make decisions using historical data, and data carries human bias. Without governance, automation can quietly replicate the very inequalities it was meant to remove.
So it’s not just about job loss. It’s about what kind of culture we build when the “human buffer” layer thins out.
Where the human goes next
If automation takes the grind, what’s left for people? Probably the parts of management that have always mattered most.
- Curators and interpreters. People who understand what AI output means, spot when it’s wrong, and turn it into stories and decisions that others can act on.
- Relational leaders. The ones who mentor, mediate, and build trust – the kind of leadership that data alone can’t replicate.
- Designers of work. People who know how to structure human–machine collaboration and make it fair, effective and meaningful.
The World Economic Forum and McKinsey both emphasise the same thing: the future belongs to those who can redesign jobs, not just perform them.
What employers can do now
- Map tasks, not jobs. Identify which parts of a role are automatable and which rely on human nuance. It’s rarely all or nothing.
- Protect learning pathways. Don’t strip out every entry-level task. Redesign them so people still build judgement and leadership skills.
- Build governance. Establish oversight boards or appeal processes for algorithmic decisions. Treat AI management the same way you’d treat financial compliance.
- Reskill deliberately. Offer training for managers in AI supervision, data literacy and ethics. The returns are faster than most leaders expect.
None of that is radical. It’s just practical.
What this means for recruiters and candidates
Recruiters will need to look for different signals. Employers will start asking for “AI-literate managers” – people who can oversee systems as confidently as they run teams.
Candidates should build credibility in areas like coaching, communication and ethical decision-making. Those are still the currencies that matter when the spreadsheet already knows the numbers.
A final thought
The shift we’re living through isn’t about robots taking over. It’s about redefining what we actually value at work.
Automation has already taken the physical load off human labour. Now it’s nibbling at the cognitive load too. What’s left – empathy, creativity, moral judgement – might finally be the part of management that feels most human.
If we get this right, AI won’t replace leadership. It’ll force us to remember what leadership actually is.
