There’s something in the air recently, and it feels like it’s gathering steam. I think we’re witnessing the real-time collapse of the decades-long emotional contract between corporate employees and their employers. You might even call it the end of trust.

While I’m more than five years out of corporate life, I still speak to a lot of people who are immersed in that world and there are a few themes that are growing clearer with each passing day. The main one is that there seems to be a growing disconnect between leadership messaging and how people are experiencing work.

The mood right now feels different from anything I’ve ever really seen before. It feels super cynical and jaded, and I’m not really sure if companies know how to fix it.

To be frank, from what I can gather, a lot of companies don’t even know they have a problem yet, let alone the will to fix it.

The psychological contract is breaking down

Right now we’ve got a few factors converging at once that are contributing to this mood:

• Burnout remains widespread. Around three-quarters of employees report experiencing it.

• Trust in leadership continues to fall. According to recent Gartner research, only 48% of employees trust their senior leaders.

• One recent study found around a third of employees admitted they were actively resisting or sabotaging AI initiatives inside their organisations, because they don’t trust what’s coming next. And honestly, with what companies like Meta are doing right now, who could blame them?

This is not simply resistance to a new technology. It reflects a broader breakdown in workplace trust.

For decades, work operated on an unspoken emotional agreement between employees and employers.

Employees gave extra effort, emotional energy and loyalty. They stayed late when needed, took on additional responsibilities above and beyond their job description when asked. Many were true believers in company culture and direction. In return, they expected some version of stability, career progression, belonging or meaning.

The arrangement was never perfect. Corporate life has always involved trade-offs and power imbalances. Still, many people believed the exchange was fundamentally fair -or fair enough not to disrupt the status quo too heavily.

That belief has started to fracture in recent times. Companies that used to call their staff “family” have resorted to layoffs over Zoom. And right now we’re hearing more and more companies talk about their new “AI first” cultures, after years of promoting their “people first” approach on LinkedIn.

The about-face - and dare I say it, the hypocrisy - is truly astounding.

People notice that disconnect, and once they do, it changes how they engage with work.

Employees are reassessing the deal

Many employees are no longer emotionally investing in organisations the way they once did. They’re pulling back to protect themselves, and approaching work more cautiously and transactionally.

In practice, that looks like doing the job and getting paid, then going home. Keep your boundaries where you can.

Many employees are no longer willing to provide unlimited discretionary effort simply because the company asks for it. If overtime becomes routine, they expect to be compensated. If organisations demand loyalty while offering less stability in return, employees can (and should) reassess the arrangement accordingly.

The biggest disconnect comes when leadership teams frame this as disengagement, poor attitude or even laziness. You know the ones - they complain about not being able to find good people, after years of treating their people worse than strangers.

That interpretation is not just tone-deaf, it completely misses the point. What many organisations are seeing is employees undertaking a highly rational recalibration of risk and reward, even if they don’t realise they’re doing it.

Employees watched repeated rounds of layoffs affect high performers and long-tenured staff alike. They saw companies praise resilience while laying people off in record numbers. They watched organisations celebrate flexibility before introducing aggressive return-to-office mandates. Now many are being told AI will reshape their roles, while leadership struggles to clearly explain what that means for their future.

Under those conditions, emotional withdrawal becomes a form of self-protection.

Why AI resistance is really about trust

That context also explains why AI adoption is becoming far more complicated inside organisations than many executives expected.

Leaders often assume employees resist AI because they fear change or lack technical understanding. In reality, many employees simply don’t trust leadership to deploy AI in ways that genuinely benefit workers. Resistance is predictable if employees believe productivity gains will primarily lead to workforce reductions, cost-cutting or unrealistic performance expectations.

Trust shapes adoption. Without it, even strong technical initiatives will inevitably fail.

Culture can’t survive on messaging alone

The long-term risk for organisations is the gradual loss of the discretionary effort companies have relied on for decades to be profitable or successful.

Many corporate cultures depend on employees giving more than the formal employment contract technically requires. The unspoken assumption has always been that strong culture, purpose and values would sustain that investment.

That only works while people believe the relationship is reciprocal. Once trust disappears, culture starts to look performative rather than genuine.

Branded values can’t compensate for that loss. Neither can free lunches, wellbeing webinars or another internal campaign about purpose.

Rebuilding trust comes first

If companies want employees to contribute discretionary effort and engage meaningfully with the future of work, they need to rebuild trust and credibility first.

Right now, many employees are rejecting an arrangement that no longer feels mutually beneficial. And once trust is gone, it takes a lot of effort to get it back.

I remember saying, “I’m about to go into surgery and there’s a chance I don’t make it out. I’m trying to enjoy some time with my son. Could you please call someone else?”

This was back in 2019. At the time, the interaction barely even registered as strange to me. It was just part of doing business - or so I thought.

Looking back now, that probably tells you everything you need to know about how normal burnout had become in my life.

The strange thing is, I was successful in my career.

I’d spent years building a career in high-pressure corporate and government environments. I was respected and trusted in a crisis. From the outside, I probably looked highly functional.

Internally, I was slowly burning through every reserve I had.

The environments that rewarded me were also exhausting me

The warning signs started well before my 2019 health crisis. Earlier in my career I’d worked in professional services for a few years. As anyone who has worked in that sector knows, it can be competitive and emotionally draining. For the most part, people inside those environments often treat that intense status quo as normal.

Long hours were expected and many people ended up on stress leave. Drinking culture was common, particularly across shared and corporate services teams. There was an unspoken understanding that people were replaceable and that pressure was simply part of being ambitious.

I survived two or three team restructures in my short, three-year tenure at this firm. I remember one colleague telling me “I never keep anything in my office except for my bag in case my role is made redundant, then I can just grab it and go”.

At the time, I thought I was built for it. Or that I could at least survive it, because it was good for my skills and CV.

Part of that was true. I now understand that my ADHD traits can make me very effective in high-pressure situations for short periods. Tight deadlines energised me, and crisis situations give me a bit of a dopamine hit. That means I could solve problems quickly and perform well when things got messy.

In certain environments, that tends to get rewarded. I was promoted and trusted, having built a reputation as someone who could handle difficult situations.

What I didn’t understand back then was that the same brain that performed well in intensity also struggled with sustained overload.

I know now that I’m autistic as well as ADHD, although I was only properly assessed much later when my son was going through his own assessment process. Noise, interruption, constant meetings, fluorescent lighting, emotional management, office politics and being socially “on” all day took a huge amount out of me. I could tolerate it temporarily, but not indefinitely.

So I did what us neurodivergent folks tend to do in those situations. I masked, so I could keep functioning and delivering. Then I would go home and feel completely depleted. Before having kids, there were days when I would get straight home and go to bed without eating. More days than I care to admit.

At the time I assumed everyone felt that way, and that this was just how working life was.

Burnout became my normal state

Years later, I moved into a senior government media and communications role during a particularly difficult period for the organisation.

When I joined, it was already coming out of a major restructure. While I was there, the organisation underwent a significant culture review linked to historical allegations of sexual abuse and misconduct. I managed the internal and external communications response around that review, which meant I was exposed to a lot of emotionally heavy material for extended periods.

At the same time, it was effectively a 24/7 media environment. The organisation delivered essential services around the clock, which meant that my team was expected to be responsive around the clock too. There was always another issue to deal with, and my phone seemed to ring constantly.

For a while, I still convinced myself this was just what high-performing careers looked like. Then it started bleeding into the rest of my life.

One of the clearest memories I have from that period is sitting in the car crying before my son’s second birthday party because work had been calling me all morning about an issue. All I wanted was one peaceful Saturday with my family.

That was probably the first time I consciously thought: this can’t be right.

Not long after that, I became so run down that I ended up in hospital with a severe sinus infection my body couldn’t fight off properly. It escalated into major head surgery and a month in hospital away from my little boy.

Somewhere in the middle of all that, I still thought answering work calls was normal. That’s probably the part I find hardest to explain to people now.

High-functioning burnout is difficult to recognise

One of the reasons burnout lasted so long for me is because I never stopped functioning externally.

I had always been a high achiever academically. I’ve learned to be quite articulate when I’m masking (although naturally my mouth is a little clumsy), and I’m good at solving problems. I could talk a good game in meetings and think quickly under pressure. The same traits that made me successful also made it easier to hide how much I was struggling.

Many people think burnout looks like collapse. Instead, mine looked like competence.

I kept delivering work and being dependable. I kept pushing through exhaustion because I thought that was what capable adults were supposed to do.

Looking back, I can see how much of corporate culture rewards that behaviour. If you’re productive, responsive and useful in a crisis, very few people stop to ask whether the environment itself is sustainable for you. Often you don’t ask yourself either.

I also think neurodivergent people can become especially vulnerable to this trap. Some environments genuinely suit certain nervous systems better than others. I actually perform very well in high-intensity environments for short bursts because novelty and urgency stimulate me. It’s only after a little while that I start fading into dysfunction, as the autism side of my brain starts kicking in and craving stability and safety.

The moment I knew I couldn’t keep doing it

By 2021, after the first year of COVID chaos, I was exhausted in a way that felt deeper than incidental stress. I took a month off work over the Christmas break.

The first week I mostly lay in bed staring at the ceiling. The second week I kept bursting into random crying fits. I felt melancholy and listless. I was probably depressed.

Somewhere during that break, I finally admitted to myself that I couldn’t continue living the way I’d been living. This wasn’t some inspirational breakthrough moment where I suddenly knew what came next - probably because I was still in deep burnout.

I just knew corporate life was no longer compatible with how I functioned, and that realisation changed almost everything afterwards.

I redesigned my life

Today I work for myself and my life operates very differently.

I only work school hours. I’m at the school gate. I structure my work around my actual energy levels instead of pretending I have unlimited capacity.

I rarely schedule meetings longer than 45 minutes because I know that’s close to the edge of my concentration and sensory tolerance. If a meeting runs over, I leave. I don’t need to make an elaborate excuse to do so, I just say “I have to go”. I no longer answer unexpected phone calls. If someone wants my attention, they need to book time in advance so I can prepare mentally for the interaction.

I also choose work differently now.

Certain environments are simply not a good fit for me. Disorganised teams, chaotic communication and constant interruption create a level of cognitive load that I now recognise as harmful for my nervous system.

For years I interpreted those struggles as weakness, however getting properly assessed for autism and ADHD after suspecting it for a while helped me understand that a lot of what I was experiencing was actually chronic mismatch.

Corporate life isn’t inherently toxic

I write a lot about corporate life, and from the context of what I write you’d be forgiven for thinking that I’m against it as a concept. This is not the case. A lot of corporate environment aren’t toxic and everyone experiences work in different ways. Some people genuinely thrive in high-pressure settings. I can even thrive in them myself temporarily.

What I can’t do anymore is ignore the cost. I think more people are reaching that point now, which is why I’ve decided to start speaking up about my experiences and advocating for things to be done differently.

Modern knowledge work increasingly rewards constant responsiveness, emotional availability and uninterrupted productivity. AI will probably intensify some of those expectations, not reduce them. Faster systems rarely create slower workplaces.

In that context, the classic 9-5, “command and control” model of work is outdated and excludes talented people from our workforce. That in itself is a productivity and innovation risk.

For a long time, I thought resilience meant overriding my limits. Now I think it probably means understanding them properly in the first place.

Why in 2026 is the four-day work week still treated like some unrealistic fantasy?

We have AI tools capable of automating hours of administrative work. Teams already answer messages from their phones late at night. Productivity software tracks everything from response times to output. Entire industries now run on digital infrastructure that allows people to work from almost anywhere.

Work has fundamentally changed, yet many companies still expect people to organise their lives around a five-day work model built for a completely different economy.

For decades, we’ve been told that technology would eventually reduce the amount humans needed to work. Automation was supposed to remove repetitive labour, and digital systems were supposed to increase efficiency. Over the past few years, we’ve heard from tech leaders including Bill Gates, Elon Musk and Eric Yuan that AI was going to free people up to focus on more meaningful tasks, and condense the working week.

Instead, right now, many workers feel more stressed and overloaded than ever. Around three-quarters are reporting they’ve experienced burnout.

So what’s gone wrong here?

Productivity up, freedom down

This is a contradiction that sits at the centre of the modern work conversation. Productivity has accelerated dramatically, but the average worker doesn’t feel like they’ve gained more control over their time. In many cases, the opposite has happened.

The workday now spills into evenings, weekends and family life. Responsiveness has become part of expected performance, and people are expected to be permanently reachable while also maintaining the appearance of enthusiasm for increasingly demanding workloads.

Most knowledge workers are not doing deep, focused work for forty hours a week. They’re also sitting in meetings that could have been an email, or managing ever-increasing volumes of communication across an array of channels. Many are navigating fragmented systems and endless notifications.

A lot of organisations still measure visibility more comfortably than they measure outcomes. That matters because the resistance to the four-day work week is often less about productivity and more about management culture.

Many leaders still feel uneasy when they can’t physically see people working. Entire corporate systems were built around presence and time spent at a desk. Even in hybrid environments, many workplaces still reward performative busyness over meaningful output.

If somebody can do their job well in four days, why should the fifth day exist simply to satisfy an outdated expectation around visibility?

AI is intensifying workloads

The uncomfortable reality is that many companies haven’t fully adapted to the type of work knowledge workers actually do now, and AI is making that very clear.

One of the more interesting recent findings came from an eight-month Harvard study of workers at a US-based tech company. Researchers found that AI tools often intensified work rather than reducing it. Employees completed tasks faster, then absorbed broader workloads and longer hours as a result.

That probably feels deeply familiar to many workers already living through this reality.

The promise of AI was increased efficiency. The lived experience for many people is that efficiency simply raises expectations. If you finish work faster, more work appears. If you automate one part of your role, the scope expands somewhere else. If a task takes half the time, companies often treat that as an opportunity to increase output rather than return time back to workers.

This is probably why so many conversations about AI currently feel more stressful than exciting. Right now it feels like race to the bottom for many of us.

Workers are hearing less about improved quality of life and more about headcount reduction and doing more with fewer people. Instead of asking how technology could improve human life, many organisations appear focused on how aggressively they can optimise labour costs.

At some point, we need to ask a bigger question about the purpose of all this technology:

If productivity keeps rising while burnout rises alongside it, what exactly are we optimising for?

Capability isn’t the problem here

We already have evidence that alternative working models can succeed.

A large-scale four-day work week trial highlighted by the World Economic Forum found participating companies reported reduced burnout, stress and fatigue among employees, alongside improvements in mental and physical health. Companies also reported revenue growth during the trial period, with most choosing to continue the model afterwards.

Why hasn’t that success meaningfully transferred to mainstream work structures? For me, it suggests that the barriers are probably cultural and economic rather than operational.

A genuine move toward shorter working weeks would require companies to rethink how they evaluate performance, structure management and distribute productivity gains. It would require leadership teams to focus more heavily on outcomes and less on time spent appearing busy.

For some organisations, that represents a significant loss of control.

Who is carrying the cost?

There’s also a deeper social layer underneath this conversation: the people most exhausted by performative work culture are often those already carrying significant responsibilities outside work, for example:

• Women are still disproportionately managing caregiving labour.

• Parents are balancing increasingly expensive and demanding family logistics.

• Neurodivergent workers are navigating workplace environments that often require constant masking and social performance on top of their actual jobs.

For many people, the issue is sustained overload, and that overload has become normalised.

Modern corporate culture often frames exhaustion as a badge of honour. Being permanently available gets interpreted as commitment, and working through evenings becomes a sign of being valuable.

For me, this is why the conversation around the four-day work week matters so much symbolically. It challenges the assumption that work should consume the majority of a person’s energy and identity.

I fundamentally disagree with that assumption.

Who benefits from AI?

The four-day work week debate should also make us think about who should benefit from productivity gains created by technology. Right now, many workers don’t feel like they are benefiting very much at all.

The strange thing about modern work is that technology keeps making tasks faster, while somehow making workers more available at the same time.

We now have tools capable of reducing administrative load, accelerating production and automating routine work across huge parts of the economy, yet many people feel less in control of their time than they did a decade ago.

For me, that suggests that the technology may not be delivering on its intended promise and benefits. However, beyond the tech it’s also a leadership and economic choice.

Until organisations are willing to prioritise outcomes over visibility, the four-day work week will continue to be treated like a radical idea instead of what it probably is - a reasonable and even expected response to how work has already changed.

Recent research on people experiencing burnout at work has been eye-opening, to say the least. Several studies have found that the rate of burnout has increased year-on-year and is now the top challenge employees face.

It’s easy to dismiss burnout as someone who is just feeling tired or a bit over it, but that underplays the seriousness of the issue. Proper burnout is chronic stress that doesn’t switch off. It shows up as exhaustion, detachment and a drop in performance -even when someone is trying to keep up.

A recent report by Spring Health found that up to 74% of employees have experienced it, which suggests to me that we’ve moved beyond the remit of the HR department and wellbeing programs, to the point of needing to have a discussion about design and what’s going wrong in the wider system.

Here are a few thoughts that I’d put on the table for consideration.

Disappearing workloads that don’t actually disappear

Let’s start with what’s quickly becoming standard operating practice, particularly in the current economic environment - workforce cuts and restructuring to take costs out of the business.

However, in a lot of cases, the work doesn’t go anywhere after the person doing it has departed the organisation. It gets redistributed across the people who remain.

Organisations rarely say this explicitly. The language is usually efficiency, optimisation, or doing more with less. In practice, it means the same output is expected from a smaller base.

Spring Health’s data points to unmanageable workload as a primary driver of burnout. That isn’t surprising to me, because many workplaces I’ve seen now assume stretch as a baseline, not an exception.

Redundancy used to imply a reduction in scope and roles that were “genuinely surplus to requirements” (yes, you can tell I used to be a senior manager in the government sector!). Now it often signals a redistribution of effort.

If companies that are still posting profits are taking roles out of the workforce and giving their work to AI, then AI should be handling that work - not the people left behind.

The workday no longer ends

Now consider what’s happened to our time and boundaries over the past few years.

Technology has removed most of the natural boundaries around work. For many people, there’s no clear start and finish; no no real separation between being available and being off.

Too many people feel pressure to “stay across what’s happening” and keep things moving. It might feel reasonable at the time, especially if something urgent has come up. Collectively, those moments create a workday that never properly stops.

Technology has effectively put many of us into a constant state of alert, where people feel connected but depleted. Work spills into evenings and weekends because the signals that used to mark the end of the day have disappeared.

Remote and hybrid work amplified this. Flexibility increased, but the trade-off has been weaker boundaries.

The result is both longer hours and fragmented time. Attention is constantly pulled back into work, even when the day is technically over. Without proper recovery, stress accumulates.

Technology raised the baseline

AI and automation are primarily framed as productivity tools. Which they can be, because they make it possible to do more in less time.

However, they also change expectations. If something can be done faster, it is expected to be done faster. If a tool can increase output, output becomes the new baseline.

At the same time, AI introduces uncertainty. People are aware that parts of their role could be automated or redefined. That awareness creates a low level of fear and shapes behaviour.

Many people respond by pushing harder to prove themselves valuable. They might feel the need to be more visible and produce more, or to keep up with the new tools and platforms.

Often you end up with a combination that is difficult to sustain:

• higher output expectations

• fewer people doing the work

• constant connectivity

• ongoing pressure to stay relevant.

I read an interesting article in Forbes recently which framed technology as something that keeps the brain in a loop of checking and scanning. AI extends that loop, because it adds performance pressure on top of attention pressure. This is where burnout starts to accelerate.

Employees are absorbing the cost

Put all these pieces together and a pattern starts to emerge:

• workload increases without a corresponding increase in capacity

• time boundaries disappear

• performance expectations rise again.

The system might look more efficient on paper, but it becomes more extractive in practice.

The cost of that extraction doesn’t sit on the balance sheet. It sits with employees. It’s visible in exhaustion, disengagement, sick leave and attrition. It shows up in people who are still doing their jobs, but with less energy and less margin.

All too often, companies treat burnout gets treated as an individual issue to manage. People are told to take some paid time off, or call the employee assistance program. These things have a role in addressing the symptoms, but they don’t address the underlying mechanics.

People aren’t fixing their burnout

Much corporate thinking assumes that burnout can be solved at an individual level with wellness programs and support. What I’m seeing instead is people starting to question whether the model works for them at all. They’re asking whether they want to keep operating in an environment where this level of pressure is normal.

We could be in the early stages of something broader - not a mass exit from the workforce overnight, but a steady reassessment of what work is worth.

Finally, burnout is often framed as a warning sign for individuals, but it’s also a signal for organisations. When most of the workforce has experienced it, the model itself might be broken.

There’s a conversation happening right now about women “falling behind” with AI and honestly, I’m finding it really unhelpful.

High-profile voices have joined in to reinforce the message, with a mixed response. Reese Witherspoon has encouraged women to engage with AI to avoid being left behind. Her efforts have been received poorly in many quarters, particularly considering her role as a book-to-screen producer and the fact that AI is trained on copyrighted works.

At the same time, Sheryl Sandberg of “Lean In” fame has been speaking out in support of initiatives to address the growing gender gap in AI usage. (I’ve got my own set of issues with the whole “Lean In” philosophy, but that’s another article for another time.)

Right now, all the data is suggesting that women are reporting lower daily use of AI tools than men. Meanwhile, we’re also hearing speculation that women’s roles are more likely to be taken or transformed by the technology. From here, it’s logical to conclude that we have a problem that’s going to impact women and their career progression.

That assumption needs closer examination.

What no one is questioning

This narrative relies on a set of assumptions that haven’t really been questioned, being:

• It treats AI adoption as inherently beneficial (to whom?).

• It presents participation as necessary for relevance.

• It interprets lower usage as a problem that requires correction.

Most commentary presents these positions as facts, rather than arguments.

A group with a long history of managing the consequences of poorly designed systems, such as women have in the workforce, have every right to approach a new one with caution. That response is likely to reflect their experience, rather than a deficiency.

Hesitation is not the same as being behind

Many women manage the realities of how work operates in practice. Caring responsibilities, administrative load and the ongoing negotiation between professional and personal demands shape how they assess new tools.

According to the UN, women do around 75% of unpaid care work globally, which is worth around 40% of the global economy. It’s the work that keeps everything else moving. We manage households and schedules, kids and ageing parents. And just to underline that word in the first sentence of this paragraph, in case you missed it, we don’t get paid for it.

In some cases, hesitation to adopt AI might be due to concerns around privacy, sustainability, creativity or ethics. For others, it might also reflect a clear assessment of time, effort and trade-offs.

The current narrative removes that nuance, because it reduces the issue to a single variable: adoption speed. That simplification limits the conversation.

The pressure to keep up

Currently we’re seeing pressure to “keep up with AI” aimed at a group of people who already manage significant demands.

Experimenting with new tools and integrating AI into workflows adds to existing responsibilities. Those responsibilities often include raising children, running a business, managing health and handling daily logistics. Sometimes getting through the day is enough, without adding the need to develop one’s AI skills on top of that. In that context, deprioritising AI reflects a rational choice.

Honestly, your average woman might be forgiven for wondering why AI can’t be tuned to meet us where we are, and solve some of the problems we’re currently facing. Why are we being burdened with yet another responsibility to carry, when the fundamental role of any technology is to make life better in some way?

Where is the actual benefit?

There’s also an elephant in room that we simply don’t talk about enough. We’ve been promised that AI is going to solve some of the world’s greatest challenges. So far, that doesn’t seem to be the case. In fact, I’d argue that the world is in worse shape than it was when ChatGPT arrived a few years back.

Some organisations are seeing improvements. They’re reducing costs and claim to be improving efficiency. At an individual level, the value is less clear. Many people struggle to identify consistent, tangible benefits. Learning the tools requires time, and outputs vary in quality. There are significant concerns about environmental impact and workforce implications.

When individuals carry the burden of adoption while organisations capture most of the benefit, the entire premise deserves scrutiny. Why are we doing this at all, if it only benefits the few, rather than the many?

A position based on experience

At this point I also want to note that my perspective doesn’t come from AI hatred or avoidance. I adopted AI early because it directly affected my work. Writing was one of the first functions to face disruption, so engaging with the tools made sense. I even wrote a book about it last year.

Over time, my usage has changed. I now apply it selectively. In my process, the outputs aren’t always reliable, and after a while every piece of copy starts to sound the same, no matter how much I try to tune the model. Now I’d rather spend that time tuning my brain instead.

I think it’s a useful technology that isn’t being harnessed to its full potential right now. If as a society we were to create a balance sheet of pros and cons, I feel that it would be weighted to the con side right now. That’s something that could be corrected with greater public engagement in the development and adoption, plus regulation and oversight to manage the environmental, workforce, creative and ethical issues.

The question we should be asking

The current framing doesn’t distinguish between lower usage and deliberate choice. It treats every gap as a problem that requires correction.

I’d argue that a more useful line of inquiry is to examine what’s driving the push for universal adoption, which outcomes organisations prioritise and who benefits from those outcomes.

We also need to assess whether the expectation that everyone integrates AI into their work reflects genuine need or a combination of commercial incentive and momentum.

Let’s park the conversation around “women being left behind by AI”, take a step back and have this conversation instead:

Until a clear answer emerges, the focus on who is ahead and who is behind remains premature.

I posted something recently on Instagram about AI, cost cutting and corporate decision-making. I didn’t think it was anything particularly controversial - until the comments started.

My argument was that companies looking for ways to reduce overhead in a tighter economy should consider options such as flexible work for eligible staff, which has been demonstrated to deliver savings of up to $11,000 per worker annually through reduced overheads and real estate costs. What’s more, these options should be considered and tested before mass layoffs are rolled out as part of doing business ethically and sustainably.

(I also think companies should be made to demonstrate they’ve done everything they can to manage costs before cutting staff en masse, but I know that’s never going to happen.)

I found myself getting involved in a bit of back and forth with one person who took it upon himself to explain to me, in some detail, that payroll is the biggest cost for most companies, so of course companies cut people first. Most importantly, he really wanted me to know that if AI allows you to do more with fewer people, it’s a cost lever that should be pulled immediately.

His position was that it’s simply how businesses need to operate, especially listed ones, because that’s what fiduciary duty requires. And to be fair, none of that is wrong. I work on investor reporting and communications, so I know and understand that logic from inside the company. Your number one focus needs to be reducing costs and maximising profits to deliver to your shareholders. That means reallocating capital when it’s required and investing where the returns look stronger.

You can defend every step of that. What’s there to argue with, really?

What I’d like to argue with here

Mansplaining aside, it took me a little while to work out why I was so bothered with what he was saying. It wasn’t the logic, it was the boundary of the argument. The “shareholder value always comes first” argument only works if you treat the company as a closed system, and that is simply never the case.

Companies draw on shared infrastructure all the time. They benefit from public roads, energy systems, communications networks, regulatory stability and education systems that produce skilled workers. None of that sits on the balance sheet in the same way payroll does, but it’s foundational to how businesses operate.

When things are going well, the returns are clear. Company revenue increases without having to pull too many cost efficiency levers, which means more profits and benefits to shareholders.

Friction appears when the economy is tighter, like we’re experiencing right now. When decisions are made to reduce cost, the impact doesn’t stay neatly inside the organisation.

People lose income, which means households adjust spending. Communities absorb the change and governments pick up second-order effects through support systems and reduced economic activity.

Of course, no single company is responsible for that entire chain. However, they all contribute to it in some way, and it still exists. If multiple companies are trying to optimise at once to protect themselves, everyone carries the burden of that.

What gets measured, what gets absorbed

We have a system that measures and rewards financial outcomes very precisely, and treats everything else as secondary. Workforce impact is acknowledged, sometimes reported, but rarely carries the same weight in decision-making.

Decisions that are rational at the company level can produce outcomes that feel increasingly uneven at the system level. You can see it more clearly right now because of how those decisions are playing out.

It’s harder to ignore when those decisions aren’t even driven by acute cost pressures. We’re seeing companies that are delivering strong results and still reducing their workforce at scale. Oracle is one example.

Those moves are often framed as strategic. In Oracle’s case, they are cutting workers to redirect investment toward areas like AI and infrastructure. The forward story makes sense for the company. However, what’s missing from that story is the fact that these outcomes don’t happen in isolation, and the company’s current success has only been possible because of the support of the shared systems, resources and infrastructure that underpins growth - even if that’s not directly accounted for in financial reporting.

When decisions are made to reduce workforce at scale, the impact extends beyond the organisation, while the gains remain tightly held.

AI is accelerating the pattern

Right now, AI is increasing the perceived replaceability of labour. It strengthens the case for structural cost reduction and then allows those decisions to be executed faster and at greater scale.

The logic might be easier to apply, but the consequences don’t become easier to absorb. Far from it.

None of this means companies are acting irrationally. In many cases, they are doing exactly what the system asks them to do. And that is my point in a nutshell.

When every company optimises for its own position, using the same set of incentives, the effects accumulate across the system. They don’t remain within the firm. We’re starting to feel that accumulation right now, and it’s going to get worse before it gets better.

That gap has always existed to some extent. What’s changing now is the speed and scale at which it’s playing out. AI is making it easier to reduce labour, while market pressure is making it easier to justify.

Meanwhile, the systems that absorb the impact (households, communities, governments) don’t move at the same pace so the imbalance becomes more visible.

Where to from here

This isn’t about asking companies to act against their own interests. It’s about recognising that the current definition of those interests is incomplete. If companies rely on shared systems to grow, then the consequences of their decisions can’t sit entirely outside those systems. Right now, that’s exactly what happens.

Until that changes, we’re going to keep seeing the same pattern repeat: rational decisions inside the business, uneven outcomes everywhere else.

A lot of what we’re being told about work right now doesn’t hold up under scrutiny - particularly when it comes to corporate and white collar work.

We’ve reduced complex, structural changes to simple and often heated debates that are easy to argue about, but harder to act on. Office versus home; AI versus job security; flexibility versus productivity.

These are important conversations, but they’re also incomplete. Right now they tend to focus on what’s visible (the impact on individuals), while the underlying mechanics stay largely unexamined.

Meanwhile, people are trying to make real decisions about their careers based on incomplete information and the debates they’re hearing in the public domain.

The problem is not where you work

The work from home debate is a good example.

We’ve framed it as a question of location, as if performance is determined by whether someone is sitting at a desk in an office or at a table at home. This is simply not the case.

We don’t all work the same way, or need the same conditions to do our best work. Some people, like me, need quiet and stillness; others need collaboration and energy. Most need a mix that changes depending on the work they’re doing.

For a lot of organisations, the push back to the office has been framed about collaboration and performance, but there are also underlying concerns about visibility and control. It’s also about what leaders feel comfortable managing.

That’s a different conversation about trust, and whether employers have trust in their employees to do the right thing. And going one layer deeper - if employers don’t trust their employees to do the right thing, why are they hiring them in the first place and then retaining them in the workforce, rather than managing their performance?

Until that’s addressed, changing location won’t fix anything.

The AI conversation is running ahead of reality

At the same time, we’re being told that AI is about to fundamentally reshape the workforce. I believe it will, over time.

We’re already seeing tech companies like Oracle and Amazon laying staff off, and blaming AI for it. However, there’s a real question around what’s really driving those layoffs. Are the roles really being replaced like-for-like by AI, or are companies taking the opportunity to cut costs and redirect that budget into speculative AI investments, in the hope they pay off?

While it’s difficult to make any sweeping statements on this, the evidence suggests that the gap between what AI is promising and what’s actually working inside organisations is still pretty significant.

Most companies are still figuring out how to use AI properly, and the vast majority of AI pilot projects are failing. The workflows aren’t fully there, and the outputs still rely heavily on human judgement. In other words, they’re just not scaling into something usable.

Yet we’re already seeing decisions being made as if the capability is mature, with little to no public accountability for those decisions, which impact numerous lives. Not only in terms of those who have lost their jobs, but also the remaining team members who have to take on more work to pick up the slack, because AI isn’t capable of operating at the level of the worker who has been replaced.

Meanwhile, work might get faster, at least temporarily, but it doesn’t necessarily get better. The company loses capability and context gets lost. Shareholders might be happy with the numbers presented at the next quarterly update, but I don’t think they’re going to like the longer-term story.

Flexibility has been reduced to a policy tweak

We also need to continue the conversation around flexible work.

Several years ago, we were talking about how work was going to evolve to fit around people’s lives. Flexibility was meant to open up access for people who couldn’t operate within rigid, office-based structures.

In many organisations, it’s been reduced to a single day at home - if that option is even offered at all.

For people with caring responsibilities, for people managing complex lives or disabilities, or for people whose energy and focus don’t follow a standard pattern, that gap determines whether work is sustainable or not.

Individuals shouldn’t have to solve structural issues

A lot of this gets pushed back onto individuals to solve. We’re told to work it out ourselves, adapt faster or find something else to pay the bills.

However, many of the tensions people are feeling are not personal failings. And when so many people are feeling it at once, it’s reasonable to conclude this is the result of systems that have not kept up with how people actually live and work.

The friction often becomes visible at particular moments and life stages:

• When children start school and the structure of the day no longer aligns with corporate roles.

• When flexibility becomes something you have to negotiate rather than something built into the design of work.

• When there’s significant change ahead in the workforce, but no one is telling you what’s really likely to happen.

People feel like they’re struggling to keep up, when in reality they are operating inside systems that weren’t really built for them.

Why I’m launching Track Changes On

I spent years in senior corporate roles. I left to start my own consulting business, because the reality of corporate life no longer worked for me. With some distance, I’ve had an opportunity to look at what’s going in in that world with an impartial eye, and I can see there are some very deep flaws in what we’re being told and how we’re expected to operate.

I also work with a number of corporate clients on projects involving brand, change, AI adoption and culture, so I’m exposed to these discussions every day. I think a lot about how organisations communicate, how they adopt new technologies and how they structure work.

I know from first-hand experience there is often a gap between the narrative and the reality, and that it’s employees who are likely to suffer most because of that gap. This is why I’m going to try to fill in some of the blanks.

I’m building a place to go deeper on what’s happening at work and what it means for you. That includes:

• How AI is being used in practice, not just what’s being promised.

• How corporate structures are changing, and where we need more visibility and accountability.

• What flexibility actually looks like inside organisations.

• What to pay attention to if you’re starting to question your own path inside the corporate world.

Ultimately I want to help you make sense of the environment you’re operating in, so you can make better decisions as you navigate it.

If you’re starting to question things

If you’re starting to feel like there’s a gap between what you’re experiencing and what you’re being told, that’s probably not your imagination. You may also be feeling like corporate work no longer fits the shape of your life. You’re definitely not alone there.

If you’re trying to work out whether to stay, change roles, or do something else entirely, we should find strength in numbers. Many are walking the same path as you right now, and many have gone before you. I was one of them.

In my experience, most people don’t talk about what they’re feeling that openly. We tend to sit with our dissatisfaction, or make moves behind the scenes. I think it’s time we have more frank and open discussions about what’s really going on in corporate life, and what people are feeling right now.

Track Changes On is here to host those conversations. Subscribe to join the discussion and support my work.

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