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The Future of Work – Less Admin, More AI?

Will AI replace us? Is the white-collar career promise failing?

Generations have been promised that a University education, a decent suit and a willing attitude would land you a job and a decent white-collar career. Lattes and cheese plants aplenty.

Although the proportion of young people with a degree is now 60%, the UK is seeing rising unemployment rates, especially among young people. Finding a job in the current job market can be endlessly dissatisfying with hundreds of applications and no response.

I work with SMEs in Hackney, East London. How is all the adoption of AI going to affect entry level jobs? And work in general? What can we learn from previous patterns of automation?

The Bad News First

In the UK, proposed mass dismissal programs rose by 5% in 2024/25, involving over 267,000 proposed redundancies. UK businesses accelerate layoffs amid AI surge and legislative uncertainty. Full adoption of generative AI could save nearly 24% of private-sector workforce time, equivalent to the output of 6 million workers. Predictions are that nearly 40% of global employment will be affected by the end of the decade. The Impact of AI on the Labour Market

White-Collar Worries?

The Centre for AI and Digital Policy (CAIDP), a US non-profit research organisation, produces its report on global AI policy every year. Here’s a summary of the CAIDP’s 2025 Index on which job roles will benefit from AI automation and which will suffer. The word clerks keeps coming up – lower-skilled, administrative roles i.e. the first step on the corporate ladder. CAIDP Index 2025 – Center for AI and Digital Policy

Fastest-Growing Jobs (Technological Focus)Fastest-Declining Jobs (Clerical/Administrative)
Big Data SpecialistsPostal Service Clerks
FinTech EngineersBank Tellers and Related Clerks
AI and Machine Learning SpecialistsData Entry Clerks
Software and Applications DevelopersCashiers and Ticket Clerks
Security Management SpecialistsAdministrative and Executive Secretaries
Data Warehousing SpecialistsPrinting and Related Trades Workers
UI and UX DesignersAccounting, Bookkeeping, and Payroll Clerks
Renewable Energy EngineersTelemarketers

Tomorrow’s World – Speed, Control and Service Improvements

Imagine it’s the early noughties. The introduction of self-service tills, along with the promise of no more queuing. You would now be in control of your own shopping experience, could scan and pack your own bags at your own pace, and do so privately without feeling undue pressure. Based on the estimates at the time, what would cost the supermarket £2.50 in staff costs would now cost them 15 pence, with the implication that prices would also be affected. You’d soon be waiting less and spending more for your weekly shop.

Even the staff are about to be liberated from monotonous and repetitive tasks. They will take on more supervisory roles and had more flexible interactions with customers.

A 2003 Nielsen survey found that 52% of shoppers considered self checkout lanes to be “okay,” while 16% said they were “frustrating.” Thirty-two percent of shoppers called them “great.” Nobody likes self-checkout. Here’s why it’s everywhere | CNN Business

The Paradox of Automation – Worse All Round?

A 2025 Serve Legal study found 37% of shoppers admit to stealing at self‑checkouts, contributing to retail crime losses of £4.2bn annually. As supermarkets removed manned tills and pushed self‑checkout, more shoppers reported waits up to three minutes or more instead of no queue.

Studies of over 6,000 workers cited by The Grocer describe high stress, abuse from frustrated customers, and a sense that front‑end staffing levels are no longer sustainable. Proof that self-checkouts are causing a decline in customer service | Comment & Opinion | The Grocer

Only 10% of customers (from a 300 UK customer sample size) want more automation in store (research conducted by GetApp in February 2024) UK survey shows self-checkouts top store automation technologies

So Why Do They Still Exist?

Supermarkets typically operate on a 3% profit margin. After billions of pounds in investment in the technology, the promised savings of replacing labour with automated tills are not there. Include shoplifting, security and reputational effects and the margins are tight but, crucially, there are there. There is still a margin of profit.

As competitors have all installed the technology to seem equally interested in their customers, there’s not really any alternative so, even after a poor experience, you can’t vote with your feet and shop somewhere that hasn’t converted to self-service.

And We’ve Gotten Used To Them …

Stores today are catering to shoppers who perceive self-checkout to be faster than traditional cashiers, even though there’s little evidence to support that. But, because customers are doing the work, rather than waiting in line, the experience can feel like it’s moving more quickly. Nobody likes self-checkout. Here’s why it’s everywhere | CNN Business

According to the GetApp survey mentioned earlier, consumers are now positive about self-checkout tills:

  • 69% of respondents would rate their experience with self-checkouts good to excellent.
  • 73% who use self-checkouts stated they plan to continue using them in the future.
  • Over three quarters (78%) agreed that their encounters with self-checkouts have improved over the last 5 years.
  • 73% claim self-checkouts add efficiency to their shopping experience.

UK survey shows self-checkouts top store automation technologies

The Pattern of Adoption


Industry activityPublic perception
Step 1Automation is driven by cost savings (primarily labour) and associated profit marginsChange is presented as progressive with promises of improved experience
Step 2Accelerated adoption of automation by a competitive marketPoor experience and sympathy towards job losses and the marginalised minority (See Margins and Marginalisation below)
Step 3Accustomisation as experience improves beyond a lower threshhold of expectationCustomer perception of independence develops as they get more skilled at the delegated work
Step 4The automated process is normalised and issues minimalisedSympathy for job losses and the marginalised minority evaporates

Margins vs Marginalisation

Of course, not everyone has accepted the automation of everyday life tasks. Consider how automation can instead become exclusion. In the 10 years since 2013/14, the estimated number of disabled people in the UK has increased by 4.9 million. Among 16 to 24 year olds, there are twice as many reporting as disabled, increasing from 8% to 18%. UK disability statistics: Prevalence and life experiences – House of Commons Library

Imagine you want to use a Self-Service checkout and you have a visual impairment. You have to use a touchscreen, there is no headphone jack for headphones to have a voice explain what you can see, the flat screen does not provide any tactile means to identify where you should press. Or you have a motor impairment. Cramped self-service areas. Wheelchair users cannot reach up and forwards enough, scanning requires precise movements, machines freeze if there’s a delay.

The Reality Of Automation

In 2024, several major UK and US retailers began reintroducing manned tills specifically because of feedback regarding accessibility and the “unfriendly” nature of automated lanes for vulnerable customers.

The Jevons Paradox

So, where are we on the AI automation of white-collar work?

Delving deeper into the CAIDP’s 2025 Index, we see the expectation of a gentler transition than the headlines might suggest. Enter the Jevons Paradox. This states that as a service or resource becomes more efficient, the overall demand for what it creates rises.

LED lights are more efficient. Older lights are replaced but new LED lights displays on signs or other media have been introduced. The fact they’re cheaper means there are more of them.

AI makes coding and software creation significantly cheaper and faster. What happens? More software, more tailored offers and more use cases. And this creates new specialist roles. The transition is less sudden and cliff-edge and more gradual as companies learn the skills to use AI competently and humans are employed to manage the areas it can’t handle or needs supervision for.

Human institutions are slow to adapt and change to new technologies. I interviewed a Finance Director in a niche sector several years ago and he told me there was still a niche part of taxation where the form had to be sent by fax. They still had a working fax machine. Yes, AI is faster in its lane but it can’t comprehend the distinct personality of a company’s management structure and how Brian likes his folders labelled.

What Does This Pattern Of Adoption Predict?

Step 1.

AI is a new wave of automation. It promises to do the repetitive, resource-heavy tasks you hate for you and free you up for more satisfying work.

We will see an acceleration of adoption among the companies who can afford large-scale AI investment. Recruitment among big companies will slow or freeze. However, initial hopes of significant profit leaps will not materialise.

Case Study – Klarna’s AI Agent

At the leading edge, Klarna (the digital bank with the buy-now-pay-later instalments feature)have claimed its AI customer assistant does the work of 853 full-time agents and this saves them $60 million a year. However, overall customer service and operations costs were slightly more year-over-year ($50M vs $42M in Q3 2025). Klarna Investor Relations, “Q4 2025 Results & Strategic Update,” Feb 19, 2026. They have halved their workforce since 2022 as their revenue has doubled. Klarna Group plc – Klarna Accelerates U.S. Growth and Delivers $1bn Revenue Driven by Rapid Banking Service Adoption

However, cost savings were masking an underlying issue. A quarter of the customers with resolved issues were coming back. Their problems still existed after all. The company have now pivoted as of February 2026 to a model that re-introduces a human for more involved or high value queries.

Klarna Saved $60 Million with AI. Then It Had to Rehire the Humans.

Step 2.

It seems to me we’re still at early Step 2.

For most people in most work or office situations, AI certainly helps but the quality of the results is poorer than expected. Over-reliance on what AI can be trusted to do causes issues down the line.

Partly, this is because we haven’t been trained how to use it well enough and partly because the AI models aren’t reliable enough.

What Have We Learned?

The AI automation of repetitive administrative work is not a wholesale replacement of white-collar clerical workers. At least not yet. Instead, it’s a way to build efficiency into the admin work being done so that employees can achieve and produce more with less human resource.

Traditional ways of working take time to adapt and add blockers even when companies do want to automate. People don’t trust new technologies. The change will be more gradual and will probably a decade or two.

What it does mean is that new clerical roles will stall. The need for new entry level and junior roles is where the change is taking place.

However, new roles in quality assurance, AI agent management and software development will also be created.

SMEs with specialist skills can fill the gap that a drop in entry level roles will leave behind. Tailored software solutions or management services will offer businesses alternatives to developing new staff. This out-sourcing of talent and responsibility will become more attractive as the risks of AI become more apparent. But that’s a future blog.

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