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Yves here. On the one hand, the account below, from Richard Murphy’s son Tom, on how AI has upended the job market and career paths in the UK, is anecdata. On the other hand, Tom provides a lot of informative color. I hope readers who either directly or through family and colleagues have further information and insight will pipe up in comments.
It is also maddening, in light of this post and other issues that Murphy has raised about AI, to see him as an enthusiastic user and even AI tout. At the end of his piece, which I have not reproduced given our policy of being firmly opposed to AI use as bad societally, theft of intellectual property, massively destructive environmentally and a reducer of skill levels in users, he encourages readers to write to their MPs….using a ChatGPT tool…which he warns can generate errors and must be checked.
Does Murphy have NO self-awareness? No wonder the Left sucks and Labour is in the state it is in. He’s openly supporting the sabotage of workers. He knows, or ought to know, that MIT has found that 95% of the companies that tried implementing AI did not find it was net productive and that LLMs are not accurate, and these problems are inherent (as in the idea that they would operate vastly better with sufficient scale is false). And this post means he can’t pretend to unaware of the impact of his treating AI use as not just defensible but even desirable.
By Richard Murphy, Emeritus Professor of Accounting Practice at Sheffield University Management School and a director of Tax Research LLP. Originally published at Funding the Future
AI is reshaping work faster than universities, employers, or governments can adapt.
In this intergenerational conversation, I talk with my son Tom about how artificial intelligence has destroyed the old promise: work hard, get good grades, and you’ll get a good job.
From “ghost jobs” to algorithmic hiring and a two-tier workforce, this video explores what happens when AI changes everything — and how young people can still shape their future.
This is the audio version:
This is the transcript:
I closed this week’s Funding the Future podcast by saying:
We are living in a period of change. You are going to live through a lot more change than I’ve seen in my career.
The conversation that I was concluding was with my son, Tom, who, for the past eighteen months, has been behind the camera for every YouTube video we’ve made. For the first time, he came out from behind the lens to talk about something that directly affects his generation: how artificial intelligence (AI) is reshaping employment, and what that means for young people trying to enter the world of work.
The conversation ranged from personal experience to hard data, and from graduate disillusionment to the new inequalities of AI. What emerged was a sobering, and at times disturbing, portrait of a labour market being transformed faster than most people — including employers — can comprehend.
The AI Revolution Without a Plan
I began by noting that many businesses are rushing into AI adoption out of FOMO — the ‘fear of missing out’ — rather than as a consequence of having any coherent strategy. Few know why they might use it for, or with what consequences. Yet, despite this confusion, the impact on real people, and in particular young people, is already enormous.
Tom’s observation was blunt: young people, students and graduates are entering a “confusing situation” in which they don’t know what skills to acquire or what jobs will even exist.
When he started university in 2020, AI was a distant rumour. Four years later, it dominates everything in the world of work he faces. He likened it to the spread of smartphones; initially novel, then suddenly everywhere.
The result is a generation being told to invest in education without any clarity about where it will lead. That uncertainty is spreading fast.
Graduates Are Being Squeezed Out
The graduate employment system, as Tom described, has become dehumanised and alienating. Job applications are filtered through AI-driven forms that strip out personality and force applicants to re-enter every detail manually — “the most boring thing in the world,” he said. After hours of aptitude tests and algorithmic vetting, most applicants receive automated rejections, often with no feedback.
The scale of the mismatch is startling. A survey by Hult International Business School found that 98% of employers said they struggled to fill vacancies, but 89% admitted they did not want to hire graduates. In short, employers complain of a skills shortage while rejecting the very people they demand that the economy produce.
The absurdity deepens. In 2024, there were just 17,000 graduate jobs advertised in the UK, attracting 1.2 million applications, or about 70 applicants per job. Of course, many people applied for many jobs, but it is still the case that universities continue to expand their intake, producing another 465,000 graduates each year. Whatever the data underpinning the ratios, the arithmetic simply doesn’t work.
No wonder Tom concluded: “The old idea — get good grades, go to a good university, get a good job — is dead.”
The Rise of “Ghost Jobs”
If that weren’t demoralising enough, many of the jobs graduates do apply for turn out to be ghosts. These are vacancies that companies post without any intention of filling them, whether to collect CV data, to signal “growth” to investors, or simply to test the market.
Tom cited data suggesting 30% of advertised positions are ghost jobs, rising to nearly 60% in some sectors. His friend applied to seven such roles, all of which remained online long after rejection letters arrived. Another firm Tom had applied to kept the same vacancy open for a year, re-advertising it every few months, but never seeming to want to actually fill it.
The result is an economy where hope is systematically wasted. Jobseekers spend weeks applying to roles that don’t exist. Companies exploit the illusion of opportunity to mine personal data or inflate their image. It’s a form of corporate dishonesty — employment wash, if you like — and it leaves young people exhausted and disillusioned.
AI and the Death of Entry-Level Work
Tom’s own field of study was accounting and finance. Yet, as he discovered, the firms that once hired thousands of trainees are now scaling back. The Big Four accountancy firms, he noted, have cut graduate recruitment by between 6% and 29% in a single year.
Why? Because AI can already do much of the routine data work that once required human accountants. Employers are filling entry-level gaps with algorithms rather than apprentices.
The same pattern is visible in marketing, coding, and customer service — professions now being “AI-washed.” As one local business owner told me, his marketing agency has effectively become a tech firm: it writes AI prompts for clients instead of campaigns. The problem, he admitted, is that “if there are no juniors now, who replaces me when I retire?”
This is the new paradox of automation: short-term efficiency at the cost of long-term sustainability. If companies eliminate the bottom rung, there will be no ladder left to climb.
Learning to Master the Machines
Yet not all the news is bleak. Tom and I both use AI every day in our work — for research, structuring videos, and accelerating creative processes. Used intelligently, it saves time and sparks ideas.
But, as we agreed, AI must be mastered, not served. The real risk is not that machines take our jobs, but that people forget how to think. Writing a good AI prompt is not like typing into Google. It’s a craft requiring clarity, precision, and critical awareness — the very skills universities should be teaching.
Yet universities, fearful of cheating and plagiarism, have mostly retreated from AI training. They are preparing students for a world that no longer exists. The Hult survey again offers insight: 94% of graduates who learned AI skills said it improved their career prospects, but few are being offered the chance to learn those skills formally.
So, we have an education system afraid of the tools that define the modern workplace. That cannot last.
Job Killer or Job Creator?
Tom’s view was that AI is both: it destroys routine work but creates new opportunities for those with initiative. It can do in seconds what once took hours — from writing citations to data analysis — freeing people to focus on creativity, design, and strategy.
But he also warned of an emerging two-tier workforce:
- AI users — lower-paid, task-driven, and easily replaced;
- AI designers and strategists — fewer in number, but commanding far greater influence.
That divide, he suggested, will define his generation’s inequality. Not just between rich and poor, but between those who learn to work with AI and those who are worked by it.
Lifelong Learning or Lifelong Precarity?
Our conversation ended with something more hopeful. Over the past eighteen months, Tom has reinvented himself as a videographer, editor, and digital learner — mostly self-taught through online courses and peer learning. He has acquired a range of skills, from lighting and sound to AI-assisted editing, none of which existed in his original degree.
That, perhaps, is the lesson. In a world of accelerating change, learning can no longer stop at graduation. It must be continuous, self-directed, and creative. Those who adapt will find opportunities. Those who wait for the old job market to return will wait forever.
A New Social Contract for Education and Work
The deeper problem is, I think, systemic. We are asking young people to invest time, money, and hope into an education system that no longer guarantees them a livelihood.
Employers complain of shortages while excluding the newly qualified.
Universities sell courses while refusing to teach the skills employers now demand.
Governments celebrate “innovation” while ignoring the growing despair of those left out.
If we want AI to serve society, not enslave it, we need a new social contract between learning, work, and technology — one that recognises human potential as our most valuable form of intelligence.
As I said at the close of the podcast:
AI is changing the world, whether we like it or not. The only question that remains is whether we shape it — or let it shape us.
AI isn’t the end of work. But it is the end of pretending that the old rules of education and employment still apply.
