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The Missing RUNG? AI and the Future of Entry-Level Work

Table of Contents Foreword

The Picture Around AI and

Early-Career Roles Student Research Findings

Student Interviews

1 A golden window of opportunity

2 Fluent in AI, but do you know who you are?

By Francesca Morichini, Global Head of HR, Electrolux Group

3 Become more valuable with AI than without it

4 The job market changes but does not disappear

5 How graduates can make themselves invaluable in an age of AI

6 Why entry-level recruitment remains a smart business choice 11

Otso Lammi, President of the CEMS Student Board, studying at Aalto University School of Business, Finland

6 Becoming a super individual

Key Takeaways

Insights

1 Ten insights for employers and

business leaders 13

2 Ten insights for educators of

Wenjie Chen – Tsinghua University School of Economics and Management, China

resonsible leaders

Expert Insights

1 Front-Runners: preparing students for an AI job market

Professor Bart Van Hoof, School of Management, Universidad de Los Andes, Colombia

Frank Steinert, Global Head of HR Regions at Henkel

András Csanádi, CEMS student board representative studying at Corvinus University of Budapest, Hungary

5 A difficult position but a real opportunity

A conversation with Gianmarco Mazzocchi (Esade / HEC) and Merthe Weusthuis (RSM / WU Vienna) CEMS alumni working at corporate partner Whiteshield

Zixuan Wang, CEMS Student Board representative studying at Tsinghua University School of Economics and Management, China

4 The cat is out of the bag

Phillip Nell, Professor of Global Strategy and Academic Director of CEMS at WU Vienna, Austria

İldem Demir, CEMS Student Board representative studying at Louvain School of Management, Belgium

3 In China we see the opportunity first

Manuel Zorn, AI Deployment Strategist Director at Salesforce, CEMS Alumnus 2020 (University of St.Gallen / Esade)

Friedrich von Bechtolsheim, CEMS Student Board representative studying at the University of Cologne, Germany

2 A machine shouldn't decide about me in a millisecond

Ten insights for early-career professionals

Nicole de Fontaines EXECUTIVE DIRECTOR CEMS GLOBAL ALLIANCE

Foreword Few questions right now provoke more anxiety than what the rapid rise of artificial intelligence (AI) means for those just starting out in their careers. Barely a week passes without a headline warning that the bottom rung of the career ladder – in other words the first step up - is being pulled away by automation. For young people preparing to enter the workforce, including our CEMS students, and for those of us who educate and employ them, the concern is real and it deserves serious exploration. Obviously, this is one question among many others, the most essential ones being the preservation of human dignity, the cultivation of critical thinking, the freedom to pursue truth and ensuring that technological progress contributes to the common good rather than concentrating wealth and power in the hands of a privileged few. This key theme first surfaced in our previous report, Augmented Leadership, as an issue our community felt most warranted deeper exploration, and so we set out to examine it directly. We interviewed a sample of our global student body to find out how they feel about entering work at this unique moment in history. We then asked a selection of corporate partners and academic experts how close they believe the fear around entry-level roles is to reality, and what ambitious graduates - in partnership with employers and business schools - should do about it. What emerged was a more balanced account than the headlines suggest. This is not a myth, and we certainly do not pretend otherwise. The graduate job market is genuinely challenging, with roles likely to disappear as AI reshapes work against a difficult economic and geopolitical backdrop. Yet the fuller picture is far from the one in which every junior role vanishes. Removing the bottom rung, our experts are clear, simply does not make business sense: it is detrimental to the pipeline through which companies grow their future leaders and sustain their values and culture. Entry-level roles are not only a means of getting work done; they are where people develop judgement, responsibility and the practical experience on which organisations ultimately depend. The bottom rung, they told us, is not missing so much as changing shape. We do not yet know exactly what that will look like, however our contributors are positive that this opens up a genuine opportunity for many graduates to contribute more meaningfully, and earlier in their careers than ever before. As the first generation of true AI natives, they have a unique opportunity to bring exceptional value to employers, provided they are willing to put in extra effort, experiment creatively, and cultivate the critical thinking and sound judgement needed to use AI wisely, carving out a niche for themselves. If anything, this moment underlines the value of alliances like CEMS. Graduates will increasingly be expected to arrive ready to contribute from day one, rather than spending their first years acquiring the groundwork that AI can now absorb. Preparing them, through close collaboration between leading universities and the world's major employers, is exactly what our alliance was built to do.

The picture around AI and early-career roles Before turning to what our students and contributors told us, it is worth setting out the existing evidence. The data on AI and early-career work is genuinely mixed, and reasonable people read it in quite different ways. Some of it points to entry-level roles being squeezed; some of it points to graduates being more sought after than ever. Many sources cite additional reasons for a difficult graduate job market, including economic instability and geopolitical unrest. CEMS corporate partners are among those painting a contrasting picture:

A 2025 McKinsey survey found that 51 percent of organisations reported that generative AI was reducing their need for entry-level roles.

Gartner tracked 1.4 million layoffs in 2025 and found that fewer than 1% were due to AI productivity gains, arguing that AI is changing jobs faster than it is cutting them.

Accenture, meanwhile, has committed to hiring more entry-level workers in 2026 than in 2025, on the reasoning that recent graduates bring crucial AI fluency and they want them in the workforce to help them.

Bain & Company data backs this up: AI-related job postings have surged by 21 percent annually since 2019, opening new opportunities as fast as it closes others.

The issue is far from clear cut. With a wealth of corporate and academic expertise across its network, CEMS is well placed to explore it more deeply, and to move the conversation beyond the headlines to what graduates, educators and employers should actually do.

Student Research Findings To begin exploring the issue, we polled a selection of students, including representatives from the CEMS student board, drawn from more than 20 countries. We asked how they use AI, whether they are concerned about finding an entry-level job in an AI world, and whether they believe AI will increase or decrease their generation’s creativity and capacity for independent thought.

Concerned

Not Concerned

Other

83%

69%

use AI to get quick answers.

69% worry that AI will decrease, or significantly decrease, their generation’s creativity and ability to think independently. 61% are concerned that AI will make it harder to find a job after graduation, while only 22% are not concerned.

Only 16% believe it will increase it.

86%

use it for research.

72%

Over half (55%) use it to upskill themselves, and one in six (16%) even use it to plan their day.

use it to check their work.

With a selection of these students, we then went deeper, exploring the challenges and opportunities they believe AI presents for their careers and the skills they are most keen to develop. Following that, we conducted interviews with six CEMS student board representatives in depth, capturing the perspective of those about to enter the world of work. Their accounts appear in full later in this section, and the themes they raised gave us the foundation for the questions we went on to put to our expert contributors. Grouped by theme below, their responses set out the hopes, fears and challenges they see ahead.

What skills and capabilities do you think will be most crucial in order for your generation if they want to have a successful career in an AI-driven workplace? Critical thinking and verification: evaluating AI-generated content with healthy skepticism, rigorous fact-checking and independent analysis, so that what you rely on is genuinely accurate. AI technical proficiency: mastering effective prompting, knowing which platform suits which task, and automating workflows, while treating AI as a support to human judgement rather than a replacement for it. Strategic judgement: discerning which problems call for AI and which call for independent thought and drawing AI outputs into your own understanding without becoming over-reliant on them. Human-centric skills: building strong interpersonal skills, such as communication and negotiation, which remain vital alongside constant technical adaptation.

What do you think are the biggest opportunities for your generation when it comes to AI? Efficiency and productivity: automating routine, manual tasks to speed up workflows and free up time for the complex, high-impact and strategic work that matters most. Competitive advantage and upskilling: fluency with AI offers a real career edge, bridging business and technical domains, accelerating development and letting graduates make a meaningful impact early on. New career frontiers: new roles emerging around AI operations alongside renewed growth in creative and human-centred fields such as automation frees up time.

On the other hand, what do you think are the biggest challenges? Job market displacement: concern that entry-level positions are disappearing as automation reduces headcount and intensifies competition for the roles that remain, leaving fewer ways for junior talent to gain experience. Skill degradation: over-reliance on AI risks eroding critical thinking, analytical skills and creativity, as people lean on the tool instead of building their own capabilities. Recruitment barriers: automated hiring can strip out human oversight, making it harder for candidates with non-traditional backgrounds to be judged fairly and widening the gap between talent and opportunity. Professional development gaps: a worry that companies will cut back on training juniors as AI absorbs their tasks, storing up a future shortage of experienced senior professionals and fewer chances for mentorship and hands-on learning.

What are the most valuable things business schools can do to prepare students for leadership in an AI age? Technical skill development: prioritising practical training in prompt engineering, workflow automation and the use of AI across specific industries such as consulting and finance, with specialist electives for students who want to go deeper. Integration and critical thinking: weaving AI into everyday coursework and projects to build familiarity, while fostering the critical reflection that keeps students sceptical, ethical and clear-eyed about what these tools can and cannot do. Industry-aligned curriculum: drawing on partnerships with startups and consultancies for guest speakers and real case studies, so teaching keeps pace with current industry practice and real-world AI applications. Responsible implementation: moving away from restrictive policies towards assessments that treat AI as a legitimate tool for research and analysis, while keeping in-person elements that verify each student’s own learning and mastery.

Student Interviews A golden window of opportunity When I think about the next five years, my feeling is mainly excitement, with a few worries thrown in along the way. The biggest thing AI changes is the nature of the tasks we do. A lot of CEMS students - myself included - look towards consulting, where a significant share of the work has meant assembling slide decks and aligning documents. I believe AI will steadily take over these more mechanical tasks, freeing you to spend your time on the work you actually find interesting.

Friedrich von Bechtolsheim CEMS Student Studying at the University of Cologne/ Universidad Adolfo Ibáñez

The job market itself is difficult at the moment, but I take some hope from what I still see around me. Our CEMS Club in Cologne runs as many corporate events as ever, and companies are still showing up at the career forum in large numbers. There is clearly still a vast appetite for talent. So how do you make yourself worth hiring? The buzzword is AI literacy, and there is something real behind it. Getting a result out of AI is easy; getting an exceptionally good result is a genuine skill, and it means staying close to the state of the art and understanding how the models actually work. Alongside that, interpersonal skills only become more important. I can't imagine an ultra-high-net-worth client being happy to discuss how their wealth is managed with a chatbot. That is still very much human work. I learn by doing. I have set up my own OpenClaw with an API key and now talk to it through WhatsApp, though it still sometimes sends error messages to the wrong chat! I use Claude Cowork to automate tasks, and I use vibe coding tools like Lovable and the Gemini canvas to build things, including an app to analyse my chess games. My generation is both advantaged and exposed at the same time. AI literacy is still far from universal, so the advantage is not automatic. But this is also the golden window: companies themselves are uncertain about what AI can and cannot do, so bright young people who really understand it can make themselves highly valuable. AI is not going away, so the work is to keep learning, on your own shoulders, and to stay curious about where it goes next. 8

A machine shouldn't decide about me in a millisecond I'll be honest: when I picture my career in five years, I am not that excited. We are in a transition phase where no one, probably not even the CEO of OpenAI, knows where this is heading, and that uncertainty makes me anxious as I prepare to enter the workforce. I am a bit sceptical of AI, and I try to minimise how much I use it right now. There was a period when I used it for everything, and I started to feel that I was losing my own cognitive skills. These days I force myself to do things manually, and I save AI for genuinely hard tasks, like summarising a large report on a short deadline. What worries me most is the hiring process. Every management or business role on LinkedIn has at least a hundred applicants, sometimes thousands, because people pay AI tools to optimise their CVs for every posting and fire off fifty applications a day. I'm anxious about a machine looking at my CV for a millisecond and making an instant decision about me. When I tick the box saying I don't have a European work permit, the AI can eliminate me automatically. A human might look at something specific and see why I am actually a strong candidate.

İldem Demir CEMS Student Board representative Studying at Louvain School of Management / HEC Paris

This is why I value the human aspect so much. I work in sales right now and appreciate the fact that we call clients and speak to them rather than relying on emails, because every day I receive fifty emails with the same tone. Sales is one area where people still want a human relationship, and that is exactly where we make a difference. The rise of AI hasn't made me want to abandon my plans. I still want to work in financial services or policymaking. However, it has made me think harder about what I bring as a person. Finishing the CEMS programme signals that I'm a disciplined, hardworking, well-rounded person, with international exposure and a strong network behind me. Even when AI can do many of my tasks, I still bring something only a person can.

In China we see the opportunity first When people ask whether my generation is advantaged or disadvantaged by AI, I lean towards advantaged. People who are already working may have more practical experience to draw on, but when it comes to using the tools, students like us often have the edge. We have more time to explore them, and we are freer to do so. I would challenge the idea that AI is simply erasing entry-level jobs. What I see is that the requirements at entry level are rising. Because recruiters and companies know these tools exist, they expect you to do more than you could before.

Zixuan Wang CEMS Student Board representative Studying at Tsinghua University School of Economics and Management / University of Cape Town Graduate School of Business / Norwegian School of Economics

For example, when I interned in the IT industry as a product manager, my job was to stop at drawing a prototype and describing the functions before handing it to a developer. Now, with vibe coding and coding agents, a product manager is often expected to build a working demo, not just a prototype. So the entry-level work has not disappeared; the bar has risen. There is a real difference between how Chinese and European students feel about the impact of AI on careers. In China we have our own independent technology ecosystem; open your phone and you find a completely different set of apps for messaging, taxis or food delivery. In contrast to Europe, there is a substantial concentration of well-capitalised AI startups, and established firms are racing to embrace AI too. So, a Chinese student tends to see the opportunity first. The anxiety that follows isn't a fear of being replaced by AI, but a sheer panic of falling behind those who embrace and leverage it.

I am investing in skills AI cannot replace. AI can draft a document or generate slides, but someone still has to stand up and present it, so communication matters. Outside work, it is worth keeping a real hobby, whether art, music or sport, because that develops your taste and judgement. What I would like from universities is to teach us how to use these tools well, rather than restricting them in the name of critical thinking. Give us a hard topic to learn in a day using AI, then have us present it. A presentation proves the knowledge is really in your head, even if AI helped you get there. That is a far better way forward than pretending we will not use these tools at all. 10

The cat is out of the bag I am genuinely excited about my career, and AI is a huge reason. I have always been drawn to technology because it is what moves us forward, so my instinct is to treat these tools as an opportunity rather than a threat. I already use AI in ways that have become second nature. When I read a technical book or hit a difficult passage of statistics or mathematics, I treat the AI like a professor and ask it to explain the idea in a more approachable way. I use it heavily for programming and also use it in ways that are less common, like running sentiment analysis on an email before I send it, to make sure that I am coming across as I intended. Tasks that once took a day now take twenty minutes, so why wouldn't I use it? People worry that AI will pull out the bottom rung of the career ladder, but I see it more as a shift towards softer skills. AI is going to be like the calculator. For years we were told we wouldn't always have one in our pocket, and now they are needed for exams. The point of an exam will stop being whether you can recite something and will instead focus on whether you can interpret it. A career is the same: the tool gives you the output, but you still need the knowledge to understand it, question it, and reveal the truth.

András Csanádi CEMS Student Board representative Studying at the Corvinus University of Budapest / Rotterdam School of Management, Erasmus University

That is why I am not too worried about entry-level roles disappearing. The basic work is managed, which frees you to focus on what actually adds value. For me it comes back to one idea: you own your output. You can do your work manually or you can use these tools to enhance it, but either way the result is your responsibility. My generation has a real advantage here because we are already fluent in this. The cat is out of the bag. We are not going to push AI back, so the real advantage goes to whoever learns to use it well, and ethically.

A difficult position but a real opportunity When I think about the next five years, my overall feeling is excitement, even though I know the picture is complicated. My background as a business student is quite technical, and it is genuinely exciting to start a career at a moment when a junior employee can have a big impact by bringing in fresh expertise that companies often cannot find anywhere else. Last year, I joined a company as a data analyst and ended up pioneering its AI approach at the same time, which was hugely valuable for my professional growth.

Otso Lammi President of the CEMS Student Board Studying at Aalto University School of Business / Bocconi University

I do not want to be naive about it, though. Overall, I think my generation is entering the workforce at a disadvantage. We are arriving at the exact moment when many companies have decided AI is good enough to replace junior employees. On the other hand, we are already seeing signs of a rollback. Some companies that moved quickly to cut junior roles are now realizing that AI also comes with costs, limitations and implementation challenges. So it is definitely a mixed picture.

That is why you have to put in the work yourself as a student. CEMS helps, because schools are trying to keep pace with developments. At Bocconi this spring, our syllabus changed in the middle of the semester to keep up with AI, which showed that the courses were built to prepare us rather than just to tick a box. It is also about mindset: taking your own time to understand the technology and using that to push your career forward. What used to be nice side projects alongside my main work have become the most valuable things on my CV. There is one risk I keep in mind. Even if AI keeps becoming more important, the exact tools, use cases and ways of working will almost certainly change quickly. If you bet everything on one specific use case of AI, you could find parts of your newly built skill set becoming obsolete in record time. That usually happens to employees in their fifties or sixties, not at the start of a career. So I stay curious, keep my options broad, build skills in different areas and try to stay adaptable as the technology develops.

Becoming a super individual I could have graduated this year and gone straight into a job but instead I took a gap year. You can’t plan a career three to five years ahead anymore, because in that time everything will change, so I would rather pause and find opportunities at this AI turning point, when I have more time and attention. Some of my peers worry that entry-level roles are vanishing. I see it differently: the work is shifting, not shrinking. The routine execution that once filled a junior's day, collecting information, drafting proposals, writing basic code, is exactly what AI now does faster and cheaper. What is left is more valuable, and that readiness will come from us. We have to take ownership of our own upskilling and become what I think of as super individuals: people who can move across roles, serving as product manager and programmer at once, framing the problem and then directing AI to solve it.

Wenjie Chen CEMS student graduate Studied at Tsinghua University School of Economics and Management / University of St.Gallen

The fastest way to get there is through a community. There is too much information online to sort alone. Join a community of people who genuinely understand AI, become a core member, and build alongside them, and you find the tools and strategies that actually work. During my gap year, I co-founded ATOX, a global outlier community initiated by students from Tsinghua and Peking University, connecting young AI builders, founders, and innovators across Asia. Most recently, we partnered with the World Artificial Intelligence Conference (WAIC), where seeing early-stage ideas and communities come together has further strengthened my belief that the future belongs to those who build. It also changes what I might look for from an employer in the future. The companies worth joining use AI in their own workflow, trust young people with real responsibility, and encourage us to challenge the processes that are not working and change them. For many of my generation, though, the more exciting path is to build something ourselves, which is what my gap year is really for. In China we now talk about the one-person company (OPC): with AI as your agent, a single founder can start a business at low cost and high productivity. Joining a startup, chasing the next unicorn, has become the ambition. AI has made the independent entrepreneur genuinely powerful, and that is a future worth choosing.

Expert Insights The student insights were rich and varied, ranging from concern and trepidation to hope and genuine optimism. Together they made it clear that the issue is anything but clear cut, and they gave us a strong basis on which to consult experts from across the alliance: corporate partners, academics and alumni. From their perspectives, set out on the following pages, we have drawn a set of key takeaways (pg. 27) and recommendations for employers (pg. 30), for educators of responsible leaders (pg. 31), and for early-career professionals themselves (pg. 32).

Front-Runners: Preparing Students for an AI Job Market AI will create many new jobs, and existing roles will shift, but that's normal. It will hurt, of course, because it challenges the status quo, and as with many things in life, there will be winners and those left behind. However, amid uncertainty around the future of entry-level roles, something gets lost: the winners will be the graduates who know how to wield AI with judgement.

These graduates will be of enormous value to companies, and it is our job as educators to prepare them. This moment should be a rallying point for business schools, an opportunity to bring unprecedented expertise to students and genuine value to employers.

Professor Bart Van Hoof Universidad de Los Andes School of Management, Colombia

What AI actually does To understand where early-career roles are heading, you first have to be clear about what AI actually does. AI works when you know what you want to begin with. Use it as an assistant, that does exactly what it's told and nothing more. If you use it as a senior advisor, it becomes a minefield, because you don't have the criteria to make the interpretations. As a student of mine wrote in his reflection essay: if you're stupid, AI makes you super stupid. The same is true of companies. One that deeply understands AI will use it to make operational processes more efficient, while protecting the critical paths and the critical teams. AI makes those teams more productive; it doesn't replace them. Students who have been trained in AI, and who have also invested time in upskilling themselves, will be of enormous value to companies. The truth is that many companies see AI as a steep hill to climb, and don't necessarily have the knowledge to maximise its impact. That's why graduates who can cleverly design how a company uses AI to its advantage will matter in this era of new job roles.

How we teach it It is the responsibility of business educators to teach both the opportunities and the limitations of AI within their courses, setting students on this upward path to success. 15

I actively encourage my students to use AI, for example in research and machine learning, because it enables them to build much larger datasets, with the caveat that it always rests on a clear methodological design. At Los Andes we're designing a course for a business project that teaches a consultancy method, using AI on three levels:

The first level is functional: the course is built on a manual, a step-by-step approach to managing a client and designing a project. We use AI as an alternative way to deliver that information; you can read the manual, or work through it with a bot.

The second level is feedback: students complete exercises in set formats, and we've programmed several models so that AI gives feedback on them. The professor accompanying the students receives this feedback too, so their own comments build on what AI has already given.

The third level is generative: when students upload a consultancy proposal, AI can generate several solution scenarios, and the students then discuss the different scenarios with their professor, explaining why they would choose one over another.

The result is that discussions become sharply focused, and the coaching time delivers immense value. I rely on the professors to understand AI's feedback so they can bring in the criteria the students might be missing. After all, AI is a tool, not the gatekeeper. The professors are the gatekeepers, and the result is higher-level contributions.

The responsibility ahead Ultimately, the academic system must teach what AI is, how to use it ethically and how not to use it. Rather than swimming against the tide, we must embed AI into our own teaching and research to deliver higher-quality outcomes for students as they move into their careers. Right now, rather than seeing only the negative impact of AI on jobs, there is a real opportunity for management students to be the front-runners in bringing AI into organisations ethically, as they step into the ever-changing world of work. It is up to us, as educators, to open the door to AI rather than block it, giving students the best possible chance of success.

Fluent in AI, but do you know who you are? The way the younger generation learns is changing so radically that universities and employers must prepare for graduate employees who will not need an instruction manual to use AI, because it will be innate. However, the tools are the easy part. The harder question is how we ensure that young people develop the identity and values they need to judge what AI gives back, use it creatively and ethically, and know when they are being misled.

Using AI tools will come naturally

Francesca Morichini Global Head of HR Electrolux Group

My son, who is fourteen, has never had training on AI, but he can do far more with it than many professionals. When he faces a problem, his first instinct is to ask whether AI can solve it. By way of analogy, when I started skiing I spent my first lessons learning to get down the mountain one ski at a time. Today instructors take a child of two and simply say, follow me, because what matters is not technique but the courage to go for it: you find your balance first and add the technique later. In that sense, current and future business graduates have a huge advantage. In the next few years they will have been fluent in AI since early childhood, so using these tools will be as natural as reading and writing. Yet the very thing that puts the next generation ahead is what risks leaving them exposed. Early-career professionals are being asked to step onto the second rung of the career ladder while the first - the one that used to build personal judgement - is becoming increasingly unstable. They do not always have the lived experience that teaches them to question what those tools give back, or to make the right choices.

The challenge is how we help them develop a strong sense of identity and clear values, which matters both for how they engage with AI and for their careers. There are a few key areas where educators and employers can intervene.

Deliberately help develop an identity and values base Instilling strong values, ethics and a sense of self, so that young people can navigate everything from manipulation to burnout, will matter more than ever. This sits with family, community and schools as much as with universities and employers. Young people develop their whole personality through experiences with real stakes, such as sport, volunteering, a part-time job, travelling, a cause they believe in. A robust value system is what allows a person to resist manipulation by AI, as they really know who they are. These experiences are also where you meet friction, which is what our epidemic of burnout is missing. Burnout is rising among young people despite the corporate focus on well-being, and I suspect that is partly because when everything is instantly accessible, life offers too little challenge to build resilience. It is the small frustrations the micro traumas as I call them - that teach you to cope when something hard eventually arrives.

Blend the university path more closely with hands-on work experience Once they join a company, graduates will no longer have the time to learn the operational side of a job from scratch over time, the way we used to, so universities need to fill part of that gap. Take recruitment for instance. Early in my career I filtered through thousands of CVs, and that is what built my instinct for a good candidate. Graduates today will not get those hours, so give them the equivalent during their studies: ask them to make the shortlist with AI, then prove it is sound. What would you have done to reach the same conclusion without AI, and is it the same? Why did you make those choices?

Question and adapt curriculum content The question for educators setting a curriculum is: what are the pivotal things that help a graduate build their identity and the capacity to think for themselves? I am a strong advocate for broader curricula built on foundational knowledge, rather than the highly specialised degrees we have drifted towards. When I was at university there were five faculties and everybody studied one area; then these splintered into over seventy narrow degrees. We need to bring those broader subjects back, so that graduates share a common base of knowledge rather than narrow technical experience.

University-employer partnerships are key None of this works without robust university-company partnerships, such as CEMS. Universities must grasp that companies today move at a vastly different pace from the academic world, and rethink their programmes accordingly, so that graduates arrive with identity, judgement and real experience, not only technical fluency. This doesn’t mean taking AI out of the curriculum; without it, students simply switch off. It is about guiding them to judge where the tools help and where they do not. Companies, in turn, need to recognise that a group of very smart young people with no identity is dangerous, so their job is to keep developing that identity once graduates arrive, through real responsibility, structured mentoring and a strong culture - whilst being conscious of the fact that they learn very differently from even ten years ago. The goal is not to shape graduates into technical experts; they are fluent enough already. It is to shape people with the judgement to use that fluency well, with a clear personal identity, learning agility and the flexibility to adapt. 18

Become More Valuable With AI Than Without It Can you guess which company this advert is for? "Product X speeds through thousands of intricate computations so quickly that on many complex problems it's like having 150 extra engineers. No longer must valuable engineering personnel, now in critical shortage, spend priceless creative time on routine, repetitive figuring." If you guessed an AI company, you're wrong. It's IBM, and the product is an electronic calculator. The advert is seventy years old.

Manuel Zorn AI Deployment Strategist Director at Salesforce, CEMS Alumnus 2019 (University of St.Gallen / Esade)

We've been here before We have been here before and fear has always outrun the reality. Think about what junior analysts at banks did fifty years ago: manual spreadsheeting and calculation, by hand. Excel arrived and automated all of it, yet investment banking is as competitive and as demanding as it has ever been. The work moved up; it didn't disappear. That is the part today's anxiety misses. The routine tasks that used to fill an entry-level role - the drafting, the data pulls, the initial analysis - are exactly what AI is now absorbing. But those tasks were never where the value sat; they were the toll you paid to earn judgement. The real question for a graduate is not whether that task work survives; it is how you build judgement, and a genuine understanding of the business, faster than the generation before you had to. In large enterprises, the blockers to gaining value from AI are rarely technical. They are human: old processes, people defending their own kingdoms, and years of accumulated technical debt. A graduate who understands both the business and the tools is enormously valuable precisely because those blockers are everywhere. Enable yourself with AI and you hold the same advantage the first internet-native generation held twenty years ago.

Become a builder So what should students and graduates actually do? The answer is anything and everything, honestly, as long as it makes you a builder. One of my mentees recently asked whether he should even mention on his CV that he is building a project with AI and with Claude Code. Absolutely, I told him. To him, being technically minded, it seemed obvious that everyone was doing this. In reality, plenty of his peers still don't know what an agent is. The builder terminology matters. Salesforce made a point of announcing it is hiring a thousand graduate "Builders" worldwide, mostly in the US, and we are putting money behind it in Europe too. Builders are junior employees we believe we can train quickly to do 70 to 80% of the work a senior would do. What a technology company (and what our customers) look for are people who can stitch something together. It doesn't have to be perfect; that is what you pay consultants for. But it has to be a start, and it has to show an understanding of the entire business process. Building is how you acquire that understanding at speed. Get your Claude, ChatGPT or Gemini subscription and ask: how can AI help me with this problem? Then build something out of it. It will take you far longer than simply doing the task once, and that is the point. You are not buying efficiency on that one task; you are learning to do something much bigger: you are getting “hands-on” experience that you cannot get from reading, studying or listening to a podcast. And you don't need to code: stitching a few agents together with point-and-click tools is absolutely fine.

Raise your hand This is also a great equaliser. Companies everywhere are struggling to find subject-matter experts who are happy to spend time experimenting with how AI can help them. The instinct I sometimes see in early-career professionals, to quietly resist technology in the hope of protecting their role, is exactly the wrong one. Raise your hand instead. Look at which problems exist around you and ask how AI could help. Experimentation is also how you learn where the limits lie. The person who insists AI can do everything is as unhelpful as the one who refuses to touch it. A solid, current grasp of what these tools can and cannot do is immensely valuable because it lets you push back with authority, even though those limits shift every week.

Grasp the chance to prove your value The goal is simple: be more valuable with this technology than without it. When I joined Salesforce in 2019, fresh from CEMS, I was on a consulting team where everyone had ten-plus years of experience. I had no chance of competing with them on technical or consultative depth. So I focused instead on an add-on analytics and AI product that was only two years old and still small. Within six months I was the go-to person on a team of very senior architects. That is the whole opportunity. Nobody has ten years of experience with these tools. You cannot out-experience the veterans on the old thing. However, you can become the most valuable person on the new one.

The job market changes but does not disappear For about a year I worried, like many, that AI would destroy many entry-level roles our CEMS graduates walk into. That no longer concerns me. Here are some of my thoughts. I write this as a researcher and lecturer at WU working on strategic problem solving and AI-augmented decision-making. I also build on my more recent experiences as a co-founder of an AI-native startup that focuses on building agentic automation for SMEs. Dario Amodei, CEO of Anthropic, warned in mid-2025 that AI could eliminate up to half of entry-level white-collar jobs within five years, and a number of indicators demonstrate real effects on the job market due to non-negligible productivity jumps on all levels of an organisation. On the other hand, (agentic) AI still has a number of serious (and interrelated) problems such as hallucinations, contextual knowledge and understanding, model choice, geopolitics-influenced model access, and excessive (and very convincing) confidence. The costs of compute have also gone up leading to the outcome that – for many tasks – humans may (continue to) be cheaper that AI systems.

Phillip Nell Professor of Global Strategy and Academic Director of CEMS at WU Vienna, Austria

New kinds of roles emerge Thus, while essentially all firms are experimenting with agentic AI and while there are some true effects, I do not believe that there will a massive shock on the job-market: it will change but not disappear. For example, the Frankfurter Allgemeine Zeitung, using Indeed data, just recently reported that German employers posted 288 new AI-focused job titles in the first quarter of 2026 alone – most of them outside the tech sector. What used to be a junior brand analyst producing weekly competitor reports shrinks into one task inside a bigger AI-managed workflow. Around that workflow appears another kind of role: someone who frames the questions, judges the outputs, coordinates the agents. Still market research, but not the same work. 21

Use AI seriously For graduates the implication is straightforward and I am not worried about this part: get foundational knowledge of AI (what are the core mechanics that produce these outcomes) and then use AI a lot, in many different ways and forms. Learn what these systems do well and where they fail. In other words, try to figure out the jagged frontier of the systems (if you do not know what a “jagged frontier” is then this is one of the first things to look up). AI-skills will, by the time you finish your degree, be taken for granted by employers and they will increasingly be at the core of AI-related jobs. Refusing to use and master AI seriously during your studies will, in a few years, look the way refusing to learn Excel would look today.

Do not skip the fundamentals However, there is also first evidence emerging that globally, social science students use AI in a suboptimal way. Cheating has gone up and, increasingly, many students use AI to produce content in a copy-paste way, especially in subjects in which they think they can get away with it easily. So far, this strategy works out for the most part because universities have not adapted fast enough. A recent study by Igor Chirikov of Berkeley found that, since the emergence of LLMs, the share of top grades increased much more in those courses that involve skills which LLMs are supposed to be good at (e.g., writing) compared to those which LLMs perform less well. That creates a real danger: if AI agents change many jobs, they will also change the organisational processes around them – approvals, hand-offs, escalation paths, incentive structures – all of which will need redesigning once agents sit inside these workflows. Doing this well requires a real understanding of organisation design, process management, incentives, principal-agent problems, and so on. These are "boring" fundamentals of a business degree, but they will decide whether a firm's AI adoption produces value or nonsense. Skipping this understanding because LLMs can produce well-graded stuff quickly, and without creating any real learning for the student, is not ideal. Someone who has not properly studied the fundamentals cannot design agent-infused organisations well and cannot ask the right questions. And because AI problems also still persist in what could be named “factual knowledge”, not developing subject-specific fundamental knowledge and understanding will also disable students’ abilities to check, qualify, and correct AI output. I try to deal with these issues in the following way: in my Strategic Problem-Solving course at WU I first cover key theoretical content without any AI, so that CEMS students work through theory and related case studies from scratch. Only later in the course do we discuss: where and how can AI be added to the mix? How can it sharpen my thinking and lead to deeper outcomes? Where does it fail and how would I know? We then try out AI-tools.

In summary As a student, use AI a lot to upskill yourself and enhance your own original thinking, because this will be the future. Not using it is nonsensical. However, do not use it as a substitute for the fundamentals of your business education, because that does not really work. The graduates who will do well are those who develop both – a real understanding of core business concepts and mechanisms, and the skills to use AI properly, efficiently and effectively.

How graduates can make themselves invaluable in an age of AI A conversation with Gianmarco Mazzocchi and Merthe Weusthuis, CEMS alumni working at corporate partner Whiteshield, who discuss how, as AI reshapes early-career work, the opportunity lies with graduates who can go the extra mile.

Gianmarco While it’s true that there’s a downturn in the job market, the causal link between that and the rise of AI is still to be proven. I don’t believe the reduction in entry-level jobs is going to be structural or permanent. Many companies have been too aggressive in their plans to replace employees with AI tools, but the real cost is starting to show.

Gianmarco Mazzocchi Head of AI Economics at Whiteshield, CEMS Alumnus 2019 (Esade/ HEC)

Replacing a junior resource with AI tools alone isn’t really a big cost saving; in fact, it can often be more expensive, and if you’re doing it to automate generalist or low-level tasks, it’s simply not worth it. We’re now starting to see companies go back to hiring junior resources and interns to bring those AI costs down.

Merthe Continuing to hire graduates is crucial for the leadership pipeline. We’ve always found it difficult to hire externally at a senior level; our leaders have nearly always come up through the ranks. These are people you can gradually build into Merthe Weusthuis exceptional managers and senior leaders at the firm, Head of Product at Whiteshield, particularly coming straight from university. CEMS Alumna 2020 (RSM/ WU)

Gianmarco For me, the issue is not that AI takes jobs, but that it risks taking away everything that makes a candidate hireable and trainable. AI can build slides for you and create reports, but if you also outsource thinking when a client has a problem and copy a solution from ChatGPT, then there is a serious pipeline issue. The danger is that everyone starts to sound the same, making it hard to find highly trainable graduates in two or three years.

Merthe On the other side, this is a moment for graduates to really differentiate themselves and prove they have what it takes. Everyone has the same tools now, so what distinguishes hireable graduates is how they use AI and the judgement they bring to the table. For example, we can immediately see a difference between someone who has copied and pasted an answer from AI and someone who has prompted it, had a discussion, asked follow-up questions and steered the tool in the right direction. AI has the potential to increase the quality of work exponentially if you use it in the right way; not because of its raw power to be creative, but because it can take away all the work that previously took you several days, freeing up your time for innovation. The graduates who put in the effort, guide AI in the right direction and challenge what it produces, will place themselves well in front of their peers. AI can take them further and help them achieve more than they ever could alone.

Gianmarco There’s also so much you can do on your own as a recent graduate to get ahead in a challenging job market and showcase your skills to employers. You don’t need a big team of colleagues because you can use AI tools to provide that ecosystem.

Five tips to get ahead in the job market in an age of AI

01.

Understand as deeply as possible how to use AI and integrate it into your work processes to enhance outputs. The ability to ‘babysit’ AI is still extremely important today.

02.

As well as internships, do projects on your own. Set up a small startup, or even a fake one as a portfolio. Develop models against a common online problem, host them on a self-designed website, and build the infrastructure to demonstrate at interviews.

03.

Build your personal brand. Produce two or three original articles you’ve written yourself, showing your own thinking on a topic relevant to the company or industry to which you are applying. Good writing signifies good thinking and challenges the critical thinking skills that matter most now.

04.

Post original content on LinkedIn, share resources, join online networks, attend conferences. Show employers you’re active and building your own thought leadership - not the way 80% of LinkedIn does it now, with AI writing the message.

05.

Never underestimate personal connection. For example, anyone can talk to us at career fairs, but most interactions are flat and often AI-generated. Making the effort matters: everyone has the same exposure, so don’t waste the opportunity to make a big impression. The job market rewards effort, not volume.

Why entry-level recruitment remains a smart business choice As the global business landscape continues to evolve, AI and digital transformation is just one of many topics discussed at multinational organisations, but it’s also a very important one. There is significant discussion around how AI will impact jobs, specifically entry level positions. This is a topic we, at Henkel, revisit while at the same time already implementing tools; but it’s fair to say that we are still at an early stage overall.

I clearly see the benefits behind AI and how workplaces can transform to make more impact. What I am convinced of is that AI will change the way people work, not only for some, but for all of us. However, what I don’t believe is that entry level opportunities will be dismissed at large scales. From a business perspective, cutting new graduate hiring out of an organisation completely, is not a smart option. Frank Steinert Global Head of HR Regions at Henkel

If you go to the extreme and say, we are not hiring entry-level positions you may have created a significant risk for future growth. A few years down the road, the natural career progression of your leadership pipeline breaks down and as a result it also negatively impacts your company culture, something you built up diligently for years or decades. It's that simple. Take the foundations away and, while the cracks may not show up immediately, they will show at one point in time and that’s unavoidable. At Henkel, many colleagues have been with the organisation for a long period of time; 20 years or more. You cannot buy in the institutional knowledge, context, culture, and ingrained company values these colleagues carry. This is something vital to our organisation and this will be vital for the generations to come, too. These colleagues grew with Henkel, many of them in one entry-level cohort at a time, and are the reason a community holds together strongly.

The foundations still matter There are roles at the entry level where the impact of AI is likely to be greater than others. Junior roles that entail in large parts analytics, basic customer-service functions, and pure administration will likely be more affected by AI than more human-centered roles such as those in labs, sales, manufacturing, or engineering.

Regardless of the roles and the degree of AI impact, you still need people who have built the foundational skills in their professions. Someone has to understand the task from the ground up before they can effectively utilize and supervise the technology doing it. If you never bring talent in at that level in the first place, in a few years you've automated away not just a set of tasks but the background knowledge too.

Capability, not redundancy When we talk about AI strategy at Henkel, we ask ourselves a few questions. How can we benefit as an organisation from AI? What capabilities and skills do we need from our people? What are the preconditions we have to create and the mindset required? AI is about capability, not redundancy. Personally, I am convinced that AI literacy, changefulness, agility, empathy, adaptability, problem solving capability, natural curiosity, and a mindset of life-long learning will be the key success factors. Arguably, they are important now and have been in the past; however, I strongly believe that they will be absolutely essential for success in the future. I am often asked whether hiring at Henkel has changed due to AI, I'd say that while there is always a fluctuation in hiring, much of that is due to economic cycles. As of right now, it remains a challenge to directly track if AI has impacted those numbers. I think it is important to be honest about that distinction rather than using technology as a quick and knee-jerk explanation. For Henkel, we will continue with our trainee and rotational programs, confident that this is going to support us in becoming even more successful in the years to come.

What is really at stake When I look at the current generation of students and graduates, overall, I'm very optimistic. These are digital natives, having grown up with technology, so they should enter the workforce with a degree of confidence that they can make a difference. Graduates will need to adapt, of course, the way previous generations had to adapt 20, 30, 40 years ago, with the dawn of the PC, internet, Google, and now automation and AI. But if they are mindful and able to pivot swiftly, the future will be bright!

I'd encourage companies to embrace AI. Those that adapt will bring in the generation that has grown up with technology, while continuing to build the pipeline of employees who understand the work from the ground up. While AI will continue to reshape how work gets done— the need to attract, develop, and invest in early-career talent remains unchanged. Entry-level hiring is not just about filling roles today—it is about building the expertise, culture, and leadership that will drive the business tomorrow. By embracing innovation while continuing to create opportunities for the next generation, companies can ensure they are not only prepared for the future of work but actively shaping it. 26

Key Takeaways These takeaways draw together what our contributors told us about the future of early-career work in an age of AI. There is no doubt that the graduate job market is difficult, and some roles will go, though how much of that is down to AI rather than the wider economy is still far from clear. How well graduates navigate what comes next

Key 3

Key 2

Key 1

will depend on how closely they, their educators and their employers work together.

In most cases, the rung is moving, not missing. Routine drafting, data pulls and first-pass analysis are being absorbed into AI-managed workflows, but new roles are forming around them: someone still has to frame the questions, judge the outputs and coordinate the agents.

Continuing to hire graduates is crucial: the leadership pipeline depends on it Senior people are grown from the ranks, one cohort at a time, and the organisational knowledge and values they carry cannot be bought in. Choosing not to hire graduates risks negatively impacting the company culture you have built up diligently for years. Replacing juniors with AI is rarely the saving it appears to be, which is why many employers are already reversing course.

Early career development must be deliberate The workplace basics that once accumulated slowly on the job can no longer be picked up that way. Employers need to build both technical and softer skills into onboarding, through real responsibility, structured mentoring and learning programmes, as well as a culture that encourages experimentation and treats failure as learning.

Key 4 Key 5

Judgement is what makes graduates hireable The real risk is not that AI removes jobs, but that relying on it removes the judgement and critical thinking that makes a candidate worth hiring and developing in the first place. A graduate who copies a chatbot's answer is easy to spot. What distinguishes early-career professionals is how they steer AI creatively: prompting, questioning, challenging and improving what it returns.

Key 8

Key 7

Key 6

AI fluency is a springboard, but only for graduates who go further No-one has a decade of experience with these tools, so AI-fluent recent hires can become in-house pioneers within months. However, using AI will soon be assumed, so doing the minimum will not be enough. The graduates who stand out to employers will be able to demonstrate that they are "Builders" who can stitch tools together into something that works end-to-end: a working demo, a side project or even a mock startup that shows how they think.

AI fluency without a sense of identity is a liability Developing values, interests and a point of view is crucial for graduates to stand out in a crowded job market. Importantly, knowing who they are enables them to judge the value of AI output, resist manipulation, make ethical choices, avoid burnout and have a clear sense of what they want to contribute. Identity is built from experiences and pursuits with real stakes, such as sport, music and travel.

Business schools have never mattered more, so must embrace AI The dawn of AI has raised the bar for graduates, and with it the responsibility of the business schools that prepare them: to send AI-savvy, responsible young people into work ready to make an impact straight away. Restricting AI in the name of critical thinking is no longer a reasonable option. The stronger response is to redesign assessments to surface each student's own contribution and knowledge, then have them build on it with the latest tools. Teaching the "jagged frontier", where these systems are strong and where they fail, is also crucial to help students make informed, ethical choices.

Business-education partnerships are more important than ever Curricula have to keep pace with a business world that moves faster than the academic calendar. Close academic-corporate partnerships, such as CEMS offers, make that possible. Real projects, cases and internships give students the operational grounding they will no longer absorb slowly on the job and enable them to experience AI in a real setting. Employers, in turn, gain early access to talent and to responsible, AI-fluent leaders of the future.

INSIGHTS The following pages set out a series of insights for companies and their leaders, for educators at universities and business schools, and for early-career professionals. All are drawn from the ideas of contributors to this report: experts from across the global CEMS community.

Ten insights from our contributors for employers and business leaders Treat entry-level hiring as a strategic advantage, not a cost. Entry-level hiring is not just about filling roles today - it is about building the expertise, culture, and leadership that will drive the business tomorrow, while investing in the people who will shape its future. Run the real numbers before replacing a junior. Replacing a junior resource with AI tools alone isn’t really a big cost saving; in fact, it can often be more expensive. Some employers are already reversing course. Frame AI as a question of capability and mindset rather than redundancy. Keep human judgement in how you hire. Automated screening can reject a strong candidate in a fraction of a second, often those from non-traditional backgrounds who do not fit a template. Students told us this is one of our biggest fears about entering the workforce. Keep a person in the loop, so that potential rather than keyword-matching decides who gets through. Protect your critical teams and paths. Use AI to make your strongest people stronger still. Companies that understand technology deploy it around their critical work, not through it. Develop graduates deliberately and patiently once they arrive. The grounding that once accumulated slowly on the job now has to be built by design, through real responsibility, structured mentoring and a strong culture, where people have the confidence to learn, question and grow. Embrace the AI fluency new joiners bring. Nobody has a decade of experience with these tools, so position graduates to pioneer AI inside your teams. A motivated new hire can become your in-house expert within months. Reward the builders. Value the people who can stitch tools and agents into something that works and who understand how the whole business fits together. It need not be polished, but it must show they grasp the process from end to end. Remember that the blockers are often human, not technical. Old processes, defended territory and years of accumulated technical debt, rather than the technology itself, are usually what stop AI from creating value. Retain the people who understand the work from the ground up. Even in the roles AI changes most, someone still has to know the work well enough to “babysit” the technology doing it. Automate that grounding away and you lose the ability to judge whether the output is any good. Partner closely with business schools and universities. Give students real projects and genuine exposure to how AI shapes decisions. The graduates who arrive ready are the ones that employers helped prepare, and by collaborating with educators you help them keep pace with a fast-changing world of work while developing not only technical capability, but also judgement, responsibility and a sense of purpose. 30

Ten insights from our contributors for educators of responsible business leaders Seize the moment. Graduates who know how to wield AI with judgement will be of enormous value to companies, so use this moment as an opportunity to bring unprecedented expertise to students and genuine value to employers. Embrace AI in your teaching. Rather than swimming against the tide, embed AI into your own teaching and research, and equip students with the practical skills they are asking for, from effective prompting to automating workflows, so they graduate genuinely fluent. It is up to educators to open the door to AI rather than block it. Use AI at many levels. Let it deliver content, give feedback and generate scenarios for discussion, with the professor as the gatekeeper who supplies the criteria students would otherwise miss and ensures higher-quality contributions. Don't skip the core concepts. Being able to redesign organisational structures will require a real understanding by graduates of the fundamentals, including process management, incentives and principal-agent problems. Assess personal contribution. Continually redesign assessment so a student's own reasoning is visible. For example, asking them to learn a topic quickly and then present it proves the understanding is theirs. Build human skills. Even in a technical course, cultivate the wider capabilities that travel across a changing workplace, such as clear communication, ethical reasoning, problem framing and the ability to work across disciplines. Fill the grounding the workplace no longer provides. Graduates will not get the slow hours that once built instinct, so give them the equivalent during their studies, through real, specific business scenarios in which they have to weigh evidence and make informed decisions. Teach the "jagged frontier". Show students where these systems are strong and where they break, so they learn to check, qualify and correct what AI produces. Build identity, not just fluency. Help students develop a clear sense of self: values, taste, interests and a point of view. Redesign programmes so they shape well-rounded, interesting people, not solely technical experts. Partner with global employers. Make sure you understand their pace and requirements, and rethink your programmes accordingly, so you can prepare graduates who arrive with both identity and judgement.

Ten insights from our contributors for early-career professionals Use AI with purpose. Don't ask only what AI allows you to do, but what it enables you to contribute. The graduates who stand out will be those who combine technological fluency with sound judgement, curiosity and critical thinking - using AI not only effectively, but responsibly. Grasp the unique career opportunity AI presents. Through enabling yourself with AI you will hold the same advantage the first internet-native generation held twenty years ago. AI can take you further and help you achieve more than you ever could alone. Learn how tools work, use them intentionally. Understand as deeply as possible how AI works, its strengths and its limitations, and integrate it into your processes to enhance your work. A command of AI is fast becoming the baseline employers assume. Become a “Builder”. Take on your own projects - whether a working demo, a small startup or even a portfolio built purely to show your thinking. Making something that works from end to end gives you a cooncrete example to take into an interview. Aim for an excellent result, not just a result. Anyone can get an answer out of AI. The skill, and the value, is getting an excellent one and knowing why it is good. That difference is exactly what separates a graduate an employer wants to develop from one whose work they could have produced themselves in seconds. Steer AI, do not copy and paste. Most employers can tell the difference instantly. Prompt, question, challenge and follow up, so your judgement shows through the work. Raise your hand. Companies everywhere are struggling to find subject-matter experts who are happy to spend time experimenting with how AI can help them. Be the one who volunteers to evaluate where AI could help your team, and to share what you find. Pursue real interests. Sport, music, art or a cause with real stakes build taste, resilience and identity. Build a clear sense of who you are and what you value, through experiences beyond your studies, because that is what lets you use AI rather than be used by it. Seek out and cherish human moments. The skills of presenting, building trust and managing a client are growing more valuable as the routine work is automated. Seek out the moments that build these, since they are the skills an employer can’t get from a chatbot. Do your part in genuinely caring for the others around you, enabling their growth. Stay adaptable. Don’t bet everything on one tool. The specifics of jobs will change fast, so keep your options broad and your skills spread, which is what enables you to pivot. Build your personal brand. Write original pieces, share your authentic thinking on social media, connect in person. Effort stands out in a job market flooded with AI-generated sameness.

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The Missing Rung? AI and the Future of Entry-Level Work