The creaking career ladder is now a bungee jump – prepare your students for a multi-career world

For many people, their “career” is singular journey and simply means climbing the ladder towards their ideal job. 

But today the new normal means being good at many different jobs, all at the same time. For Gen Z, their futures lie in multi-faceted careers – and universities need to help prepare them for this.

Modern graduates aren’t just sitting around waiting for an ideal role to land. If this doesn’t sound familiar, pause for a moment and look at your own students. 

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Young people today want variety, flexibility and the rapid take-up of multiple projects, rather than a lifetime of office drudgery, stuck at the same desk and facing a narrow careers pathway.

They seek high levels of autonomy, stimulus and a faster pace of development than the old, tired route of slow promotion and occasional advancement.

Imagine replacing the old, creaking career ladder with a bungee jump. Movements are rapid, up, down and even sideways, all with high levels of exhilaration along the way.

For example, I work with over 1,000 students in both North Africa and North America. Our experiences find these GenZs are only accepting entry-level roles, regardless of the big names or big pay, if employers allow three days working remotely and working on side gigs. This goes against prior generations’ priorities when choosing jobs.

Universities that keep training students for single, linear careers can leave them behind, and those employers demanding five days in the office are losing talent to their more flexible competitors. 

Likewise, universities that don’t reflect remote working environments, experiential work-based learning and AI tool adaptation will handicap their graduates in the multi-career world.

A new role for AI

AI tool adaption needs the same curiosity and agility that the advent of the internet and, later, the smartphone required. 

Remember when universities had computer labs with controlled access to the internet? Or when faculty required students to “leave the phones in the basket” when they entered a classroom? 

Each of these technological interventions required about 10 years for us to create norms for usage. We are seeing this same repeat with AI tools.

It’s true that some professions will shrink or change radically, like research, consulting, software development and financial services sectors, including risk management and fraud. But this is not new. 

There was a time the internet threatened libraries; when robotics threatened blue collar workers. If we remember this, then we can learn from history and re-forecast how AI will replace certain tasks, and create new multi-career jobs.

So what should do faculty do? Based on history and forecasting, I recommend three strategies:

1. Curiously embrace AI to collaborate and accelerate

It’s important to embrace AI in order to accelerate student learning and performance. 

For example, instead of teaching students how to write a report on East African governments, you teach them how to write the best queries, understand which data sets will offer valid African data and how to evaluate the AI’s responses. 

This means faculty must first use the tools themselves. If you are an expert on risk management, you must become an expert on which AI tools and prompts provide the best results and then teach these in line with larger strategic goals. 

Faculty need to double-down on the value of human judgement, ethics and context in order to teach students how to use AI. The opportunity is for students to learn how to write strong prompts, debug inaccuracies and use AI as a collaborator and accelerator, not a replacement.

We are already seeing the bottom rungs of the career ladder reconfigure. In the last year alone, our work with 250 global employers indicates that for every four junior positions previously hired, they are now hiring just one. This is because AI is reducing the requirement for junior roles, and supervisors have become more effective with AI and need less junior support.

2. Use experiential and work-based learning for realism

The most effective responses are experiential and work-based learning. Experiential learning mimics professional pressures and is replacing the use of passive case studies. 

At my university, we host monthly corporate gamification events, which act as live simulations with corporate partners to help students perform under real-world time and conflict constraints that can’t be simulated in a classroom. 

Similarly, we’ve blended the North American best practices of co-ops – Drexel and North-eastern – which reflect best German practices for work-based learning and put students in environments with 100 employers across Morocco while they complete their studies. 

Drexel's co-op programme is 110 years old and features one of the most successful initiatives in the US market, while North-eastern has one of the largest comparative operations. This work-based learning is mandatory for all students and results in high levels of employability.

Our goal is that 75 per cent of all students have between 12 and 18 months’ work experience in this “alternating” scenario. 

Using these methods, I’ve seen students work though five-hour game-based assessments at a reinsurance firm. And then, two hours later, the employers hire them. 

I’ve also witnessed students complete a strategy for eliminating a cash-based culture in a weekend - and then, during the award ceremony, receive job offers and entrepreneurial investments.

3. Extend to cross-generational working

Universities also benefit from embracing cross-generational learning in the classroom and workplace because we are seeing all five generations, from baby boomers to GenZ, in work environments.

In one instance, we had a German logistics firm put mid-level engineers into joint classroom projects with students, so that each side understands the other’s strengths and blind spots.

These programmes serve to reduce friction, build empathy and teach managers how they can benefit from younger colleagues’ AI fluency. For academics who might be worried about obsolescence, treat this as a learning curve, not the end of the road.

So what should universities and faculty actually do to keep up with these changes? Here are five practical tips to use in employability and entrepreneurship:

Top tips for employability in a changing world

1. Normalise multiple roles: Teach time management, expectation setting and ethical disclosure, so students can hold concurrent jobs without conflict.
2. Build simulated junior experiences: Replace some traditional internships with intensive, live project games that demonstrate real capability.
3. Make AI fluency universal: Embed practical AI tools into every course and teach students prompt craft, verification and bias awareness.
4. Create cross-generation partnerships: Invite industry mid-managers and alumni into classrooms to work alongside students and build mutual understanding.
5. Prioritise experiential teaching design: Flip content delivery outside of the classroom and use short, active and in-class exercises that change every three to five minutes.

Altogether, it is crucial to channel curiosity into structured practices that build resilience and good judgement.

Finally, don’t let nostalgia dictate policy. If you can’t beat the new tools, join them, learn from them and find new value in human expertise. The internet once prompted cries that calculators would ruin the study of mathematics. Those predictions were wrong, and the same is true of the current hand-wringing about AI.

If universities steer toward experiential learning, AI literacy, ethical multi-employment and cross-generational practice, we will ultimately produce graduates who are adaptable, creative and trustworthy.

This will keep them employed, useful and fulfilled in careers that are no longer linear, but all the richer for it.

Deborah Bartlett is chief employability and entrepreneurship officer at Al Akhawayn University.

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