How to start building a career in the age of AI?

Internships and apprenticeships have long been effective for graduates and young adults to test their learning, develop new skills and secure employment. For organisations, they provided a way to identify potential hires.

However, recent advances in artificial intelligence and agentic systems are quickly making this ‘on-the-job’ learning and hiring channel vulnerable – much to the dismay of students and young adults.

Many organisations are now rethinking entry-level roles and budgets, increasing AI spending while reducing these positions. This shift raises questions about career prospects for those looking to build a future in the coming decades.

Let’s start with the basics. A career is a long-term professional journey marked by skill development, mobility and rewards. This journey has become increasingly chaotic for successive generations, but the biggest change began with Gen X (those entering the workforce between the mid-80s and mid-90s).

Gen X witnessed a major shift in employment that challenged the traditional linear progression theory, where people typically start and end their careers at a single company. They entered a job market that valued individual competency over loyalty.

Looking back, we can see how the Internet, personal computers and globalisation transformed the stable job market of the Silent Generation. These changes flattened organisational hierarchies and created a new, laterally mobile talent pool. However, a deeper analysis reveals a hidden pattern: a world in flux that needed a new breed of talent.

The world was shifting away from Abraham Maslow’s ‘Hierarchy of Needs’ theory towards David McClelland’s ‘Human Motivation’ theory. While both ideas centred on individual needs and growth, McClelland’s theory removed the rigidity of Maslow’s. He realised that individuals don’t necessarily need to follow strict hierarchies to achieve fulfilment. Instead, people can meet their needs in non-hierarchical and non-linear ways.

Competency became the most crucial factor for growth and career advancement, surpassing loyalty and years of experience. Learning new skills led to promotions or switching to companies offering higher pay for those skills. This fluidity in the job market allowed people to move laterally and explore new industries and roles.

While formal skills and advanced degrees still commanded premiums, large language models—codified knowledge from textbooks—have nearly absorbed all existing digital formal knowledge. This disruption is affecting talent flow at the entry level and changing hiring practices.

In this future workforce, entry-level positions will begin with young professionals building augmentative working mechanisms using agentic AI systems.

Today’s job market demands that career builders to view existing AI tools as learning facilitators rather than task finishers. This distinction is vital because any AI-performed task diminishes the human element, which is something you’d rather avoid. Ideally, seek roles that allow you to develop skills by enhancing your learning outcomes through AI tools. This is the sweet spot to be in as the current crop of AI tools offer a range of options for those curious to learn and do.

Also, this approach will gradually build a solid foundation, enabling you to add value to your profile and direction for your next move. It will also cultivate the right mindset to seek and build human-centric roles.

It’s inevitable that AI agents will displace some jobs but new ones will eventually emerge. However, this development is beyond your control at the moment. Instead, you’ll be shaping it through augmented employment. For organisations, this is the perfect time to rethink talent pipelines as they experiment with AI agents across various tasks and functions. A checklist on the best and worst cases from their AI deployments will help them identify areas where human factors remain crucial even as AI systems advance.