Dr Vivek Soundararajan from the University of Bath discusses how learning and training is changing for the workforce of tomorrow following the advancement of AI.
For a long time, the multitasking agreement was simple enough. Entry-level employees perform routine tasks to receive training, skill development and clear career paths.
This program meant that employers had affordable jobs, and workers received training and a clear career path. Both sides benefited.
But now that is changing it collapses. AI is doing the grunt work for itself – the repetitive, boring but important tasks that young people used to do and learn from.
And the results hit both ends of the workforce. Young workers cannot find a place to stand. Older workers are watching the talent pipeline dry up.
For example, one study suggests that between the end of 2022 and July 2025, entry-level employment in the US in AI-exposed areas such as software development and customer service fell by nearly 20pc. Employment of older workers in the same sectors increased.
And that pattern makes sense. AI is currently leading the way in administrative duties – things like data entry or filling. But it struggles with nuance, judgment and a plethora of other skills that are hard to muster.
So experience and the accumulation of those skills becomes a defense against the migration of AI. But if entry-level employees don’t get the chance to build that experience, the savings never get built.
This is also important for organizations. Researchers using a large amount of data about employment in the US have explained how to develop professional skills over time, by matching the work methods to the tree structure.
General skills (communication, critical thinking, problem solving) make up the personality, and then special skills come out of that.
Their key finding was that the wage premiums for specialized skills depend entirely on having those basic skills that are less common. Communication and critical thinking skills are not optional extras – they are what make advanced counseling skills.
The researchers also found that workers who do not have access to basic skills can be locked into career paths with limited upward mobility: what they call “skilling”. This structure has become more prominent in the last two decades, creating what researchers describe as “barriers to career growth”.
But if AI eliminates the entry-level positions where those foundations were built, who develops the next generation of professionals? If AI can do small tasks better than real people, older workers may stop delegating altogether.
Researchers call this “lack of training“. The little one doesn’t read, and the pipe breaks.
Uneven disturbance
But the disruption will not hit everyone equally. Wantedfor example, that women face almost three times the risk of having their jobs replaced by AI compared to men.
This is because women is often more likely being in clerical and administrative roles, which are among the most exposed to AI-driven change. And if AI closes off traditional routes to skilled work, the results are less likely to be evenly distributed.
So what can be done? Well, just because the old collective bargaining agreement between junior and senior staff is broken, doesn’t mean a new one can’t be formed.
Young workers now need to learn what AI cannot replace in terms of knowledge, judgment and relationships. They need to seek (and be offered) roles that involve human interaction, rather than just screen-based tasks. And if traditional entry-level jobs disappear, they need to look for structured programs that still offer real skill development.
Older workers, meanwhile, can learn a lot from younger workers about AI and technology. The concept of mentoring can be reversed, with younger students teaching new tools, while older ones provide guidance and instruction in nuance and judgment.
And employers need to resist the urge to cut off young workers. They have to keep sending to those workers – even when AI can do the job much faster. Entry-level roles may be restructured rather than eliminated. Finally, if the young ones are not trained, there will be no one to give him.
Protecting the pipeline of skilled and valuable workers is in everyone’s interest. Of course, some types of technology will become less important in the age of AI, distracting people who may have invested years in developing them.
But expertise is not necessarily about retaining knowledge. It is about refined judgment applied in difficult situations. And that is always valuable.
Written by Dr. Vivek Soundararajan
Dr Vivek Soundararajan is a professor of labor and equity at University of Bath. He conducts research on labor rights management in supply chains, inequality in and around organizations and the future of work. He leads a research program called Embed-Dignity and works as deputy director of the Center for Business, Organizations and Society (CBOS) at the University of Bath.
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