As organizations adopt AI at scale, many workers fear losing their jobs. HR teams can help them through this transition by teaching them to work with the machine rather than against it.
A Future of Jobs report from the World Economic Forum (WEF) finds that 86% of employers expect AI and information processing technologies to fundamentally transform their business model by 2030. According to the same study, an average of 39% of current skill sets will be transformed or become outdated by 2030.
Little wonder that many workers fear being replaced. "That fear is justified," says Laurent Pilliet, associate director at La fabrique digitale RH, which helps organizations navigate this technological shift. "That said, people tend to see the glass as half empty: AI is also going to create opportunities we can't yet imagine." The WEF study bears him out: structural transformation of the labour market is expected to eliminate roughly 92 million jobs while creating about 170 million others — a net gain of 78 million.
What if, instead of talking about replacement, we thought about a new division of tasks between humans and AI?
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How Should Work Be Divided Between Humans and AI?
Despite workers' fears, research from the MIT Sloan School of Management suggests AI is more likely to complement them than replace them. Laurent Pilliet points to consulting as an example: the role once involved a great deal of documentation work and press reviews. Today, search engines and databases have dramatically cut the time spent on that task, yet every skill tied to advising clients remains just as relevant. "A job doesn't disappear just because the way its tasks get done evolves," he argues.
AI is already widely used by HR teams for repetitive work and data entry: drafting documents, building presentations, entering expense accounts and expense claims, or preparing salary increases. Other tasks, though, can only be done by a person. "For instance, AI can screen resumés, reach out to prospects on LinkedIn, even schedule interviews — but meeting candidates, understanding what they need, choosing the right person for a role, presenting an offer that fits their salary expectations: those are tasks a human has to carry out," Pilliet explains.
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Talk to our expertsWhich Skills Will Gain the Most Value?
According to the WEF's Future of Jobs report, the skills currently considered essential in the labour market are:
- creative thinking
- resilience
- flexibility and agility
- curiosity and lifelong learning
The fastest-growing skills through 2030 will be:
- artificial intelligence and big data
- networks and cybersecurity
- technology literacy
According to Laurent Pilliet, HR teams would do well to start prioritizing candidates who learn quickly and can adapt to change. He also offers this prediction: "We're going to need people who are exceptionally good with other people, because the bulk of some roles will come down to the client relationship."
Read more: The End of the Traditional Resume: The Rise of Skills-Based Hiring
How Should Organizations Prepare for This New Division of Work?
The scale of reskilling ahead is considerable: roughly 59% of employees worldwide will need training by 2030, according to WEF estimates. Employers are better off investing in their human capital now. "The sooner they start supporting their people, the smoother the transition will be," says Pilliet.
He suggests HR teams begin mapping jobs now to identify which will be most affected. AI can actually help with this otherwise time-consuming exercise. The approach:
- Break jobs down by task and assess how automatable each one is. Entering variables into a payroll system, for instance, can be handled by AI.
- Build targeted training plans to develop new skills. Payroll staff, for example, could learn to supervise and configure an AI agent to handle that task.
- Support staff through the transition. As the AI agent becomes more reliable, the employee gradually moves away from data entry toward validating and reviewing the work produced.
"It's a process that takes time," Pilliet notes. "You don't just have to train these people — above all, you have to prepare them psychologically. They need to realize that if they want to keep their job, they have to evolve."
A learning management solution built into the HRIS is what connects that skills mapping to individual development plans, without starting from scratch each cycle.
Read more: People Analytics: How to Use HR Data Strategically
How Do You Protect Workers' Employability?
HR teams are on the front line in helping employees make this transition. "They have to act as the bridge between leadership, which has a vision for how AI will serve the business, and employees who may feel overwhelmed," Pilliet explains.
Some will adapt to this new paradigm easily; others will struggle. For the latter, more sustained support will be needed. "For a smooth transition, we'll need to identify which tasks these people can take on without straying too far from their existing skills," he suggests.
In his view, HR teams need to be carriers of hope: "Even if some roles do disappear, there are other things we'll be able to entrust them with."
To go further:
FAQ
Will AI actually destroy jobs?
The World Economic Forum estimates roughly 92 million jobs will be eliminated by 2030, while 170 million will be created — a net gain of 78 million. The real challenge isn't work disappearing, but moving workers from one type of role to another.
Which HR tasks can be handed to AI?
Repetitive, low-value work: drafting documents, building presentations, data entry, initial resumé screening, interview scheduling. Judgment, the candidate relationship, and the hiring decision stay human.
Which skills will gain the most value by 2030?
According to the WEF, artificial intelligence and big data, networks and cybersecurity, and technology literacy will grow fastest — alongside human skills like creative thinking, resilience, and agility.
How many workers will need reskilling?
The WEF estimates roughly 59% of employees worldwide will need training by 2030.
Where should a job mapping exercise start?
By breaking each role down by task, assessing how automatable each one is, then building targeted training plans. AI itself can speed up this otherwise very time-consuming exercise.