Companies planning for great realignment of labour for AI age

With excitement around agentic AI on the rise, many companies are planning for a labour-realignment they believe it will necessitate. Most than six-in-ten executives have told BearingPoint they are using reskilling and training initiatives to shift workers from areas of ‘over-capacity’, to places where AI-related skills are scarce.

While investments in artificial technology continue to accelerate, business excitement around the technology has noticeably cooled in 2025. With landmark reports finding AI projects had benefitted fewer than one-in-ten organisations, and talk of a ‘bubble’ increasing – as leading players in the AI software sector continued to post colossal losses – Agentic AI has increasingly been presented as the last great white hope of the technology to actually deliver on its promise.

Unlike traditional models, the proponents of agentic AI claim the systems can ‘learn’, ‘reason’, and ‘act autonomously’ to ‘solve’ complex, multistep problems. In theory, this enables a model to refine its decision-making over time, leading to improved outcomes. And the excitement around it might be said to be palpable in a new report from BearingPoint, which found bosses claiming they were already planning for the “over-capacity” it was expected to cause.

For many years, it has been said that the productivity boost delivered by the speed and accuracy of AI in repetitive roles would mean large numbers of jobs in back-office, administrative or customer service functions would become redundant. But rather than simply leading to widespread unemployment, it has also simultaneously been argued the technology would require new human roles to be created, to get the most of it.

Polling 1,010 C-level professionals from business-to-business organisations in August 2025, BearingPoint’s ‘How agentic AI is reinventing organisations’ paper found that companies are beginning to contend with that workplace ‘realignment’ long hinted at by AI’s biggest champions. Within three years, all companies surveyed claimed they would experience at least 10% overcapacity, while 45% expected to manage 30% to 50% excess capacity thanks to the efficiency of agentic AI.

Conversely, the AI-induced transformation is also said to be creating acute talent shortages in new and evolving roles. Demand is surging for individuals who can build, orchestrate, supervise, and fine-tune AI agents — from prompt engineers and domain-specific model trainers to AI ethicists and agentic workflow designers. A 44% chunk of C-level executives estimated the shortage of staff able to work effectively with AI at 40% to 60% – while 47% of executives still forecast a 20% to 40% shortage of AI-savvy talent by 2028.

In terms of the action being taken, BearingPoint found that 66% of firms are prioritising upskilling and reskilling initiatives – while 57% are hosting regular reviews for their workforce planning functions. Alongside a number of other options, this suggests that realigning staff, over simply laying them off to let AI do everything is the most common source of action. Much of that may hinge on the economic health of firms heading into the coming era, however – after all, everyone has a plan until they get punched in the mouth. And as growth continues to slow across the largest companies implementing AI, some like ABN AMRO seem to panicked enough to simply roll the dice on AI, and lay off large numbers of workers.

Even as those cases catch the eyes of headline writers, though, however, it remains the case that many other firms are yet to be convinced that AI can really fulfil its promises. After three years of heavy-hype and inflated valuations of the tech companies peddling it, BearingPoint found that 17% of executives are still expecting a return on investment within one-to-two years – while a majority anticipate benefits would materialise over a three-to-seven-year horizon. Worse, close to two-in-five respondents told the consultancy that concerns around ROI ever materialising were holding back their company’s AI transformation.

The researchers noted, “This reflects both the complexity and scale of enterprise-wide transformation. Agentic architecture demands more than aspiration – it requires structured execution. Each phase builds on the last: from secure foundations, to reimagined workflows, to value-creating marketplaces. Enterprises that advance systematically will compound competitive advantage, while those that hesitate risk stalling in pilot mode as competitors scale ahead.”