NewsProductivity AI7 May 2026 · 5 min read

Allianz: AI Will Reorganize Work Faster Than It Eliminates Jobs

Allianz says AI will reorganize work at a faster rate than it will eliminate jobs – here's why productivity leaders should care.

Alex Cole

Allianz AI reorganizing work faster than eliminating jobs

AI and automation are often framed as a simple jobs story: replacement, redundancy, disruption. But Allianz’s latest labour-market report points to something more useful for productivity and automation leaders. The bigger shift is not mass job loss. It is the reorganisation of work itself. Tasks are being redistributed. Roles are being reshaped. Workflows are being rebuilt faster than many organisations are ready for.

That matters for UC Today readers because it changes the management question. The challenge is not only which jobs disappear. It is how support, approvals, communications, knowledge access, and team coordination need to evolve when routine cognitive work starts moving around the organisation.

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AI Is Reshaping Tasks Faster Than It Is Eliminating Jobs

Allianz says AI is likely to affect 23.3% of jobs across major economies over the next one to three years. But the mix is what stands out. Reorganisation accounts for 10.4% of jobs, ahead of augmentation at 5.3% and outright displacement at 7.6%. Exposure also varies sharply by country, from 9.2% in Italy to 28.7% in the US, with the UK at 17.7%, Germany at 16.2%, France at 14.7%, and Spain at 12.4%.

Katharina Utermöhl, Head of Thematic & Policy Research at Allianz, summarised the shift clearly in the LinkedIn discussion around the report:

“The key change is inside jobs: AI will eliminate some roles — but the bigger shift is that tasks are being reorganized, roles redefined, and workflows rebuilt.”

That is a better frame for enterprise buyers. AI may not hit the labour market first through dramatic layoffs. It may show up through task redesign, hiring restraint, and weaker entry points into white-collar work.

Younger Workers Look More Exposed Than Senior Staff

Allianz says early evidence already shows pressure on younger and less experienced white-collar workers in routine cognitive tasks. By contrast, gains are flowing more toward higher-skilled, AI-complementary roles. The report adds that higher AI adoption since late 2022 has been linked to larger increases in youth unemployment, with AI exposure explaining about 40% of cross-country variation once high-unemployment economies are excluded.

The LinkedIn discussion around the report points to the same conclusion. The risk is not just unemployment. It is whether younger workers are being given the skills and entry-level pathways needed to adapt. Mario Oreste of Allianz Trade Italy highlighted pressure on younger and less experienced white-collar workers, while Antony Martini of the Luxembourg House of Financial Technology argued that Europe’s real problem is not just employment. It is a “future-ready skills gap.”

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Why This Matters for Productivity and Automation Leaders

If AI reorganises tasks faster than it removes them, then leaders need to focus less on headcount headlines and more on workflow design. That is where many automation strategies still fall short. They add tools, copilots, and assistants, but do not redesign how work actually moves between people, systems, and decisions.

The risk is easy to miss. A business may automate part of a workflow, but still leave employees managing exceptions, checking outputs, and stitching together context across too many tools. In that scenario, AI does not reduce workload cleanly. It redistributes it.

Policy May Shape the Outcome More Than the Technology

Allianz’s conclusion is blunt. What happens next depends less on the technology itself and more on policy choices, labour-market support, and how firms decide to deploy AI. The report calls for stronger re- and upskilling, active labour-market programmes, social protection, and incentives that push firms toward augmentation rather than pure replacement.

“The priority is clear: incentivize augmentation over automation and accelerate labor reallocation through skills, mobility and transition support.”

That is the practical takeaway for enterprise leaders too. For employers, it means treating reskilling, internal mobility, and workflow redesign as part of the automation business case, not as HR activity that happens later. AI will not deliver sustainable ROI if it only strips out tasks. It needs better workflow design, stronger internal mobility, and visible investment in the people expected to work alongside it.

The Bigger Question for Enterprise Leaders

So yes, AI may reshape the job market. But for productivity and automation leaders, the more urgent question is narrower and tougher. The real test of AI adoption will not be whether organisations automate more tasks. It will be whether they redesign work well enough to avoid becoming more fragile in the process.

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FAQs

What does the Allianz report say about AI and jobs?

Allianz says AI will affect 23.3% of jobs across major economies over the next one to three years. The bigger shift is not outright job loss. It is the reorganisation of tasks, roles, and workflows.

Will AI eliminate more jobs than it augments?

Not according to Allianz’s near-term view. The report says task reorganisation accounts for a larger share of impact than either augmentation or outright displacement, which means businesses should focus closely on workflow redesign.

Which workers look most exposed to AI disruption?

The report says younger and less experienced white-collar workers in routine cognitive roles appear most exposed, while higher-skilled workers in AI-complementary roles are more likely to benefit.

Why does this matter for productivity and automation leaders?

Because AI is likely to move work around before it removes it completely. That means leaders need to redesign workflows, decision points, support models, and knowledge access rather than simply adding more AI tools.

What should companies do if AI is reorganising work?

They should invest in skills, internal mobility, better workflow design, and clearer operating models. The key question is not only which tasks AI can do, but how teams, systems, and processes should change around that reality.