In 2025, the tech industry had a year marked by disruption induced by artificial intelligence (AI) and layoffs. After the COVID-10 pandemic, layoffs have hit the tech industry the most, but if the predictions are true, the next industry to see job cuts could be banking.
Now, Morgan Stanley has issued an AI job warning for the banking sector and has forecast that over 200,000 European banking jobs could be lost in the next five years due to accelerated AI adoption and branch closures, reports Financial Times. The report states that more than 200,000 European banking jobs are under threat over the next five years as lenders increasingly embrace artificial intelligence and close more branches, analysts have estimated. Morgan Stanley has forecasted that European banks could cut 10 percent of the jobs by 2030. The report further highlights that these job cuts will be driven by efficiency gains from digitalisation and AI. The analysis done covers around 35 European lenders which employ around 2.12 million staff.
AI to cut banking jobs, warns Morgan StanleyMorgan Stanley reports that as many as 2,00,000 European banking jobs could disappear in the next five years. The job cuts in the banking sector are most likely to come from within banks’ “central services” divisions, which include back- and middle-office roles, as well as risk management and compliance positions. These roles are reportedly seen as repetitive or data-intensive, and are said to be the prime candidates for automation using machine learning and AI tools. Some of these tasks include monitoring transactions, preparing reports and processing large datasets. Algorithms can execute these functions faster than traditional manual processes, a factor driving banks’ interest in technology-led restructuring.
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“Many banks have quoted efficiency gains coming from AI and further digitalisation to the tune of 30 per cent,” Morgan Stanley noted. Europe’s lenders have come under intense pressure from investors to find new ways to cut costs and boost returns on equity that persistently lag behind their US rivals.
Banks have already started to cite AI as a catalyst for restructuring their operations. In November, Dutch lender ABN Amro announced plans to cut around one-fifth of its full-time workforce by 2028, while Société Générale chief executive Slawomir Krupa warned in March that “nothing is sacred” in his drive to rein in the French bank’s persistently high cost base.
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According to analysts at Morgan Stanley, artificial intelligence offers banks a fresh opportunity to improve cost-to-income ratios — a key efficiency metric closely watched by investors — as traditional cost-cutting measures have largely run out of momentum. The forecast highlights how accelerating digitalisation and wider adoption of AI could significantly reshape Europe’s banking sector in the coming years, particularly among consumer-focused lenders and in countries such as France and Germany, where cost-to-income ratios remain elevated.
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AI could transform European bankingUBS analysts echoed the view that AI could transform European banking. The Swiss bank has already begun using the technology to create analyst avatars, sending videos of simulated bankers to clients. Jason Napier, head of European banks research at UBS, said efficiency gains are already visible in sectors such as audit, law and consulting, but banks have yet to fully realise similar benefits.“Cost bases remain large, and these powerful new tools are still not fully implemented,” Napier said, adding that sceptics should spend more time exploring AI tools that are already available. As part of its push, UBS recently sent its 250 most senior leaders to Oxford University for an AI-focused leadership summit, according to people familiar with the matter.
However, even as banks face growing pressure to extract savings from AI, some senior executives have urged caution. Conor Hillery, JPMorgan Chase’s co-chief executive for Europe, the Middle East and Africa, warned against losing sight of core banking fundamentals amid the rush to adopt AI.
He said JPMorgan was seeking a balance between using AI to speed up routine tasks and ensuring junior staff continue to develop essential skills such as building cash-flow models and analysing price-to-earnings ratios.
“Otherwise, we’re storing up a big problem for the future,” Hillery said.