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Study funds 75% of banks actively exploring Gen AI, 36% already deploying
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April 10, 2025

Key Points
75% of banks are exploring generative AI, with 36% actively deploying it, according to a Temenos survey of over 400 senior banking execs.
Banks are using Gen AI to automate tasks, aiming to free up staff for more personalized client interactions.
The shift towards automation raises concerns about consumer trust and the potential loss of personal touch in banking services.
Generative AI is emerging as a cornerstone for banks seeking to boost operational efficiency, positioning the technology not only in back-office functions, but also increasingly in customer-facing services.
Three quarters are in: According to a new Temenos survey of over 400 senior banking executives worldwide, 75% of financial institutions are exploring GenAI, with 36% having already deployed or in the process of deploying it. Execs are largely focused on handling tasks that traditionally required significant manual intervention, and hopeful Gen AI can free up human staff for more focused client interactions.
Trust issues: But while a more automated transition would offer heightened productivity, it unsurprisingly raises questions about how internal roles might be redefined and, more importantly, how that factors into consumer trust. Any successful bank is built on relationships and credibility. While GenAI can streamline customer support and improve response times, many executives acknowledge the risk of losing the personal touch that has long differentiated financial institutions from more automated service providers.
Getting it right: The survey data underscores the tension: nearly half of institutions experimenting with GenAI expect to increase investment in the technology this year, yet the move also demands careful balancing of automation with one-on-one guidance. Temenos' research points to a split between banks that see early deployment as a means of speeding past competitors and those that remain cautious, letting others move first. Obviously key to adoption is success, and with a cautious rollout comes many opportunities to pressure test and evaluate the quality of AI. So the winners in the space will likely be defined by operational perfectionism, with little margin for error.