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Financial Institutions Accelerate Transition to Multi-Agent AI in Drive for Bottom-Line Value

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Financial Institutions Accelerate Transition to Multi-Agent AI in Drive for Bottom-Line Value

Financial institutions are moving beyond isolated agentic AI experiments to multi-agent AI across core banking and insurance workflows. The Capgemini Research Institute’s World Cloud Report for Financial Services 2027 reveals that while 59% of firms are piloting or deploying multi-agent AI in production, only one in ten have achieved the full orchestration required to run them autonomously across the enterprise. To scale successfully, banks and insurers recognize that modernizing their underlying tech stack is a prerequisite to succeed in the agentic AI era – with eight in ten executives prioritizing the reduction of tech debt as a key objective.

Banks and insurers look to prioritize business outcomes over agentic AI efficiencies
As finance organizations move past individual AI agents to multi-agent systems, the pressure to prove value is intensifying. By 2028, the number of executives prioritizing outcomes as their primary AI-funding criterion is projected to increase 141%, while the number focused on efficiency will drop 42% over the same period, according to the global survey of 1,100 C-suite executives of financial services firms.

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This change in approach comes as financial firms look to balance the capabilities of agentic AI with the cost of deployment. According to the research, roughly half of financial services firms cannot consistently demonstrate a return on their agentic AI initiatives and lack clear frameworks for assessing whether those initiatives deliver sufficient value to justify continued investment. To address these challenges, financial institutions are implementing disciplined cost and performance controls to continue their innovation drives.


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