Financial institutions accelerate transition to multi-agent AI in drive for bottom-line value

Paris, November 05: 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.  

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. Most organizations are deploying or expect to adopt intelligent model routing within a year that direct tasks to the most cost-effective and accurate models.

Cloud is a key execution layer for multi-agent systems

According to the report, financial institutions increasingly recognize cloud as the common execution layer that governs how agents access data, make decisions, and take action. Demand is consolidating around major providers with over half of banks and insurers identifying hyperscalers as their preferred partner to govern multi-agent deployments driven by requirements for regulatory and data residency certifications, security and identity frameworks, and auditability at scale. 

This need for cloud environments that can support autonomous operations while meeting regulatory requirements is increasing as AI agents are taking on greater decision-making responsibilities. Three quarters of respondents expect them to become a key part of customer engagement within three years, particularly in account servicing, loan origination and underwriting, and product recommendations. 

“In just 12 months, financial institutions have moved beyond experimenting with individual AI agents tackling isolated tasks to deploying multi-agent systems that coordinate actions across entire business lines. Yet adoption alone does not create value,” said Ravi Khokhar, Global Head of Cloud for Financial Services at Capgemini. “Successfully scaling these systems requires infrastructure that drives end-to-end orchestration, effective governance and security by design, and clear link into bottom-line impact. Cloud is now the operational foundation that makes all this possible. The few pulling ahead are not treating cloud as a commodity, but as the foundational pillar of their agentic AI strategy.”

Hybrid sourcing to become the dominant approach

To realize this vision, firms are converging on a hybrid sourcing model for agentic AI capabilities that balances building capabilities in-house for differentiation, buying packaged agentic solutions to accelerate deployment at scale, and working with partners for ecosystem depth. This is expected to become the dominant approach for more than two-thirds of financial institutions within three years. 

A small number of financial services firms are operationalizing agentic AI to deliver against the bottom-line

The report identifies a small group of financial institutions, representing just 5% of those surveyed, that have already institutionalized the capabilities required to operate agentic AI at enterprise scale. Their edge over the rest of the industry shows up consistently across three priorities: orchestrating agents across business and technology functions, establishing a trusted cloud foundation for autonomous execution, and ensuring AI investments deliver measurable business outcomes.