Posted by Paris, France: As many as 59% of financial institutions are adopting multi-agent AI but only 10% have gained full orchestration, reveals a new research.
According to the Capgemini Research Institute’s World Cloud Report for Financial Services 2027, 59% of financial firms are piloting or deploying multi-agent AI in production across workflows. However, only one in 10 have achieved the full orchestration required to run them autonomously across the enterprise.
For banks and insurers to scale successfully in the agentic AI era, modernising their underlying tech stack is a prerequisite. Eight in 10 executives prioritising the reduction of tech debt as a key objective.
Business outcomes priority over agentic AI efficiencies
As finance organisations move past individual AI agents to multi-agent systems, the pressure to prove value is intensifying. By 2028, the number of executives prioritising outcomes as their primary AI-funding criterion is projected to increase 141%. But 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.
Nearly half of financial services firms cannot consistently show a return on their agentic AI initiatives and lack clear frameworks for assessing whether those initiatives deliver sufficient value to justify continued investment, as per the research.
To address these challenges, financial institutions are implementing disciplined cost and performance controls to continue their innovation drives. Most organisations are deploying or expect to adopt intelligent model routing within a year that direct tasks to the most cost-effective and accurate models.
Cloud – key execution layer for multi-agent AI systems
Financial firms increasingly recognise cloud as the common execution layer for governing 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. The partner will govern multi-agent deployments driven as per 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 – 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,” added Khokhar.
Hybrid sourcing to become the dominant approach
Firms are converging on a hybrid sourcing model for agentic AI capabilities. The model that balances building capabilities in-house, buying packaged agentic solutions to push 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.
Operationalising agentic AI to deliver against the bottom-line
The report identifies a small group of financial services firms, consisting just 5% of those surveyed, that have already institutionalised the capabilities required to operate agentic AI at enterprise scale.
Their edge over the rest of the industry shows up consistently across three priorities. First, orchestrating agents across business and technology functions. Second, establishing a trusted cloud foundation for autonomous execution, and third, ensuring AI investments deliver measurable business outcomes.