AI Automation Drives Revenue Gains for 44% of Financial Institutions, Creatio Research Finds

Financial institutions are outpacing the global average in AI adoption, with 80% of organizations moving beyond experimentation into enterprise-wide execution. Creatio’s latest research highlights a critical pivot toward "agentic" AI, where automated agents work alongside human teams to drive revenue and operational capacity rather than simply cutting costs through headcount reduction.

What was announced

Creatio has released the Financial Services Edition of its State of Enterprise AI Adoption Report, a study based on a survey of more than 190 IT and business decision-makers within the financial sector. The findings, which form part of a larger global study of 600 leaders, indicate that the industry is shifting from isolated AI deployments to scaling AI agents across entire departments. Currently, 81% of financial institutions are already scaling these agents or expect to do so within the next twelve months.

The report identifies a significant correlation between deep automation and financial performance. While only 13% of institutions automating less than 10% of their workflows report revenue gains, that figure jumps to 44% for organizations that have automated more than half of their processes. Beyond revenue, the immediate benefits of adoption include a 63% increase in productivity, 51% faster decision-making, and a 42% improvement in customer experience.

A distinct group of "AI Adoption Leaders"—comprising 19% of the surveyed institutions—is setting the pace for the sector. These leaders are more than five times as likely to have embedded AI enterprise-wide compared to their peers. The research also underscores the role of governance in successful scaling; 72% of organizations with established AI governance frameworks express high confidence in their ability to scale, compared to just 23% of those still developing such frameworks.

The companies involved

Creatio is a global vendor of a no-code platform to automate workflows and CRM with a heavy emphasis on AI-driven orchestration. The company’s core value proposition centers on an environment where human employees and AI agents work together within a single interface. By providing tools that allow business users to build and modify their own applications and processes without deep coding knowledge, Creatio has positioned itself as a key player in the digital transformation of highly regulated industries.

In the financial services market, the company has increasingly focused on specialized solutions that address the specific compliance and operational needs of banks and credit unions. Its platform is designed to handle complex lifecycle management, from initial customer onboarding to long-term relationship management and service operations. This industry-specific focus is a cornerstone of its market strategy, aiming to bridge the gap between generic AI tools and the specialized requirements of the banking sector.

What FF News has reported before

FF News has closely followed Creatio’s aggressive expansion into the banking sector. In September 2026, the company made a significant move by announcing that Creatio Commits $300 Million to Its Bank.AI Platform Through 2028 to Drive AI Adoption in Banking. This investment followed the launch of a dedicated resource for the sector, as Creatio Launches Bank.AI Hub to Accelerate AI-Powered Banking Transformation. These strategic investments are already seeing real-world application; earlier in 2026, we reported that Arizona Financial Credit Union Deploys Creatio Agentic AI to Transform Member Engagement, marking a practical milestone in the shift toward agent-led member services.

What this means

The data suggests the "efficiency" narrative of AI—focused primarily on cost-cutting—is being replaced by a growth-oriented strategy. The fact that revenue gains are nearly four times higher for heavy automators proves that AI is no longer just a back-office tool for trimming margins. However, the widening gap between "AI Adoption Leaders" and the rest of the market creates a significant competitive risk. Legacy institutions that fail to move beyond the experimentation phase face a double threat: they lack the operational speed of automated peers and the governance frameworks necessary to scale safely. The real bottleneck for the industry is no longer the technology itself, but the maturity of internal governance.