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Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in around 6 minutes. I'm Nathaniel Whittemore, and this is Wednesday, September 25th, 2024. Today we're starting off today with a case study from Citigroup via the Wall Street Journal, and it is clear that for Citigroup, the agentic AI revolution is not some distant possibility.
They are not doing it halfway. According to the article, Citi is currently using over 1,500 AI agents across different areas of the business, with plans to scale to over 5,000 by the end of the year. These agents are able to access multiple systems within the company, with CTO David Griffith saying, "A couple of years ago, you could do agentic workflows with one or two systems. Now you can have agents that can access five or six systems and do relatively complex orchestrations across them."
The scale is impressive - agents are being used for customer service, fraud detection, trade settlement, and even regulatory compliance. Some agents can process thousands of transactions per hour, significantly reducing processing times from days to hours in some cases.
What's particularly noteworthy is how Citi is approaching the ROI calculation. Rather than just looking at cost savings, they're measuring the value creation from agents being able to work 24/7, handle peak loads without staffing concerns, and maintain consistent accuracy levels that are often higher than human performance.
The implementation hasn't been without challenges. The article mentions significant investment in data infrastructure, security protocols, and employee training. There's also been a cultural shift required, with some teams initially resistant to working alongside AI agents.
Looking ahead, Citi expects these agents to become even more sophisticated, potentially handling entire end-to-end processes that currently require human oversight. This represents a fundamental shift in how large financial institutions operate, with agents becoming core infrastructure rather than experimental tools.
The financial implications are substantial. While Citi hasn't disclosed specific cost savings, industry analysts estimate that large banks could reduce operational costs by 20-30% through aggressive agent deployment. However, this comes with significant upfront investment in technology and change management.
This case study from Citigroup provides a concrete example of how large enterprises are moving beyond pilot programs to full-scale agent deployment. It's a glimpse into a future where AI agents aren't just helpful tools, but essential components of business operations.