T-Bank entered the top 3 operators: how an AI agent handled 60% of requests and freed up dozens of hands

The implementation of an AI agent at T-Bank resulted in 60% of customer inquiries now being processed fully automatically. Most notably, according to internal rankings, this agent entered the top three most effective operators, performing on par with the best human employees. This is not just resource savings, but a fundamentally new approach to scaling customer service.

In a large bank, where the flow of inquiries amounts to tens of thousands per day, manual processing becomes a bottleneck. Limited throughput, human error, high recruitment and training costs – all these factors hinder development and prevent prompt response to market changes. However, today this burden can be alleviated by transferring routine operations to an AI agent.

The Problem: Why Manual Processing Became Inefficient

Before the implementation of the AI agent, all incoming inquiries at T-Bank were handled manually. Every request, whether it was a data change, product information, or a technical issue, required human intervention. This created a significant burden on the staff of operators, limiting their ability to handle a large volume of requests and scale the service. There were other challenges:

• Low processing speed. Even the fastest operators could not keep up with the ever-growing flow of inquiries, leading to increased waiting times for customers.
• Human factor. Errors, fatigue, emotional burnout of employees – all negatively affected the quality of service.
• High operating costs. Hiring, training, and maintaining a large staff of operators required significant financial investment.
• Limited scalability. Increasing the number of operators did not always solve the problem, as the volume of inquiries and administrative burden also grew.

The bank needed a tool that could process typical requests quickly, accurately, and without human involvement, leaving complex and non-standard tasks to employees.

The Path to AI Agent: Why Chatbots Were Not Enough

Many companies try to solve the problem of mass inquiries using ordinary chatbots. However, T-Bank understood that standard chatbots, operating on a question-and-answer principle, would not cope with complex tasks. A chatbot can provide information, but it cannot independently perform an action within the system, for example, change customer data or send a document. It does not analyze its actions and cannot adjust its strategy on the fly.

The bank required a system that could not only answer questions but also perform full-fledged operations, interacting with internal interfaces just like a human. This is why the choice fell on an AI agent, capable of autonomous planning, using external tools (Tool Use, in this case, Computer Use), context retention, and self-correction.

How the AI Agent with Computer Use Capability Was Designed

A key feature of the designed AI agent was the Computer Use function. This means that the agent does not just call APIs or work with databases, but actually "sees" the screen, moves the cursor, clicks buttons, and fills out forms in existing banking systems, just as a human would. This approach allowed for:

• Integration without extensive system re-engineering. The agent did not require new APIs for each operation; it used existing interfaces.
• Automation of complex multi-step processes. The agent could sequentially perform operations in different windows and programs.
• Maintaining flexibility. If an interface changed or new functions appeared, the agent could be quickly adapted.

The agent's main task was the autonomous execution of 60% of typical inquiries that previously required manual processing. This included requests for personal data changes, statement provision, and answers to standard questions about products and services. The agent was designed to independently build a logical sequence of actions, analyze the result, and, if necessary, adjust its approach.

Implementation and Performance Evaluation

The implementation of the AI agent was phased. Initially, the agent was trained on the most frequent and predictable inquiry scenarios. A crucial step was that its performance was evaluated using the same quality criteria as live operators: speed, accuracy, completeness of problem resolution, and customer satisfaction.

This approach allowed the bank to objectively compare the efficiency of AI with human labor. The results exceeded expectations: the AI agent not only handled 60% of inquiries but also achieved a level of quality comparable to the best employees. It worked consistently without breaks or errors, allowing operators to focus on more complex and non-standard cases requiring empathy and creative thinking.

Results: AI Agent in the Top 3 Operators

The main result is that the AI agent not only automated processes but became a full-fledged, highly effective team member. It entered the top three operators in terms of quality and speed of request processing. This allowed the bank to not only significantly reduce operating costs but also dramatically increase the overall productivity of customer service, freeing up dozens of human hands for more strategic tasks.

How to Implement This in Your Business

The T-Bank example shows that AI agents can become not just automation tools, but also full-fledged "employees." If your company has mass, repetitive operations that require interaction with various IT systems, then an AI agent with Computer Use functionality can deliver real results:

• Identify routine operations. Pinpoint tasks that employees perform daily, switching between multiple programs and interfaces.
• Assess integration complexity. If APIs are unavailable or too expensive to develop, the Computer Use function will allow the agent to work with existing interfaces without re-engineering them.
• Define success metrics. As in T-Bank, evaluate the agent's work using the same criteria as human work to objectively measure the results.
• Start with a pilot. Choose one significant process for pilot implementation to quickly achieve initial results and demonstrate the value of the solution.

If this case sounds like what's happening in your company, our manager can help: he'll analyze your business and niche for free and point out where an AI agent would bring a real result in your case. Message the manager