Bottlenecks in Scaling AI Features: Risks and Operational Costs

Customer service at T-Bank is not just a service—it's a client-centric ecosystem where every interaction aims to resolve issues quickly, effectively, and with empathy. To accelerate service delivery and improve quality, we are transforming existing processes and actively integrating AI—from chatbots and LLM agents to intelligent routing.
We will discuss:

• What customer service means, its structure, and key stages in resolving client issues.

• What lies "under the hood" of customer conversations and the technical challenges involved.

• Flexible vs rigid LLM agents: when hallucinations cannot be tolerated.

• Whether AI tools can be scaled over technical debt, and the solution we implemented in a payment cancellation use case.

• The flip side: when AI stops enhancing service quality and leads to unnecessary costs—sometimes it's more cost-effective to fix the existing process and stick to algorithmic approaches.