Reducing Service Load with AI-Powered First-Line Support

The customer service team was overloaded with repetitive and poorly structured requests, making it difficult to meet SLAs and efficiently route cases, so ARP Ideas designed an AI-driven first-line service dispatcher that automatically gathers context, resolves simple issues, and creates complete, well-routed cases for consultants when human intervention is required.

Before the project, customer service teams were struggling with a growing volume of incoming requests related to after-sales support, complaints, and helpdesk questions, many of which were repetitive and lacked essential information such as product models, serial numbers, or clear problem descriptions. Customers often contacted support in an unstructured way, forcing consultants to spend valuable time asking basic follow-up questions before they could even begin troubleshooting, which negatively impacted service levels and customer satisfaction.

To address this, ARP Ideas designed an AI-based first-line service dispatcher operating as a live chat, initially intended for rollout in selected markets as a controlled pilot. The AI agent behaves like an experienced service consultant, asking structured questions about the product model, order number, symptoms, and requesting photos of damage where relevant. This approach ensures that essential data is captured at the very first interaction, rather than through multiple back-and-forth messages.

When the issue is simple and well-defined, such as a known configuration problem or a common user question, the AI agent can immediately provide instructions, manuals, or PDF documentation and close the interaction without creating a ticket. This removes a significant portion of low-complexity requests from the service queue altogether. In more complex scenarios requiring human involvement, the agent automatically creates a complete case in the CRM system, including a structured description, attachments, and categorisation.

The case is then routed directly to the appropriate queue, such as quality complaints, technical failures, or logistics inquiries, using predefined case categories and routing logic. Consultants no longer start interactions by gathering basic information, but instead take over cases that already contain full context, allowing them to focus immediately on resolution.

The solution is designed to run on platforms such as Dynamics 365 Customer Service and Copilot for Service, supported by Azure OpenAI and integrated with service queues and routing mechanisms. While the draft references features beyond the standard Copilot Service agent capabilities, the architecture is ready for a pilot deployment limited to one country or one product line, allowing the organisation to validate operational impact before broader rollout.