How to strengthen customer service and improve production quality

With the help of AI, service organisations can find information faster, provide better information, and enable service consultants to provide better solutions. 

In many service organisations, particularly in manufacturing, it can be a challenge to deliver fast, accurate and consistent customer support. Products are technically complex, cases vary in detail and urgency, and both language and organisational silos often get in the way of scaling support effectively. 

If you’ve ever worked in a customer service role in manufacturing, you’ll know the drill: a technical support case lands in your inbox, the customer expects a quick answer, and before you can even begin, you’re chasing down engineering documents, digging through old cases, or trying to guess which colleague might know the answer. All while switching between systems, and sometimes, languages. 

The challenge isn’t that your team lacks dedication. It’s about time, context and clarity. And when every case is different, scaling becomes a constant uphill battle. 

AI designed for real-world service complexity 

This is where generative AI can make a meaningful difference. By tapping into your existing documentation, historical cases, product data, and preferred communication style, AI can help structure, summarise, and accelerate the work that goes into every customer interaction. 

The result? Service teams can move faster, with more confidence, and provide more consistent responses, even when dealing with complex technical enquiries. 

Explore how sales teams can also benefit from AI-driven insights in this article.

Smarter first-line support 

A typical pain point in service teams is the time it takes to categorise and triage incoming requests. Misrouted enquiries, delayed responses, and unnecessary handovers are all too common. 

With AI-driven tools, support teams can automatically classify incoming emails and messages, identify whether it’s a service incident, a routine request, or a general question, and route them to the right team, without human involvement. In many cases, suggested responses can even be drafted automatically, aligned with your preferred tone of voice and company policies. 

This cuts down on errors, shortens response times and ensures customers are met with clarity from the start. 

Supporting people, not replacing them 

AI doesn’t replace the human touch. It strengthens it. 

By bringing relevant case data and documentation to the surface in real time, AI helps both junior and experienced staff respond with confidence. And as employees interact with AI-powered suggestions and explanations, they also learn, turning everyday service into a continuous training ground. 

For businesses, this means faster onboarding, better knowledge-sharing and fewer escalations. 

Scaling support without losing quality 

One of the recurring challenges in manufacturing customer service is knowledge fragmentation. Processes live in one system, historical cases in another, and key people are often the only ones who really “know how things work.” 

Low-code AI solutions, such as Microsoft Copilot Studio, allow teams to build internal-facing AI agents that help bridge these gaps. Without needing to code, companies can create assistants that help employees quickly find documentation, flag outdated material, or understand who handles what. Think of it as a shared memory across your support organisation. 

This doesn’t replace the role of experienced service staff. It makes their insight available to everyone. It ensures consistency, reduces internal dependencies, and gives new team members a clearer starting point. 

Speed and scalability in technical environments 

In manufacturing, customer enquiries often depend on deep technical understanding, and that usually means involving engineering teams. But the time and resources spent answering support tickets can come at the expense of product development. 

With the help of AI, support staff can access relevant technical documentation and case insights faster, enabling them to handle more issues independently. And when escalation is necessary, AI can summarise case histories and highlight key points, allowing colleagues to step in with minimal ramp-up time. 

Similar AI-driven approaches are also helping field service teams respond faster and more consistently in complex environments. Read more about AI in field service here.

Bridging language gaps across borders 

Global operations often face a less visible but equally impactful challenge: language. When documentation, support teams, and customers operate in different languages, even simple issues can become complex. 

Generative AI can help translate, summarise, and generate responses in multiple languages, making cross-border collaboration smoother and ensuring consistent support, regardless of location. 

From support function to strategic enabler 

AI enables customer service to shift from reactive support to a function that adds strategic value. With faster response times, improved accuracy, and better customer experiences, service teams are better positioned to support retention, identify after-sales opportunities and free up expert resources for more valuable work. 

Start where it matters most 

While the potential of AI in service is broad, getting started doesn’t have to mean a complete overhaul. The key is to focus on the challenges that slow you down today, and match those with the AI capabilities that can create the biggest impact. 

At Columbus, we work with manufacturers to do exactly that. Translating real-life service complexity into actionable, scalable solutions that actually work in practice.