What is a co-pilot?.

Examples of such Generative AI tools

Most of us already use some form of co-pilots in our everyday life. Some examples include:

• Microsoft Copilot in Word, Outlook, or Excel, which helps draft documents, summarise emails, and analyse spreadsheets. 

• ChatGPT, which generates text, answers questions, explains concepts, and even supports creative tasks. 

• GitHub Copilot, which assists developers by suggesting and debugging code in real time. 
• Meeting assistants built into tools like Teams or Zoom, which automatically generate action points and summaries after a call. 

• Everyday AI assistants on your phone or browser, which recommend restaurants, draft social posts, or tidy up text. 

In each of these examples, the AI doesn’t replace the person, it supports them. It handles the repetitive, time-consuming parts, leaving people with more time to focus on creative thinking, decision-making, and meaningful interactions. 

AI copilots in customer service and contact centres

So, in the world of customer service, what role does these AI-powered assistants have?  

In a contact centre, an AI co-pilot is tailored to the needs of customer service teams. Instead of generating code or writing marketing copy, it focuses on assisting agents during live customer interactions. 

That means an AI co-pilot for customer service can: 

• Listen to or read conversations in real time and understand intent, tone, and context 

• Surface answers from approved knowledge sources, such as policies or FAQs 

• Suggest next-best actions (e.g. offer a refund, confirm account details, escalate to a specialist) 

• Draft responses for agents to review—across email, chat, or messaging channels 

• Summarise calls automatically, turning long conversations into concise notes for wrap-up and follow-up 

Think of it as giving every agent their own smart assistant. Instead of switching between systems, searching multiple tabs, and typing up notes after every call, agents can rely on the co-pilot to do the heavy lifting, while they stay focused on the customer. 

Other terms you might hear include Agent Assist, AI assistant for agents, or even contact centre co-pilot. They all point to the same idea: AI supporting agents in real time. 

How AI co-pilots work

So, how does it work and what technologies does it use?  

An AI co-pilot is powered by a mix of artificial intelligence technologies that work together to understand human input, retrieve relevant information, and provide real-time assistance. While the exact setup depends on the use case (software development, productivity tools, customer service, etc.), most copilots rely on: 

• Natural Language Processing (NLP) and Natural Language Understanding (NLU): To interpret what the user is asking, detect intent, and understand the context of a request. 

• Machine Learning (ML): To improve accuracy over time, learning from previous interactions and becoming more useful with continued use. 

• Retrieval-Augmented Generation (RAG): To ensure the AI grounds its answers in trusted sources (such as documents, databases, or knowledge bases), rather than generating responses from scratch.
• Generative AI (Large Language Models – LLMs): To draft content, suggest actions, or summarise information in a natural, human-like way. 

• Integrations with business systems: To pull data from the right place and take action within existing workflows. 

In simple terms, a co-pilot listens, understands, finds the right information, and presents it back in a way that’s useful—while always keeping the human in control. 

👉 Relevant read: AI glossary for customer experience 

What’s the difference between co-pilots and chatbots?

It’s easy to confuse AI copilots with other automation tools like chatbots, scripts, or IVR menus. On the surface, they all aim to make work faster and reduce repetitive tasks. But the difference lies in flexibility, intelligence, and purpose. 

• Chatbots are typically designed for customers. They sit on websites, apps, or messaging channels and answer questions directly. Some are rule-based (following scripts), while more advanced ones use conversational AI to understand intent and provide dynamic responses. Their goal is usually to deflect queries or offer self-service. 

• AI copilots, on the other hand, are built for agents and employees. They don’t replace the human in the conversation, they sit alongside them, providing real-time support, surfacing answers, drafting replies, and creating summaries. In short, copilots empower humans to do their work faster and more accurately, rather than interacting with customers directly. 

This distinction matters in a contact centre: chatbots help manage incoming demand, while copilots support the customer service agents handling the more complex, high-value conversations. 

👉 Relevant read: What is a chatbot? 

But why now? Three big shifts

The rise of AI co-pilots is being driven by three big shifts: 

1. Customer expectations are rising. Customers want faster, more personalised support, but they don’t want to repeat themselves or be kept waiting. Co-pilots help agents access the right answer instantly.
2. Agent workloads are heavier. With increasing call volumes and multi-channel queries, agents are under pressure to do more in less time. Co-pilots reduce the cognitive load by automating note-taking, knowledge searching, and admin.
3. Complexity is growing. Many queries today can’t be answered with a script. Co-pilots use AI and natural language understanding to interpret the context of a conversation and suggest relevant, compliant responses. 

For contact centres, this translates into shorter calls, faster wrap-up, higher FCR, and better agent well-being, all while keeping the human touch at the heart of customer conversations. 

Implementation tips for CX leaders

Getting started with an AI co-pilot doesn’t have to be overwhelming. A step-by-step approach helps: 

• Start small. Pilot in one queue (e.g. billing queries) before rolling out across the contact centre. 
• Clean your knowledge base. The quality of answers depends on the accuracy of your content. 
• Integrate with existing systems. Place the co-pilot inside your agent desktop for easy adoption. 
• Keep humans in control. Ensure all AI-drafted responses are reviewable before sending. 
• Track KPIs. Measure AHT, ACW, FCR, CSAT, and agent satisfaction to prove ROI.

The future of AI copilots in customer service

We’re only at the beginning of what AI copilots can do for customer service and contact centres. As technologies like generative AI and natural language processing continue to mature, copilots will move from being helpful assistants to becoming essential teammates for agents. 

Here are some trends shaping the future of AI copilots in customer service: 

• Deeper integration with business systems: Today’s copilots already connect to knowledge bases and CRMs. In the future, they’ll plug into even more systems, from workforce management to billing, creating a single, intelligent layer of automation across the entire contact centre. 

• Proactive copilots: Instead of waiting for agents to act, copilots will begin suggesting the next step before it’s even needed. For example, they could alert agents to a frustrated customer’s tone and proactively surface escalation options. 

• Hyper-personalisation: With richer data, copilots will help tailor every interaction. Imagine a copilot that not only drafts a response, but adjusts the tone based on customer history and preferences, delivering a smoother customer experience. 

• Voice and multimodal copilots: As speech recognition and sentiment analysis improve, copilots will support agents not just in chat or email but also in voice calls, video interactions, and even across social channels. 

• Greater governance and compliance: As regulations around AI evolve, copilots will need built-in safeguards. Expect future copilots to come with stronger transparency, explainability, and audit features, helping CX leaders maintain compliance without slowing down service. 

• Agent empowerment: Far from replacing jobs, copilots will become a standard part of the agent toolkit, reducing burnout and enabling new hires to get up to speed faster. The future will be less about “AI vs humans” and more about “AI and humans together.” 

Industry analysts predict rapid adoption. Deloitte forecasts that by 2027, 50% of enterprises using generative AI will deploy agent-assist tools like copilots. McKinsey already highlights measurable results: reduced handling times, higher resolution rates, and lower attrition when copilots are in place. 

Wrapping up: the role of AI copilots in modern customer service

AI copilots aren’t just another buzzword in tech but they’re becoming a practical, everyday tool for contact centres. By combining automation, natural language processing, and generative AI, these AI assistants give agents the real-time support they need to handle calls, chats, and messages more efficiently. 

The result? Less admin, fewer repetitive tasks, and more time for agents to focus on what truly matters, building trust and delivering better customer experiences. 

For CX leaders, adopting an AI copilot in customer service is a way to balance cost efficiency with quality service. It helps improve KPIs like AHT, ACW, and FCR while also reducing stress for agents and boosting satisfaction for customers. 

Think of it as moving towards a smarter, hybrid model: AI copilots handle the heavy lifting in the background, while human agents bring empathy, judgement, and personal connection to every interaction. Together, they create faster, more consistent, and more meaningful customer support. 

If you’re exploring where to start, begin small - test copilots in one queue, measure the results, and scale up. The contact centres that act now will be the ones best equipped to meet rising expectations tomorrow. 

👉 Curious about how this works in practice? Explore Puzzel’s Co-Pilot here and see how it can support your agents in delivering better service every day.