AI has gone from being buzzword of the year to becoming a core part of modern contact centre operations. Today, AI and automation solutions like virtual agents, conversational analytics, and intelligent routing help businesses optimise processes, improve customer experiences, reduce operational costs, and better support human agents.
But that doesn’t mean everyone’s using it the same way. Some teams are just starting out. Others are further along. We think both are totally fine.
What matters most is knowing where you stand, so you can make informed decisions, spot opportunities, and get more value from your AI investments.
That’s why we created the AI Maturity Curve: a practical framework outlining the five key stages of AI adoption specifically for contact centres.
Let’s take a closer look at the five stages and how to move forward from each one.
The AI maturity curve provides a clear framework to help you identify your current AI capabilities, highlight opportunities, and outline practical next steps.
Organisations in this stage are at the very beginning of their AI journey. AI adoption is minimal or ad hoc, and there may not yet be a defined strategy or process in place. While there may be interest in AI, automation is limited, and customer interactions tend to remain reactive and manual.
Key characteristics:
Next step: Start identifying practical AI use cases and invest in foundational team training.
At this stage, organisations have begun experimenting with basic AI solutions, such as rule-based chatbots or automated routing, but they often face challenges around scalability and integration. Teams may face challenges scaling these tools due to siloed data and limited internal expertise.
Key characteristics:
Next step: Improve data integration and develop a structured approach to expand AI across more workflows.
Organisations in this stage are likely seeing AI deliver real value. It’s being used in day-to-day operations, automating repetitive tasks, improving decisions, and supporting agents with timely insights. At this level, AI adoption is more consistent, although there may still be areas to optimise.
Key characteristics:
Next step: Expand AI’s role in predictive analytics and real-time agent support.
At this stage, AI is fully integrated into business strategy and customer experience operations. AI-powered automation is widely used across self-service and agent-assisted interactions, reducing friction and improving efficiency. AI insights help drive continuous CX improvements, and data is well-managed, providing a solid foundation for further AI expansion.
Key characteristics:
Next step: Strengthen AI-human collaboration, refine predictive analytics, and explore innovative AI-driven strategies.
AI visionaries are likely using AI across nearly every aspect of their customer service. AI works alongside agents to deliver highly personalised, efficient service, and helps predict and resolve issues before they escalate. These organisations continue to experiment and evolve, using AI to stay ahead of rising customer expectations.
Key characteristics:
Next step: Keep refining your AI strategy, experimenting with new use cases, and sharing learnings to lead the way in AI-powered customer service.
For customer service teams, AI maturity directly impacts efficiency, agent productivity, and overall customer satisfaction. Here are key stats highlighting the importance of investing in your AI strategy:
Clearly, the opportunities are significant. Understanding your current AI maturity stage enables you to focus your efforts strategically, saving valuable resources while maximising returns.
Understanding your current stage is the first step to unlocking AI’s full potential in your contact centre. Take our quick AI maturity assessment and receive tailored insights, recommendations, and practical resources to help you progress confidently.