There’s no shortage of excitement around AI in customer service. From chatbots to intelligent ticket routing, new tools are transforming how organisations interact with their customers. But while the technology is advancing rapidly, its adoption often outpaces the strategy behind it.
According to the Zendesk AI report, AI is already delivering clear benefits, with agents saving an average of 7.3 hours per week and 91% of companies reporting better service quality.
However, too often, businesses implement AI in siloed ways, rolling out features without considering the broader customer experience or the impact on frontline teams – in fact, the use of generative AI tools by agents outside of those provided by their company has seen a dramatic increase, with 49% now using these tools, up from just 17% the previous year. It’s a familiar pattern; like the early days of cloud and CRM, tools can arrive before the framework is ready.
To make meaningful progress, organisations must align AI investment with actual business needs and customer behaviours. That means moving beyond isolated features and integrating AI into a broader customer experience strategy – one that balances technology, people and process.
Automating with purpose
AI-powered automation – through AI agents and copilot – is one of the clearest paths to delivering faster, scalable support. These tools can resolve common customer issues autonomously, summarise conversations, route tickets based on context and surface relevant content across channels in real time.
When implemented with care, automation reduces pressure on agents while improving the speed and consistency of service. But intent is key – successful businesses are designing these experiences around real customer needs: identifying high-volume, repeatable queries and embedding AI directly into existing workflows.
Supercharging knowledge with AI
AI is also redefining how companies manage and share knowledge – both with their customers and within their teams. At the heart of this is the AI-powered knowledge base: a dynamic hub that organises and surfaces data and information on demand.
Modern knowledge bases do more than store articles. They leverage AI to learn from interactions, assist in content creation, and deliver guidance in real time – whether to a customer browsing FAQs or an agent responding to a complex query.
This not only speeds up resolution times but also helps teams maintain consistent, high-quality service across all channels. For agents, it means faster onboarding, easier access to expertise, and fewer blockers in their day-to-day work. For businesses, it’s a scalable foundation for great service.
Empowering agents to lead the change
AI should be built around people – not just by automating routine tasks, but by empowering agents to focus on complex, high-value issues. This requires working closely with teams to identify what should be automated and providing training to supervise and shape AI.
As automation scales, the role of agents is shifting. Many are now guiding copilots, reviewing AI-generated content and ensuring that automation supports the customer experience.
Zendesk research shows that 79% of agents believe an AI copilot would enhance their ability to deliver great service. But for AI to succeed, it must be easy to use and embedded in existing workflows. When done right, AI reduces burnout, improves morale and allows humans to build trust and solve problems creatively.
Speaking the customer’s language
Language is one of AI’s most powerful enablers, and the right tools can understand sentiment, intent and tone across languages – offering native translation and adapting content to match a company’s voice. This allows brands to scale globally without sacrificing quality or consistency.
But with this power comes responsibility. As AI takes on a more visible role, customers expect transparency – about who or what they’re interacting with, how their data is used, and how they can escalate when needed.
65% of CX leaders see AI transparency as a strategic necessity, while 83% consider data protection and secure AI deployment top priorities for customer service. These figures show that trust isn’t optional: it’s both an expectation and a business imperative.
This is especially critical in regulated sectors like finance, healthcare and government, where transparency and ethical oversight are non-negotiable. Clear handovers, explainable AI, and built-in safeguards ensure that automation supports human accountability.
Realising AI’s full value
To truly unlock AI’s potential, businesses must shift from experimentation to intentional design. That means:
– Mapping customer journeys and pinpointing opportunities for automation
– Empowering agents to design and supervise AI workflows
– Connecting automation to live data and knowledge bases
– Monitoring performance and sentiment in real time
– Establishing strong governance and feedback loops
– Training teams to work confidently and effectively with AI
Those that take this structured approach are already seeing results. Trendsetters are already seeing results, with those prioritising AI-led personalisation now more than twice as likely to report strong ROI. And as autonomous AI becomes more embedded, 90% of CX leaders believe these systems will soon handle up to 80% of standard queries, allowing service teams to scale efficiently without losing the human touch.
A smarter path forward
AI has the potential to radically improve how customer service is delivered – but only when implemented with structure, purpose and care. It’s about using technology to enhance how humans solve problems, build trust and deliver value.
By bridging the AI gap with thoughtful planning, strong governance and a focus on real outcomes, organisations can move beyond early experimentation and unlock lasting impact for customers, agents and the business as a whole.