AI for customer support: how artificial intelligence (AI) answers routine enquiries and frees your team for the hard ones

Agent assist, triage, knowledge retrieval and summarisation can all be built now and typically deliver value within weeks. Fully autonomous resolution works well only for well-documented, low-stakes, high-volume questions and needs careful scoping and ongoing quality monitoring. Vendor deflection figures come from other markets and often from those selling the tools, so pilot against your own ticket history.

• Agent assist carries the most solid evidence in this whole area: a peer-reviewed NBER field study of 5,179 support agents found a 14 per cent average productivity gain, around 34 per cent for newer agents, together with better customer sentiment and lower staff turnover. Triage, knowledge retrieval and after-contact summarisation are mature, low-risk builds because a human still owns the decision or the case is already resolved.[1][2]
• Fully autonomous resolution is real and operating at serious scale, as the Klarna and Intercom deployments show, but it is also the highest-variance use, and the distinction that matters is between deflection, the AI handled the contact, and resolution, the customer's problem was actually solved.[1][2]
• Read the headline figures as a compass, not a contract. Klarna's own chief executive later said the company had gone too far, that chasing cost had let quality slip, and began rehiring people for complex, premium service. Pilot against your own ticket history and judge on genuine resolution before you scale anything.[1]

You are responsible for what your AI tells customers. Keep a person in the loop wherever money or an upset customer is involved, ground every answer in your own approved content, and treat personal and payment data under UK GDPR and the ICO's expectations, reviewing your supplier's security and hosting before launch.

• There is no general UK AI statute; government policy leaves existing regulators to apply existing law to AI within their own remits. So there is no blanket legal duty to announce a chatbot, but honesty about AI is established good practice, and being unclear that a customer is talking to a machine can itself mislead. ASA and CAP guidance is explicit that disclosing AI use cannot cure a claim that is misleading in substance.[1][2]
• You answer for what your AI tells customers. In Moffatt v Air Canada a tribunal held the airline liable after its chatbot invented a refund policy, rejecting the argument that the bot was a separate entity; the sum was small, the liability principle is what travels. In the UK the equivalent exposure runs through consumer law, where the CMA can itself fine misleading commercial practices, so a chatbot quoting prices or policies that do not exist sits squarely in that territory.[1][2]
• Personal and payment data flows through every one of these systems, so the UK GDPR and the Data Protection Act 2018 apply in full, enforced by the ICO with fines of up to 17.5 million pounds or 4 per cent of worldwide turnover. The ICO's Guidance on AI and data protection sets the expectations: fairness across the AI lifecycle, transparency with the people whose data you process, a lawful basis, and a data protection impact assessment where the risk is high. Keep a person in the loop on money, safety or an upset customer, restrict which actions the AI may take, and review your supplier's security, retention and hosting before launch.[1][2]