For many SMEs, the promise of AI—automation, efficiency and cost savings—can seem like a silver bullet. Yet, customer opinions about AI are mixed.

Concerns about workforce changes are widespread. With over 266 million businesses already using or exploring AI in their operations, it’s clear that automation is here to stay. This rapid adoption has sparked concern, with 77% of people fearing that AI will prompt job losses in the near future. 

However, the future isn’t as bleak as it might appear. The World Economic Forum projects that AI will create 97 million new roles, ranging from data curators to ethics specialists. Similar to the industrial revolution, the workplace will evolve, but machines will not take over entirely. Human expertise will still be essential.

In addition to workforce concerns, past frustrating experiences with chatbots have led to scepticism about AI’s ability to deliver nuanced, personalised support. But if YouTube’s recommendation algorithm can consistently suggest content that users enjoy, sometimes even better than they might choose themselves, then there’s every reason to believe that chatbots, when properly trained and refined, can also deliver significant value.

The real issue is not that AI cannot enhance customer service and the overall experience, but rather that its effectiveness depends on how it is applied. To see chatbots succeed in customer service, the first step is to stop viewing the technology as merely a tool for deflecting contact and reducing the number of human agents.

Self-service evolved

The concept of using technology to minimise the need for human agents isn’t new and before AI it was simply referred to as self-service. Support articles, guides, informational pop-ups (tooltips), videos and even platforms like Google and social media help users handle predictable and repeatable tasks on their own. Most customers prefer not to phone or email for support, so these easy to access and understandable resources can significantly reduce the need for direct customer support, allowing agents to focus on the more nuanced or complicated requests.

While humans establish the ethics, values and culture of a business, chatbots are just another tool in the self-service arsenal. Much like support guides, they vary in effectiveness. Some are adept at handling simple queries, while others fall short.

The quality of support chatbots can provide depends on the complexity of the queries they are designed to address and how well they are configured. This variation influences how many support cases can be effectively managed through technology. And although they can reflect some of the company’s personality, chatbots cannot forge the emotional connections that humans can.

However, focusing solely on chatbots misses the broader picture of how customers, agents and AI interact.

Efficiency in the contact centre

To truly enhance the customer experience, businesses should consider how AI can simplify operations within the contact centre.

This technology already plays a prominent role by forecasting contact volumes, optimising rotas and routing customer calls and queries to the best-suited agents. Beyond these functions, AI offers additional benefits to help agents become more efficient. For instance, automatic post-call wrap-ups with summaries based on conversation transcripts can save valuable time and ensure accuracy. Additionally, AI can automatically redact any sensitive information discussed during calls, protecting customer privacy.

During the onboarding of new agents, AI can provide instant access to relevant internal tools and processes depending on the context of the interaction. This helps new hires quickly grasp the company’s systems and workflows, speeding up their integration.

Many contact centres are already heavy adopters of AI, but do so in a way that is not publicly visible. They focus on boosting agents’ capabilities, rather than replacing them.

Transforming support from the inside out

As AI improves efficiency in the contact centre, it’s also valuable to look at strategies for reducing the overall demand for support, whether it’s through self-service options or direct interaction with agents.

One effective approach is to use AI to analyse the customer journey and apply customer segmentation to better understand and anticipate customer needs.

By focusing on these aspects, businesses can proactively identify potential problem points and address them before they escalate. AI can help in understanding customer intent and predicting contact patterns, which allows companies to prepare for future interactions and reduce the frequency and complexity of support requests. Additionally, evaluating customer lifetime value, personalised offers and risk analysis enables more strategic decision-making, further minimising the need for support.

Large language models can also enhance this process by summarising feedback and interactions. They provide an objective and repeatable view of customer sentiments that might get missed in traditional support. Here is where the absence of emotions becomes an advantage as it eliminates personal biases and emotional interpretations that human agents might unintentionally introduce.

While these may not appear to be directly related to contact centre operations, they contribute by presenting clear insights from vast, unstructured data that comes directly from the customers.

The connected agent

With AI transforming customer support, it’s clear that the role of the agent is evolving, rather than disappearing. In a modern support model, an agent has access to contextual information about the customer’s call, including their aims and the next best action. They benefit from AI tools that assist with navigating internal policies and tracking any changes.

This shift changes the role of customer service agents from primarily providing technical knowledge and relaying customer feedback, to embodying the company’s ethics and values. They also provide data and insight to train and refine AI systems further.

This raises a crucial question: do we still need human agents? While hyperautomation could be introduced, it won’t solve all the complexities of support. AI excels at prediction but falls short in areas like emotion, creativity and ethical judgement. When faced with unpredictable requests, the best agents make emotional connections that create exceptional experiences and decide if they can go the extra mile for customers.

Chatbots and automation can provide positive experiences and efficiently resolve many issues. But in critical scenarios, a human agent will better understand the urgency and find a creative solution even if the computer says no.