Globally and locally, the customer service industry is in a state of change, driven by the proliferation of communication channels and the rise of artificial intelligence, pushing organisations to re-evaluate longstanding approaches and models to delivering exceptional service.

New research shows that although nearly 90% of organisations plan to use AI to enhance the customer experience, just under 45% have implemented the technology, suggesting an operational disconnect.

While it is growing in importance, the implementation of AI-enabled solutions faces several obstacles, says the report, What contact centres are doing right now. Budget has been identified as the biggest barrier, with just over 68% of organisations stating that a lack of funds prevented them from achieving their operational goals. The reality is that this will continue to remain as a stumbling block until company leadership begins viewing the contact centre as a value generating centre, rather than a cost centre, as has traditionally been the case.

A second, significant challenge lies around conflicting business priorities, as reported by 55.2% of organisations surveyed. This often results from the organisational structure surrounding technology and data; concerns around cybersecurity and governance mean that the ownership of business data, software development (including for AI), and corresponding budgets often lie with the IT department. As a result, broader enterprise projects might be given precedence over initiatives that are aimed specifically at enhancing CX across the organisation.

Other longstanding challenges include broken processes and IT issues, while there has also been a jump in organisations attributing a lack of skills as an obstacle (from 17.6% to 23.3%), suggesting that contact centres are struggling to adapt to the evolving AI landscape.

Doing more with AI to enhance experiences

When considering the use of AI in customer service, one often thinks of digital assistants or bots, though there are numerous use cases that can help organisations enhance CX, starting right at the backend. The study shows that the most popular use of AI in the field is to enable centralised access to contact centre and business systems data. Centralisation of data is seen as a foundation to ensure successful AI deployments, and 67% of organisations already have this step in place or have plans to implement it within the next year.

AI is also now being used as a tool to manage complex regulatory requirements and compliance during live interactions. For instance, a digital agent can perform security checks or readouts that are mandatory, saving human agents minutes on every single engagement. This capability drastically mitigates compliance risk.

Then, the emergence of real-time quality assurance (QA) marks a pivotal step forward, as it represents a technology that was simply unavailable in previous years. Traditional QA often involved manual reviews, with only 1-3% of interactions being checked. With AI-driven automated call monitoring, the sample set checked for compliance items can be expanded to 100% of calls, providing comprehensive oversight that manual review cannot match.

The integration of large language models (LLMs) with automated QA and speech-to-text analytics further enhances this capability, and also significantly reduces the complexity involved in building complex queries or training models on specific words.

AI also enables functionality such as sentiment analysis of interactions across text, voice and video; supervisor assistance that provides supervisors with better, real-time metrics instead of having to rely on historical reporting; and automated scheduling tools that help proactively schedule agents based on available staff and past trends. Technology can further assist with improving workflows and processes, managing ticket prioritisation and distribution, and matching the right agent with the customer.

Ultimately, organisations are increasingly focused on the ability to take a conversation, transcribe it, analyse the sentiment and feed the results back to the human agent on their screen in real time – and deploying locally-hosted LLMs is one way they are attempting to speed up this process.

Reducing the load and accelerating issue resolution

The traditional agent role, defined by scripted workflows that are designed to manage specific interactions, is rapidly evolving. Transactional engagements are increasingly being diverted away from traditional voice calls, and towards self-service FAQs, bots and instant messaging such as WhatsApp chats – which are quickly gaining in popularity in South Africa.

As automation manages the administrative and transactional heavy lifting, essentially becoming “the agent of the past”, the human agent’s role shifts to that of being an advisor who focuses on dealing with more complex engagements. This new role should be supported by agent assist tools, including automated notetaking, call wrap-ups and call dispositions, which help reduce the cognitive load on the human advisor. This frees them to genuinely listen to the customer, understand the nuance of the issue, and respond with crucial empathy, rather than worrying about the technical functionality required to assist the caller.

For the customer, this ensures they can find the information they require quicker, either independently or through an empowered advisor, helping to improve first-call resolution (FCR) and further enhancing the customer experience, with FCR and knowledgeable advisers being recognised by the research report as the top two values customers prioritise.

For sales-related engagements, AI provides agents with all the necessary information for effective upselling and cross-selling, which ties back into the new approach of seeing the contact centres as a value generating centre rather than a cost centre.

Sustainable adoption of AI

While the reasons for implementing AI often include contact reduction and cost reduction, with both being among the top three drivers, there is a need to proceed with caution. Many organisations are taking the wrong approach, focusing narrowly on implementing AI solely to reduce costs, which is a strategy that often results in a worse CX. As experts warn, if underlying service journeys are already broken, AI will only frustrate customers faster.

The sustainable way forward requires a shift in perspective: AI must be used not to replace humans, but to supplement and support them. The goal is to deliver the highest level of service and customer satisfaction possible. By enabling human advisors with the right tools and information, AI ensures that they can deliver the truly exceptional service customers expect, fundamentally transforming the service function from a cost centre into a strategic value multiplier.

This human-centric approach ensures technology empowers people, allowing empathy to define the customer relationship, supported seamlessly by intelligent automation.

Whether you require an inbound or outbound call centre solution for voice or an omnichannel solution integrating multiple digital channels, Telviva’s Contact Centre as a Service (CCaaS) solution provides comprehensive platforms to streamline your contact centre operations. Contact us today.