Globally and locally, the customer service industry is evolving as new communication channels and the rise of artificial intelligence (AI) push organisations to re-evaluate traditional approaches and models to deliver exceptional service.
New research shows that while nearly 90% of organisations plan to use AI to enhance the customer experience (CX), 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, according to the research 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. This will continue to be 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 challenge lies around conflicting business priorities, as reported by 55.2% of organisations surveyed. This often stems from the organisational structure surrounding technology and data.
Cybersecurity and governance concerns 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 challenges include broken processes and IT issues. The number of organisations citing a lack of skills as an obstacle has increased 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
AI in customer service is often associated with digital assistants or bots. However there are numerous use cases that can help organisations enhance CX, starting at the back-end.
The study shows that the most popular use 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 plan 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 mandatory security checks or read outs, 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 previously unavailable.
Traditional QA often involved manual reviews, with only 1% to 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 help improve workflows and processes, manage ticket prioritisation and distribution, and match 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 SA.
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 adviser who focuses on dealing with more complex engagements.
This new role should be supported by agent assist tools, including automated note-taking, call wrap-ups, and call dispositions, which help reduce the cognitive load on the human adviser.
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 adviser. This helps improve first call resolution (FCR), and further enhances the customer experience. FCR and knowledgeable advisers are 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 advisers with the right tools and information, AI ensures 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.
• About the author: Kelvin Brown is customer operations executive at Telviva.
This article was sponsored by Telviva.
