AI in CX: Separating Fact from Fiction – How will the role of the human contact centre agent change and will AI replace contact centre agents? Robert Mansfield, CTO at Content Guru, discusses.
Greater agent efficiency, hyper-personalised experiences, and overall improved customer satisfaction are all benefits realised through artificial intelligence (AI), and specifically generative AI (GenAI), and its application to CX. The use of GenAI APIs and GenAI-enabled applications is set to expand rapidly in the next few years, as organisations look to improve efficiency alongside agent and customer experiences. As GenAI continues to develop, it’s important to separate fact from fiction, and avoid rumours and misinformation that so often dominate the narrative; to provide clarity, we’ve analysed some of the most common questions, to help inform CX leaders and the wider public.
How will the role of the human contact centre agent change and will AI replace contact centre agents?
Early critics of AI prophesied that AI would take human jobs. In realty, AI is working to ehance human agents. Just as the tractor didn’t eliminate farmers and Microsoft Word didn’t eliminate writers, the introduction of AI to CX will increase the productivity of agents, broadening their skill set and reducing training times and giving the organisation a competitive advantage. Professor Erik Brynjolfsson forecasts that GenAI tools will create an estimated 14-35% performance improvement in contact centres, with greater productivity gains for more novice employees.
Rather than waiting to be put through to a human agent, customers are greeted by streamlined processes that use AI to determine customer intention, whether through voice or digital channels, and direct them to the most appropriate available agent. When integrated with a customer data platform (CDP), this process is able to prepare the agent with information about the customer, such as previous interactions, helping to reduce the average handling time (AHT).
After an interaction, admin-heavy post-interaction wrap-ups can be streamlined using GenAI; automatically summarising the interaction, analysing sentiment and populating forms and databases with relevant updates. This reduces after-call work time, freeing up agents to focus on delivering great CX.
Will the rise in AI mean interactions are handled entirely by AI, from start to finish?
AI implementation should be a gradual process. If phase one of AI developments was to streamline communications before, during, and after interactions, future phases should focus on expanding the scope of the contact centre, encompassing more traditionally back-office and professional roles and creating a hub for communications, relationship building, and data orchestration.
Organisations that choose end-to-end AI for CX during these early stages are likely to be caught out by imperfections in the technology. They risk putting their brand’s reputation at the mercy of volatile AI start-ups and unproven, unregulated, and inadequately vetted systems. Gartner has argued that it is too risky, expensive, and difficult to completely replace all human-facing interactions with AI-enabled chatbots, and anticipates that the EU could mandate the “right to talk to a human” as part of consumer protection laws as early as 2028.
Organisations looking to capitalise on the productivity benefits of AI in CX should instead look to integrate AI-based applications piece by piece, from established providers well-versed in intelligent automation. This protects the rest of the contact centre, and the overall reputation of the brand, while allowing them to improve the processes that are most essential to their business.
Will genAI provide the correct answers to customers every time?
It’s important to understand that genAI isn’t correct every time. In recent months we have seen numerous examples of chatbots going rogue and tarnishing the reputation of the organisations that implemented them. From incorrect refund policies costing a Canadian airline hundreds of dollars to a parcel delivery firm swearing at customers, GenAI is not ready to take off the training wheels just yet. Large Language Models (LLMs) such as ChatGPT are subject to hallucinations which, without safeguards, could negatively impact the customer experience. Customers would quickly lose patience with brands if they’re misled during interactions. A tool that should vastly improve first-contact resolution could achieve the opposite, with customers needing further support to correct previous mistakes.
That said, it is possible to reduce the likelihood of egregious chatbot errors through appropriate optimisation techniques. Chatbots can be tailored for the kind of tasks they will need to perform, using a combination of grounding, prompt engineering, fine-tuning of existing LLMs and representation engineering to provide more accurate responses tailored to the use-case. It isn’t there to make up poetry or embarrass your brand in response to malicious user-generated ‘training questions’.
Navigating the AI Terrain
These common myths are testament to a lack of consensus on AI, with many voices warning against, or advocating for, increased use of the technology. Looking past the misinformation and striking the right balance between AI-automated processes and human-led interactions is important to maintaining first-class CX while benefitting from increased productivity. Embracing intelligent automation, under the guidance of reputable CCaaS vendors, helps to ensure a seamless and effective CX transformation while minimising the risks.
Robert Mansfield is CTO at Content Guru
Content Guru makes engagement easy. Its resilient cloud-based solution, storm®, is trusted by the world’s largest organisations to deliver mission-critical, first-class customer experiences quickly and accurately. Leading organizations, from the world’s largest enterprises to public sector agencies and mission-critical service providers, rely on storm‘s unrivalled 99.999% availability and flexible, future-proof capabilities.
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