AI transforms CX to go beyond the chatbot

AI has transformed the way customers and businesses interact. While early chatbots, before the advent of public LLMs, were often clumsy and failed to help customers, the new wave of AI-powered customer service agents has drastically changed the customer experience.

"The biggest thing we're seeing is the changes in expectations of consumers with the brands and businesses they interact with," said Nigel Lindsay-Smith, the Managing Director for ANZ at NiCE.

He said direct customer interactions that are fully automated for support from product or service selection through to troubleshooting are now supported by AI. Complicated problems can be solved without a human in the loop and consumers are aware that the technology is out there.

"Customers are using tools like ChatGPT and Claude to help them. They know the power of these capabilities," he added.

The growing trend of contact centre as a service (CCaaS) has aligned with the adoption of AI. Organisations leveraging CCaaS platforms, through established partnerships, have gained a strategic advantage in integrating AI solutions. This is partly due to familiarity with technology-driven service delivery and the reduced complexity of transitioning from long-term, on-prem deployments to a more agile, service-oriented approach.

One of the big advantages that comes with an integrated platform approach is the ability to use AI in a multi-modal way. Lindsay-Smith explained that if a chatbot operates on a website there may be a back and forth interaction. But an agentic AI capability can take an inbound inquiry from a sale, link that to a credit check, and then create an order that is received by the customer as an SMS with a DocuSign capability. Order fulfilment can be managed by an AI agent.

"You can create really complex workflows without any human in the loop at all," he said. "That's probably the biggest area organisations are pushing on. But it is also the biggest area where they see risk although it's the biggest area that's will move the needle."

The level of risk organisations are prepared to accept when using AI agents in this way depends on several factors. Lindsay-Smith said NiCE works with clients in heavily regulated industries. However, he noted that there are some business cases for using AI agents in those environments.

"Many of our customers are in financial services, telecommunications and travel. And in those areas, we're seeing less appetite for risk. They're using AI to assist human agents to find the right information, improve the accuracy of information given, and minimise human error in those engagements," he explained.

Looking at how AI is used in the ANZ region, Lindsay-Smith made an interesting observation. He sees Australia lagging in less-regulated use-cases while New Zealand is probably ahead and more open to taking risks, although they're very calculated risks.

A core part of NiCE's platform is its core AI solution Cognigy. It enables organisations to deploy AI agents in their contact centre to deliver fast and personalised service to customers. The platform enables the setting of boundaries and guardrails to ensure AI agents work in the way developers intend. This enables them to bring AI to their customers while minimising the risk of a reputation damaging event.  

Perhaps the most challenging question for organisations is how to predict and measure the return on their AI investments. Most technology investments focus on reducing costs or increasing productivity. While AI can do those things, measuring the ROI when it relates to CX can be more complex.

"CX is very difficult to measure. Normally NPS [Net Promoter Score] up means customers are buying more, are happy and are referring more. It's very difficult to quantify that. But we have a variety of metrics that we use with our analytics suite that allow us to measure the before and after when an AI solution is running," said Lindsay-Smith.

He also noted that in Australia there are not many organisations measuring ROI as well as they would like. While they can recognise the potential value of the AI prize when they do deliver well in those areas, their ability to truly measure it right now is limited. And with many AI projects failing to move from proof of concept to production, the ROI question remains important.

"Not many organisations are using generative AI end-to-end across their estate. They're seeing incremental benefits but are unsure what this would look like if it moved into sales or if you moved into back office. I don't think any organisations in Australia have cracked that," he said.

AI's impact on customer experience is accelerating, driven by evolving consumer expectations and increasingly sophisticated AI agents. Integrated platforms, particularly those leveraging CCaaS, provide a strategic advantage in deploying these solutions. While complex workflows and multi-modal AI interactions offer potential, organisations are navigating risks through careful implementation although predicting and measuring ROI remains a challenge.