Generative AI can transform customer experiences. But only if you focus on other areas first

AI can help staff focus on the most important customer concerns, so long as the business has a tight grip on its data.
Written by Mark Samuels, Contributor
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There's lots of hype about the potential power of generative artificial intelligence (AI), but real-world implementations are harder to find. While the technology could change the world of work forever, its implementation right now is focused on a few key areas -- and one of these is customer experience (CX).

Forrester expects generative AI to give CX teams a big boost through 2024. The tech researcher says service agents will use AI-powered tools to ask natural language questions and receive answers to customer questions rather than searching databases for information.

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Professional services firm Genpact also expects more businesses to use generative AI to find new ways to measure and reimagine customer experiences

Some pioneering organizations are already embracing AI for CX. Take software specialist MHR, which uses Clari Revenue Platform and the provider's AI-enabled tools to give staff visibility into sales performance.

Tim Lancelot, head of sales enablement at MHR, explained to ZDNET how Clari Copilot uses AI to summarize conversations and create smart actions that integrate into MHR's Salesforce platform.

"One of the big selling points of the Copilot conversational intelligence technology is that it sits within our existing Clari Revenue Platform," he said. "So, for example, I can look at deals and, at the sales stage, we can check our staff have talked about certain things, such as contracts."

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Lancelot said the sales team now benefits from a single view of customers and they got to that point quickly by creating a consolidated technology stack.

"You can't manage what you can't measure. And you can't manage effectively if you can't measure in real time. The key to success is summarizing information to help you make the next decision effectively -- and that's what Clari does," he said.

Another organization that's using AI to boost CX is Simplyhealth. The UK health solutions provider uses Salesforce Einstein for Service to help staff reply to email inquiries with a GPT-enabled response.

Dan Eddie, director of customer service at Simplyhealth, told ZDNET that conversational AI is helping to transform agent efficiency by ensuring staff email the right information to customers at the right time.

The GPT-enabled system searches the company's databases and generates automatic responses to frequently asked questions. Eddie said an email that might have taken an agent 12 minutes to answer now takes about a minute and a half.

Also: 5 ways CIOs can manage the business demand for generative AI

While Simplyhealth is already boosting CX through AI, Eddie said other digital leaders must find the right use case.

"There is a balance to be struck in terms of the purpose of your organization and what you're trying to do," he said. "Is there a problem your team is trying to solve? Is there an outcome that the customer needs? And then how does AI play a part in that journey for staff to achieve the purpose?"

Eddie said the long-term goal at Simplyhealth is to use AI to augment CX processes: "For us, AI is going to play a part in our service, but it won't be everything. It will be a part of how our customers and patients can access healthcare."

Caroline Carruthers, CEO at consultant Carruthers and Jackson, is another expert who said professionals must ensure AI-enabled CX solutions are tightly focused on business outcomes: "Generative AI is the thing that's caught the public attention -- everybody's trying to get a generative AI hammer."

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Carruthers told ZDNET that professionals must temper business excitement by focusing on key considerations, such as internal capabilities.

"There's a cost of entry because you have to learn a whole new set of tools," she said. "And AI is an expensive set of skills to bring into an organization because everybody's interested."

Toby Alcock, CTO at Logicalis, referred to another business challenge: Hallucinations. Professionals who explore AI for CX will need to understand the limitations of the technology and the potential for generative AIs to produce inaccurate answers to questions -- or worse.

"I think there's a lot of potential for AI," said Alcock to ZDNET. "But for every positive story, you'll see the absolute nightmare scenario where a chatbot takes an extreme view and has to be shut down quickly."

Evidence suggests professionals must take a tight grip on enterprise information before they dabble in AI. Research from Aberdeen Group suggests just 35% of businesses today are satisfied with their current use of data when managing their CX programs.

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Meanwhile, Carruthers and Jackson report just 5% of businesses boast a high level of AI maturity, established AI departments, or clear AI processes.

Alcock said organizations must focus on the processes, standards, and policies that ensure data is used efficiently and securely: "I think governance, in terms of how you put some very defined boundaries around AI models, will become even more important."

That sentiment resonates with Sophie Gallay, global data and client IT director Etam, who joined the French retailer in February 2023. She's creating a group-wide strategy for key data issues, such as architecture, tooling, governance, and value.

This first phase of the strategy, which will run until the end of 2024, is focused on constructing a fresh data platform using Snowflake technology. As Etam completes the first phase of the strategy, Gallay will look for fresh ways to help Etam make the most of its data, including generative AI.

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She told ZDNET that the first use cases for AI are likely to focus on boosting support staff productivity and responsiveness.

"I want to dedicate their time to important topics," she said. "And I'm pretty sure a great product fuelled by generative AI could answer the level-one requests from our clients."

However, Gallay's priority is exposing the benefits of AI -- and that's all about building foundations, tempering business expectations, and proving value.

"Right now is a great moment for us because we have the necessary teams to test and the technical and data maturity to create products at scale once we're ready," she said.

"The worst scenario would have been to start something a year ago, to see that it has immense value, and then to stop and say, 'Sorry guys, we can't scale because we don't have the data platform, the data, and the governance.' I want to ensure that, from the second we say, 'Okay, it has value, let's scale it,' that we have the capabilities to do so."

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