The potential of generative artificial intelligence (AI) has been widely discussed, but it is difficult to find real-world applications. While this technology has the potential to revolutionize the workforce, its current applications are mainly focused on a few key areas, one of which is customer experience (CX).

Forrester, a market research company, predicts that generative AI will bring significant advancements to CX teams by 2024. This technology research firm states that service agents will use AI-driven tools to ask natural language questions and receive answers to customer queries, rather than searching for information in databases.

Professional services company Genpact also predicts that more businesses will use generative AI to find new ways to measure and reshape customer experience.

Some pioneering organizations have already started using AI for customer experience. Take software expert MHR, for example, which uses the Clari Revenue Platform and AI tools provided by vendors to help employees understand sales performance.

MHR's Sales Enablement Manager, Tim Lancelot, explains how Clari Copilot uses AI to summarize conversations and create intelligent actions that integrate into MHR's Salesforce platform.

"One of the selling points of Copilot's conversational AI technology is that it is built into our existing Clari Revenue Platform," he said. "For example, I can review deals and check if our employees have discussed certain things, like contracts, at different stages of the sales process."

Lancelot states that the sales team now benefits from a single view of the customer, which they quickly achieved by creating an integrated tech stack.

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

Meanwhile, the Carruthers and Jackson report states that only 5% of companies have a high level of AI maturity, established AI departments, or clear AI processes.

Alcock suggests that organizations must focus on ensuring efficient and secure data usage processes, standards, and policies: "I think governance will become even more important in setting very clear boundaries for AI models."

This viewpoint resonates with Sophie Gallay, Global Data and Customer IT Director, who joined French retailer Etam in February 2023. She is developing a group-wide strategy for key data issues, such as architecture, tools, governance, and value.

The first phase of this strategy will continue until the end of 2024, with a focus on building a new data platform using Snowflake technology. As Etam completes the first phase of the strategy, Gallay will explore new ways to help Etam fully leverage its data, including generative AI.

"I want them to spend their time on important topics. And I am convinced that an excellent product driven by generative AI can answer our customers' primary requests," she said.

However, Gallay's immediate priority is to demonstrate the benefits of AI, which entirely depends on establishing foundations, adjusting business expectations, and proving value.

"Now is a good time for us because we have the necessary team for testing, and once we are ready, we have the technology and data maturity to create products at scale," she said.

"The worst-case scenario is starting something a year ago, realizing it has tremendous value, and then stopping and saying, 'Sorry, we can't scale because we don't have a data platform, data, and governance.' I want to ensure that from the moment we say 'Okay, it has value, let's scale it,' we have the capability to do so."