Generative AI promises to boost efficiency in CX, but businesses face adoption and compliance hurdles.
CX technology vendors always speed ahead of their customers when it comes to the latest and greatest; there's usually a gap between what they've released and what customers have adopted. But with generative AI, the gap seems as big as the ocean -- or at least one of the Great Lakes.
Even vendor research reports, known for putting a positive shine on survey data, acknowledge it. More than a quarter of the 5,500 business respondents internationally surveyed by Zendesk for its CX Trends 2025 report released this month have delayed deployment of AI "due to a lack of budget, knowledge, or internal support."
More than half of 2,300 senior IT decision-makers have not yet aligned their generative AI (GenAI) strategies with business needs, according to an independent survey conducted in October sponsored by consultant NTT Data. Only 39% of respondents reported "significant" generative AI investment so far, with 60% of the 2,300 respondents saying they've made "some investment," or are in pilot, trial and assessment phases -- some of it funded by third parties, some of it self-funded. One percent said they have no plans to invest in GenAI at all.
Yet it's coming. Companies like Salesforce and HubSpot are not only rolling out generative AI features at a furious clip, but they're also investing in AI startups to augment their platforms and bolster the health of prospective future acquisitions.
In CX, early adopters have found a home for generative AI in customer service and contact centers. Generative AI-powered bots -- called "agents" when paired with reasoning, or logic, engines that can make simple decisions autonomously -- have the potential for these applications because they aren't creating anything; they're just finding and summarizing answers more efficiently than AI predecessors.
CX agents, for all their potential, typically require much implementation work beyond switching them on. Users must not only define the roles and processes the AI agents will fill, but they also must get their customer data and knowledge repositories in order -- which is a tall order for many IT environments.
"We're actually using generative AI with our clients in a different way -- not putting it in front of their end customers, but pointing it internally at their own knowledge, both structured and unstructured," said John Seeds, chief marketing officer at global CX consultancy TTEC Digital, which counts some large contact centers among its clients. "To start, we say 'Hey, you've got some duplication here. You've got some inconsistencies there,' and go through this massive amount of data, clean it up, right? And then clean it up on an ongoing basis with either our managed services or tools or software.
"You then have a way that you can present that data in a more effective way externally, to reduce the number of inbound calls, reduce the number of dependencies on conflicting data, and really drive self-service in a more meaningful way. [That's] always critical in the contact center," Seeds said.
Getting one's data in order is also the key to launching GenAI tools for marketing and e-commerce teams. Among others, Google, Salesforce and Sitecore have released AI that can conjure content that might not represent a finished campaign or website, but creatives can get a good start with new ideas from generative AI -- some of them more fully formed than others.