This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.
Generative AI and Data: Critical Elements for Future CX
There’s still plenty of hype to go around, but as we settle into the reality that generative AI will be a part of many if not most conversations in our industry, we’re also starting to see what the early use cases have to show us. No Jitter has run a number of posts looking at vendors’ generative AI implementations (such as Genesys and Five9), as well as analyzing the role of generative AI in modernizing the customer experience, and taking a hard look at some of the challenging issues like security. In short, if you want to have a conversation about generative AI that is neither utopian nor apocalyptic, there’s plenty to talk about.
One subject that we’ll be hearing more about is the language models on which generative AI is based. Most of us have become familiar with the acronym LLM, for “large language model,” but analysts Dan Miller and Derek Top of Opus Research will be taking a nuanced approach when they keynote an Enterprise Connect virtual summit focused on customer experience next month (registration and agenda here). Their talk is entitled, “Language Model Optimization: The New Frontier for Contact Centers,” and it's notable that in the writeup for the session, they refer to “Language Models of all sizes.”
I don’t yet know the details Miller and Top will share in their keynote, but it seems clear that enterprise leaders, particularly IT/communications/CX technology pros, will need to understand more about the specific language models used by the generative AI they’re implementing in the contact center. The other key element for optimizing generative AI happens to be the subject of the other keynote in next month’s virtual summit: Data.
Data integration has been a hot topic in the contact center for a few years now, as CX leaders recognize that the more effectively they can unlock customer and other data, the better they can get at resolving customer issues—whether the interface is an agent or a self-service Web page. Our virtual summit’s second keynote, “Why You Must Optimize Data Integration Now for CX,” will be delivered by Mila D’Antonio of Omdia, whose focus will extend beyond just generative AI to the bigger picture of how systems for the contact center leverage and integrate customer data, and why it’s critical that this be an ongoing process.
Generative AI is only as good as the data it draws on. Even if these AI systems start out primarily in an agent-facing role rather than customer-facing, their ability to improve agent metrics (and quality of life at work) is likely to vary wildly unless the enterprise has a complete strategy for implementing the technology that supports generative AI. I hope you can join us next month when we bring together the issues of generative AI and data integration for an enlightening virtual summit.