Microsoft CEO Satya Nadella revealed his plans to transform the business's Dynamics 365 portfolio with generative AI (GenAI).
In doing so, the CEO honed in on the massive potential for GenAI within contact center environments.
During the tech giant's latest earnings call, Nadella stated: "Dynamics with the GenAI built-in: this is the category that gets completely transformed with GenAI, [with] contact centers being a great example.
We ourselves are on course to save hundreds of millions of dollars in our own customer support and contact center operations.
Meanwhile, the CEO saluted the recent release of the Microsoft Dynamics 365 Contact Center platform, the potential of its embedded GenAI, and the customers already deploying the offering.
"Our new Dynamics 365 Contact Center is a Copilot-first solution that infuses generative AI throughout the contact center workflow," he said.
"Companies like 1-800-Flowers, Mediterranean Shipping, Synoptek will rely on it to deliver better customer support."
Those companies will wrap the CCaaS solution around their CRM, which doesn't have to be the Dynamics 365 for the Customer Service offering. It also connects with third-party CRMs, like Salesforce.
That CRM-centric design underlines Microsoft's aim to build a more cohesive customer experience ecosystem for its customers, in which GenAI can thrive.
GenAI & the Contact Center
Within months of the ChatGPT-3 launch and the start of the mainstream GenAI hype cycle, the first contact center use cases came to market.
Why? Because many of the applications were already there. For instance, with NLP, businesses could already auto-summarize contacts.
However, such use cases previously came as part of big, expensive conversational analytics solutions, with vendors spending hundreds of hours engineering them.
Then, with LLMs – which can automatically extract intents and entities before generating content and insights - the need for all that engineering fell by the wayside.
So, businesses – newer to the contact center space, like Microsoft – could recreate these use cases with GenAI much more quickly and cost-effectively.