RingCentral’s latest earnings call hinted at a shift many CX leaders already feel in their bones. The real value in AI is moving from “after the call” to “during the call.”
On the same day as its Q4 2025 earnings update, the vendor also announced a collaboration with OpenAI to deliver 'advance enterprise-grade voice AI,' referencing models 'like GPT-5.2,' with an emphasis on real-time performance.
That product news also sharpens one of the most telling metrics from the earnings call: RingCentral’s AI Conversation Expert (ACE) customer count now exceeds 4,800, up 144% year-over-year. Together, the two updates point to an agent experience (AX) story that is starting to harden into an operational reality.
OpenAI’s Role: From Insight To In-Call Action
RingCentral’s OpenAI integration announcement pushes the conversation forward from analysis to action.
The company says it is integrating OpenAI to 'advance enterprise-grade voice AI,' and it calls out models 'like GPT-5.2,' with an emphasis on real-time performance, as Kira Makagon, President and COO at RingCentral highlighted: "OpenAI enables us to turn powerful technology into tangible business value, from AI that answers customer calls to AI that assists every employee.”
Giancarlo “GC” Lionetti, Chief Commercial Officer at OpenAI, also leaned into the live-workflow angle:
“RingCentral shows how advanced AI moves beyond insight and into action. By working together, we are bringing intelligence directly into live voice conversations, helping enterprises move faster, serve customers better, and act with confidence.”
For AX, this matters because it accelerates a specific operational pattern: real-time agent assistance that behaves like a coach in the ear.
In practice, that can mean next-best-action prompts, compliance reminders, better discovery questions, and objection handling that arrives while the customer is still on the line.
RingCentral’s own product positioning supports that direction. The OpenAI announcement describes natural, context-aware interactions and ties them to RingCentral’s 'low-latency voice infrastructure,' which is a requirement if guidance is going to be useful in the moment.
The New CX Battleground Is The Live Call
Contact centers have spent years optimizing what happens after an interaction. Teams built QA scorecards, coaching cadences, and post-call analytics, and they also chased better summaries to reduce admin time.
But the friction point has stayed stubbornly consistent: the call itself is where outcomes are won or lost, and where agents need support most.
RingCentral’s AI portfolio framing makes this 'before, during, after' model explicit.
Makagon described how AIR, AVA, and ACE align to different moments of the conversation lifecycle, and she placed ACE firmly in the improvement loop after the call, stating:
“After the call, our AI Conversation Expert, or ACE, closes the loop, analyzing every recorded interaction for insights that improve coaching, quality and performance across the organization.”
That line sounds familiar, but the growth figure attached to it is the part that should make CX leaders pause. A 144% year-over-year increase suggests that more organizations are treating conversation intelligence as foundational to performance management, and also scaling it across sites, queues, and roles.
Why RingCentral’s 144% Metric Looks Like A Market Signal
A single vendor metric is not a market study, and RingCentral’s ACE number is a customer count growth figure, not a disclosed usage volume metric.
Still, the direction is hard to ignore, and it maps to what many operations teams are prioritizing: better consistency, faster ramp, and fewer escalations, even as channels, products, and policies keep changing.