Insight 2
Agentic voice AI succeeds at high-volume tasks, though governance sets the pace of expansion
For businesses that cite voice as a critical business channel, use of and interest in agentic voiceAI is already high. Of the leaders we interviewed, 57% have actively deployed voice AI agents across internal and external channels, and another 10% are in early-stage pilot phases. Just under a third (32%) are still evaluating adoption.
57%
Among leaders with active agentic voice AI deployments, 82% report positive ROI. They cite cost reduction, time savings, and the ability to redirect human staff to more complex work as the main benefits.
Businesses tend to start by assigning agents to the highest-volume, repetitive, lowest-complexity tasks first, usually in external-facing channels. Common use cases include customer support and service, appointment scheduling, call routing and intake, and automated reminder sand follow-ups. Once agents prove themselves in these areas, leaders look for opportunities to expand their responsibilities.
Customer support leads named use cases by more than 2.5x
Customer support & service
Scheduling & appointments
Call routing & intake triage
Order status & processing
Reminders & follow-ups
Other
Internal / employee support
Billing & payments
Agentic voice AI is deployed cautiously and successfully
As adoption matures, the findings also point to a tension between expanding how voice AI is used and setting stronger conditions around its use. Enterprises stand out on both fronts: they are more likely to use conversation data to make decisions while also requiring stronger governance.
Enterprises are further ahead in putting conversation data to work. 73% operationalizeconversation data for decision-making, compared with 50% of mid-sized and 48% of small businesses.
of mid-sized businesses
of small businesses
At the same time, 70% of enterprises say voice AI is acceptable only with strong guardrails, verified accuracy, and human handoff, compared with 42% of mid-sized organizations and 41% of small businesses.
Taken together, the findings show a more nuanced picture of adoption at scale: enterprises areputting conversation data to work more extensively while also setting stronger conditionsaround how voice AI operates.
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