RingCentral AIR Pro Launches at Enterprise Connect: Voice-First Agentic AI for Customer Support
RingCentral introduced AIR Pro, a voice-first agentic AI platform built to automate customer interactions across voice and digital channels. The release fits a clear shift in enterprise communications: real-time voice AI working alongside digital to handle complex service requests without scripted flows.
The promise for support leaders is straightforward: fewer transfers, less repetition, faster resolutions, and clean handoffs to humans when needed.
What AIR Pro Is (and Why It Matters)
AIR Pro lets teams build autonomous digital agents that converse naturally, interpret intent, and execute real tasks across business systems during the interaction. Think authentication, scheduling, case creation, or record updates done in the flow of the call or chat - not after the fact.
It sits on top of RingCentral's AI ecosystem and connects the company's earlier components - AI Receptionist, AI Virtual Assistant (AVA), and AI Conversation Expert (ACE). Together, these tools share context and learn from every interaction so both AI and human agents get smarter over time.
Key Capabilities for Customer Support
- Conversational problem-solving: Blends natural conversation with real task execution. The agent can take actions mid-conversation to cut friction and reduce handle time.
- Omnichannel consistency: The same AI agent works across voice and digital with shared context, so customers don't have to repeat themselves when switching channels.
- Multilanguage with auto-switching: Supports multiple languages and lets users switch language on the fly without restarting.
- Real-time reasoning and execution: Interprets intent, manages multi-step workflows, and completes actions like authentication, appointment booking, case creation, and updates to records.
- AIR Pro Studio (no-code): Visual tools and templates help non-developers stand up agents for support, appointment, and order management use cases.
- Deep integrations: Connects to enterprise systems so the AI can perform actual business actions, not just provide information.
- Insights and optimization: Analytics to monitor agent performance, update knowledge, adjust workflows, and retrain where needed for measurable improvement.
- Governance and security: Controls to support compliance and internal policies, with transparency into how AI agents interact with customers and systems.
The Problem It Targets
Most support operations are spread across multiple tools. Agents alt-tab through CRMs, billing, scheduling, and knowledge systems during a single call. That drives up handle time and increases error risk.
Earlier automation - IVR trees and rule-based chatbots - breaks when conversations go off script. AIR Pro moves beyond menus and static rules by interpreting intent, maintaining context, and executing multi-step tasks in the moment.
Expected Outcomes for Support Teams
- Shorter time to resolution by executing actions during the conversation.
- Fewer handoffs and less customer repetition with shared context across channels.
- Higher containment on common requests; human agents focus on high-value and edge cases.
- Faster deployment cycles with a no-code builder and templates.
This approach lines up with how customers still seek help on complex issues: voice remains the channel of choice when the stakes are high or the problem is messy. AIR Pro brings AI into that call without adding friction.
How to Pilot AIR Pro (Practical Playbook)
- Start with the right intents: Pick high-volume, low-risk workflows (order status, appointment changes, password/account support, simple billing questions).
- Map systems of record: Identify the APIs and data needed for read/write (CRM, ticketing, billing, order management). Set clear access rules and audit requirements.
- Design escalation paths: Define when the AI hands off to a human. Preserve context so customers never repeat details.
- Authenticate in-flow: Use voice or OTP flows early in the conversation so tasks can complete without back-and-forth.
- Measure what matters: Track containment rate, AHT, FCR, CSAT, and transfer rate. Compare pilot queues against control groups.
- Close the learning loop: Review transcripts, refine intents, update knowledge, and tune workflows weekly at first.
- Governance first: Enable logging, consent notices, PII redaction, data retention policies, and clear fallback behavior for outages.
Where It Fits in RingCentral's AI Stack
AIR Pro is the orchestration layer that deploys autonomous agents. It works with AI Receptionist for front-door triage, AVA to assist customers across digital and voice, and ACE to analyze conversations and support complex resolutions. Together, they create a learning flywheel that strengthens the full conversation lifecycle - from greeting to resolution to analytics.
What Support Leaders Should Ask
- Can the agent complete end-to-end workflows in our core systems (create/lookup/update) without human intervention?
- How is context shared across channels and preserved on escalations?
- What controls exist for data access, masking, and audit trails?
- How quickly can we build and deploy a new intent with the no-code tools?
- What KPIs and dashboards are available for continuous optimization?
Helpful Next Steps
For hands-on guidance, see AI for Customer Support. If you lead a contact center rollout or supervise AI agents, review AI for Call Center Supervisors.
AIR Pro signals where customer service is heading: voice-native AI that thinks, acts, and collaborates with your team - so customers get what they need without the drag of fragmented systems.
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