RingCentral AI-Native Development and Operational Integration

RingCentral has adopted an AI-native approach to business operations and product development by deploying ChatGPT Work and Codex across its global workforce. This strategy compresses the distance between initial ideas and shipped features, enabling employees across all departments to build transformative products and infrastructure.

AI-Native Development Lifecycle

RingCentral utilizes AI-native development to accelerate the entire software lifecycle, from planning and implementation to testing, documentation, and CI/CD. This approach is designed to amplify human engineers rather than replace them, with humans remaining in the loop to guide product requirements, provide business context, and make architectural decisions.

To institutionalize these skills, the company launched the "AI-Native Challenge," a project sponsored by the Office of the CEO. Participants were provided with ChatGPT Work and Codex and tasked with building complete, end-to-end projects without mandated workflows. This initiative resulted in thousands of employees, including executives and non-technical staff, delivering functioning projects and creating working repositories.

Accelerating the AI-Powered Product Portfolio

RingCentral applies Codex-enabled development to speed up the delivery of its AI-powered product suite. This process directly impacts the development of the following tools:

• RingCentral AI Receptionist (AIR)
• AI Virtual Assistant (AVA)
• AI Conversation Expert (ACE)

By reducing the time required to move from concept to shipment, RingCentral aims to sharpen its Agentic Voice AI portfolio through faster iteration cycles.

Automating PMO Operations with ChatGPT Work

Non-engineering departments, specifically the Program Management Office (PMO), have transitioned from manual coordination to AI-powered workflows. The PMO uses ChatGPT Work to create an operating system for program management that replaces scattered notes and chat histories.

Key operational improvements include:

• Automated Status Reporting: The PMO team built workflows that aggregate notifications and issues from Jira, Google Sheets, and CRM systems to automatically define blockers, owners, and actions.
• Release Governance: AI is used to streamline reporting and knowledge transfer.
• Increased Capacity: By reducing manual coordination, the PMO is able to manage a higher volume of projects with increased accuracy.

"ChatGPT brings my project context together. With ChatGPT Work, I can turn that context into actions and execution."

—Vaneet Seth, Senior Manager, R&D Efficiency, PMO, RingCentral