After nearly three decades of innovation in business communications, RingCentral is a global company with thousands of employees and annual revenue exceeding $2.6 billion. The company is now expanding that tradition by shifting toward AI‑native ways of working: by equipping every employee with ChatGPT Work and Codex, RingCentral aims to let anyone—regardless of engineering background—build impactful products and infrastructure.
The AI‑Native Challenge: experiment to practice
The Office of the CEO sponsored an AI‑Native Challenge to raise AI fluency across the global engineering organization. Participants were given ChatGPT Work and Codex and asked to deliver a complete end‑to‑end project without prescribed workflows or other constraints.
The initiative went beyond a simple coding exercise: it immersed participants in the full AI‑native development lifecycle, from planning and implementation to testing, documentation, CI/CD, and iteration. Nearly every participant produced a working repository, and thousands of employees—including non‑technical staff and even executives—delivered functioning projects.
Faster product development through internal use
The company treats the challenge as a practical model for a broader strategy: using AI internally to speed up product delivery to customers. RingCentral applies the same Codex‑enabled approach to accelerate development of its AI‑powered product portfolio, including RingCentral AI Receptionist (AIR), AI Virtual Assistant (AVA), and AI Conversation Expert (ACE). The approach shortens the time from idea to shipped customer feature.
"The clearest lesson from the challenge was that AI‑native development isn’t about replacing engineers—it’s about amplifying them. AI accelerates the entire development cycle, while humans remain in the loop, guiding product requirements, providing business context, making architectural decisions, and ensuring every outcome is tested and verified."
— Engineering leader at RingCentral who spearheaded the project
Operational change: how the PMO uses ChatGPT Work
Encouraged by the AI‑Native Challenge, non‑engineering departments at RingCentral have adopted AI‑native practices. The Program Management Office (PMO) used ChatGPT Work to build what amounts to an operating system for program management, replacing scattered notes and chat histories with AI‑powered workflows for status tracking, reporting, release governance, and knowledge transfer.
One concrete application is automated status reporting: the PMO team created workflows in ChatGPT Work that generate notifications from issues tracked across Jira, Google Sheets, CRM systems, and other sources. Rather than entering meetings asking "what changed?", teams now arrive with blockers, owners, and actions already identified.
What began as an open invitation to experiment—with thousands of engineers building from scratch—has matured into the operational backbone used by teams like the PMO. By reducing manual coordination, ChatGPT Work enables RingCentral’s PMO to handle more projects with greater accuracy.
From individual skills to company infrastructure
Across engineering and operations, the same pattern applies: giving employees room to experiment with AI builds more than individual capability—it builds the infrastructure the company runs on. Through internal adoption of AI‑native tools, RingCentral is accelerating development, improving operational efficiency, and narrowing the gap between concept and customer‑facing features.
