How RingCentral builds AI-native work from engineering to ops

RingCentral, a global business communications company with over $2.6 billion in annual revenue, is adopting AI-native development practices using ChatGPT Work and Codex. The initiative allows employees at all levels to build products and infrastructure without requiring deep engineering expertise, supported by an AI-Native Challenge sponsored by the Office of the CEO. Participants developed end-to-end projects, including planning, testing, and deployment, with thousands delivering functional results regardless of technical background.

The challenge served as a model for RingCentral’s broader strategy to use AI internally for faster product development. The company applies Codex-enabled workflows to enhance its AI-powered portfolio, including RingCentral AI Receptionist (AIR), AI Virtual Assistant (AVA), and AI Conversation Expert (ACE). This approach reduces the time between concept and customer deployment, with engineers and non-engineers collaborating to refine and test AI-driven features.

Non-engineering teams, such as the Program Management Office (PMO), have adopted AI-native workflows using ChatGPT Work. The PMO replaced manual tracking with AI-powered systems for status updates, reporting, and governance, integrating data from Jira, Google Sheets, and CRM systems. Automated workflows now generate notifications with blockers, owners, and action items, improving meeting preparedness and reducing coordination overhead.

The experiment has evolved into a core operational framework across RingCentral, with AI tools becoming the backbone of both engineering and program management. By empowering employees to experiment and integrate AI into daily workflows, the company has built scalable infrastructure that enhances efficiency and accuracy, demonstrating how internal AI adoption can transform business operations.