OpenAI on OpenAI: Applying AI to Our Own Workflows

Quick Overview

OpenAI is applying AI internally to enhance workflows across sales, HR, and support, leading to significant improvements like 70% ticket deflection and saving reps one full day per week, achieved by building internal tools like the GTM Assistant and OpenHouse, which leverage AI to amplify expertise and scale operations efficiently.

Key Points: OpenAI's internal application of AI resulted in 70% ticket deflection and saved sales reps approximately one full day per week for higher-leverage work. The GTM Assistant, built using an architecture of Surfaces (ChatGPT/Slack/OpenAI Platform), Agent Orchestration (SDKs, GPT-5), and Connectors/Knowledge (Databricks, Vector Store), supports sales workflows. OpenHouse, an internal HR/People tool, uses a similar layered architecture, connecting to HR systems and OpenAI Vector Store to onboard new employees and answer policy questions. The Support Agent framework, using Help Center/Articles and Support/SOPs data, demonstrated AI handling support tasks, achieving 80% positive evaluation. The process for creating these internal AI tools involved reviewing conversation logs, defining gold standards for actions, codifying standards into knowledge, and connecting knowledge for evals/classifiers. OpenAI is experiencing exponential growth in support tickets following product launches like ImageGen, highlighting the need for scalable support solutions.

Context: The presentation, delivered by Scotty Huh from GTM Innovation at OpenAI DevDay [2025], focuses on how OpenAI applies its own AI technology internally to improve efficiency and scale operations across different departments, specifically highlighting solutions for Go-to-Market (GTM) and HR/People functions, and later, scaling customer support.

Detailed Analysis

The presentation details OpenAI's internal application of AI to solve scaling challenges across GTM, HR/People, and Support functions. For GTM, the GTM Assistant framework, which utilizes ChatGPT, Slack, and the OpenAI Platform across three layers (Surfaces, Agent Orchestration via SDK/GPT-5, and Connectors to Databricks/Vector Store), successfully amplified sales expertise. This resulted in reps exchanging over 20 messages weekly with the assistant and saving about one full day per week for higher-leverage work. The presentation also introduced OpenHouse, an internal tool for HR/People knowledge, built on a similar structure, which helps new hires quickly understand company operations and policies by connecting to HR systems and OpenAI Vector Stores. For customer support, the Support Agent model, which uses ChatKit and Realtime API surfaces, demonstrated strong results: 70% ticket deflection, a 30% increase in solution rate, and 80% positive evaluation, outperforming legacy systems by 30%. The speaker emphasized that the key to scaling support is building this AI into familiar tools and creating a self-improving loop driven by evals and guardrails. He concluded by challenging the audience to use these principles to build internal AI tools that their teams cannot live without.