OpenAI Blog→ original

NTT DATA cuts incident analysis to 30 minutes with ChatGPT Enterprise and Codex

NTT DATA Group has deployed ChatGPT Enterprise and Codex to 9000 employees. The headline result: IT incident analysis has dropped to 30 minutes, as engineers find the root cause of outages faster and automate routine work. The company is betting on secure, large-scale AI adoption rather than isolated pilots, expanding the rollout without putting corporate data at risk.

AI-processed from OpenAI Blog; edited by Hamidun News
NTT DATA cuts incident analysis to 30 minutes with ChatGPT Enterprise and Codex
Source: OpenAI Blog. Collage: Hamidun News.
◐ Listen to article

NTT DATA Group has rolled out OpenAI's ChatGPT Enterprise and Codex to 9000 employees and cut IT incident analysis time to 30 minutes, according to a corporate case study OpenAI published in 2026.

What NTT DATA deployed

NTT DATA Group deployed two OpenAI products: ChatGPT Enterprise for everyday work tasks and Codex for working with code and diagnosing technical failures. Access went to 9000 employees of the global IT integrator, which is part of Japan's NTT group.

  • 9000 employees got access to ChatGPT Enterprise
  • Codex is used for working with code and analyzing incidents
  • IT incident analysis time has been cut to 30 minutes
  • The stated goal is to scale AI securely across the group

ChatGPT Enterprise is OpenAI's corporate version of its chatbot with stronger data protection: the company does not use customers' work conversations to train its models. Codex is OpenAI's programming tool. It reads a codebase, suggests fixes, and carries out engineering tasks from a text description.

Why incident analysis got faster

Incident analysis at NTT DATA now takes about 30 minutes because Codex and ChatGPT handle the routine part of the investigation: finding the cause of the failure, reading logs and code, and drafting a fix. Previously, the same work took significantly more time and manual effort from engineers.

Incident analysis is one of the most labor-intensive tasks at an IT services company. When a client's system goes down, engineers manually match symptoms against change history and logs to find the root cause. NTT DATA highlights the "30 minutes per incident" figure as the key result of the rollout: the faster the cause of a failure is found, the shorter the client's downtime.

How AI is being scaled securely

NTT DATA is betting on rolling out AI securely to 9000 employees at once rather than on isolated pilots. The choice of ChatGPT Enterprise comes down to data protection requirements: the corporate plan isolates work data and gives administrators control over employee access.

"NTT DATA

Group uses ChatGPT Enterprise and Codex to help 9000 employees automate their work, cut incident analysis to 30 minutes, and scale AI adoption securely," says OpenAI's corporate case study.

For a global integrator, the scale of the rollout matters more than any single feature. A tool used by thousands of engineers changes the processes themselves, not just the speed of individual tasks. The NTT DATA case adds to the customer stories section of OpenAI's site, where the company collects examples of corporate use of ChatGPT and Codex.

What this means

The NTT DATA case signals that large IT integrators are moving from AI experiments to mass adoption in core processes such as incident analysis. The "30 minutes per incident" metric shows that the value of enterprise AI is measured not by hype but by a concrete reduction in operational time across 9000 workstations.

ZK
Hamidun News
AI news without noise. Daily editorial selection from 50+ sources. A product by Zhemal Khamidun, Head of AI at Alpina Digital.
✦ Hands-On AI Engineering

Build & Ship Production AI Apps with Vibe Coding

Join Zhemal Khamidun's hands-on Vibe Coding Intensive at hamidun.com/vibecoding — master Claude Code, Cursor, and autonomous agentic workflows.

Explore Vibe Coding →Vibe Academy Platform
What do you think?
Loading comments…