NTT DATA Group cuts incident analysis to 30 minutes with Codex
Summary
NTT DATA Group, a global IT services company, has expanded its use of OpenAI's Codex to approximately 9,000 employees across technical and nontechnical roles by July 2026, building on a companywide adoption of ChatGPT Enterprise initiated in May 2025. This expansion follows an early success where Codex completed a complex incident analysis in 30 minutes, a task that previously required five engineers three days, representing a -99.3% time reduction. The company established an internal OpenAI Center of Excellence (CoE) to support AI integration, leading to over 96% employee satisfaction and 95% reported productivity gains with ChatGPT Enterprise. Codex is now being used by nontechnical employees for tasks like building lightweight tools, organizing files, analyzing Excel data, summarizing documents, and scripting repetitive processes, such as extracting transportation expenses. This initiative is supported by robust security guidelines developed by the CoE, ensuring safe and confident use across the organization.
Key takeaway
For AI/ML Directors or Consultants aiming to scale AI beyond engineering, prioritize establishing a robust internal Center of Excellence and comprehensive security guidelines. Your strategy should include broad deployment of foundational AI tools like ChatGPT Enterprise to build employee familiarity, then introduce agentic AI like Codex for automating defined tasks. This approach enables non-technical staff to perform specialized work, reducing reliance on engineers and accelerating operational efficiency across your organization.
Key insights
Agentic AI like Codex can dramatically cut complex task times and empower non-technical employees.
Principles
- Broad AI adoption builds foundational user habits.
- Secure, governed environments are crucial for enterprise AI.
- Treat internal organization as "Client Zero" for AI testing.
Method
NTT DATA Group's CoE established security guidelines, managed license distribution, and developed use cases to scale AI adoption across technical and nontechnical roles.
In practice
- Automate incident analysis to reduce resolution time significantly.
- Use AI to extract data from documents into structured forms.
- Enable non-engineers to create analytical reports directly from raw data.
Topics
- Codex
- ChatGPT Enterprise
- AI Adoption
- Incident Analysis Automation
- Enterprise AI Governance
- Agentic AI
Best for: Executive, CTO, VP of Engineering/Data, Director of AI/ML, Consultant, AI Engineer
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Editorial summary, takeaway, and curation by AIssential. Original article published by OpenAI News.