Quick Overview
This short video is a customer spotlight featuring Hiroaki Sato, Principal Technical Lead at NTT Data's OpenAI Center of Excellence. It presents real-world implementation examples of OpenAI Codex across technical and business departments at NTT Data.
Key Points
- 1.NTT Data expanded its internal Codex user base to more than 10,000 active users within a few months of introduction.
- 2.Codex is used at NTT Data to automate high-complexity incident analysis and performance diagnostics.
- 3.Technical diagnostics and report generation tasks were reduced from two days of specialist work to thirty minutes.
- 4.Non-technical teams, including sales personnel, use Codex to automate routine tasks such as customer list maintenance.
Summary
Hiroaki Sato, Principal Technical Lead at the OpenAI Center of Excellence at NTT Data, details his organization's adoption of OpenAI Codex and the wider product portfolio. Following its rollout, the internal Codex user base expanded rapidly to exceed 10,000 active users within a few months, establishing itself as the company's largest internal community.
Addressing what the tool unlocks for engineering, Sato explains that Codex automates high-complexity incident analysis as well as system performance reviews. Screen demonstrations show analysis of Windows kernel dump files in the Codex IDE and automated report generation in HTML. Technical analysis and report creation that previously required two days of work by a technical specialist are completed automatically by Codex in thirty minutes.
The deployment also extends past technical teams to commercial functions. Sato notes that sales teams have begun using Codex to automate operational assignments, such as customer list maintenance. This cross-departmental adoption has introduced new workflow changes across NTT Data that the organization had not experienced prior to implementing Codex.
Internal Community Growth and Adoption
Hiroaki Sato leads adoption efforts at NTT Data's OpenAI Center of Excellence. Following its introduction, internal usage of Codex scaled rapidly, reaching over 10,000 active users in a few months to become the organization's largest internal community.
Automating Incident and Performance Analysis
NTT Data applies Codex to automate complex technical investigations, including performance diagnostics and kernel dump evaluations. Tasks and reporting that previously required two days of specialist labor are completed automatically in thirty minutes.
Cross-Functional Workflow Transformation
Adoption of Codex has broadened beyond engineering into operational teams. Sales teams use Codex to automate routine administrative tasks like customer list maintenance, creating new workflow patterns across the company.
The Bottom Line
The case study demonstrates how NTT Data deployed OpenAI Codex to shorten complex technical analysis workflows from days to minutes while scaling usage across more than 10,000 employees. It establishes that adoption expanded beyond core developers into non-technical teams like sales for routine data maintenance. The presentation focuses on high-level operational outcomes and leaves detailed infrastructure configuration and long-term cost impacts unaddressed.
FAQ
What is OpenAI Codex and how is it used at NTT Data?
Codex is an AI tool deployed at NTT Data to automate technical tasks such as performance analysis and incident diagnostics, as well as business workflows like customer list maintenance.
How much time does Codex save during technical incident and performance analysis at NTT Data?
Analysis and report creation that previously required two days from a technical specialist are completed automatically by Codex in thirty minutes.
How large did the internal Codex user community become at NTT Data after its launch?
The platform grew to more than 10,000 active users within a few months of its introduction, becoming the company's largest internal community.
How are non-technical teams like sales using OpenAI Codex at NTT Data?
Sales teams use Codex to automate routine administrative workflows, including customer list maintenance.
Worth watching for
Enterprise technology leaders, systems engineers, and operations managers looking to understand how organizations deploy AI tools across technical and non-technical teams.
- openai-codex
- ntt-data
- incident-analysis
- workflow-automation
- enterprise-ai