Australian Payments Plus moves faster with ChatGPT and Codex

· Source: OpenAI News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, medium

Summary

Australian Payments Plus (AP+), a major operator of payments and identity infrastructure in Australia, has implemented ChatGPT Enterprise and Codex to enhance operational efficiency and work quality. The enterprise-sized financial technology firm reports that 77% of surveyed employees save hours weekly using ChatGPT, while 80% report improved creativity or work quality. Specifically, Codex reduces complex reconciliation investigation times from 4 hours to 30 minutes and enables working simulations to be built in 1 day, down from days or weeks. AP+ leverages ChatGPT Enterprise to summarize complex documents, draft member communications, and structure problems, such as navigating eftpos specifications. Codex assists technical teams in investigating intricate payment issues and is being explored for security applications like threat modeling. This adoption supports faster product development and responsible AI scaling through secure tools and integrated governance.

Key takeaway

For AI Product Managers or Directors in regulated industries evaluating AI integration, your focus should be on enabling secure, governed experimentation. Implement tools like ChatGPT Enterprise and Codex with clear boundaries and integrated governance to accelerate complex investigations and product simulations. This approach allows your teams to reduce manual effort significantly, improve work quality, and validate ideas faster, ultimately reducing innovation risk while maintaining accountability.

Key insights

AI tools like ChatGPT and Codex accelerate complex knowledge work and technical investigations within regulated financial environments, improving efficiency and quality.

Principles

In practice

Topics

Best for: Executive, CTO, VP of Engineering/Data, AI Engineer, AI Product Manager, Director of AI/ML

Related on AIssential

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by OpenAI News.