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Cebu Pacific scales enterprise AI with OpenAI and Thinking Machines

Cebu Pacific is expanding its use of enterprise AI through a collaboration with Thinking Machines Data Science and OpenAI, focusing on integrating AI into real business workflows rather than limiting adoption to isolated pilot projects. The airline worked with Thinking Machines Data Science, an OpenAI Advanced and Services Partner in the Asia Pacific region, to […]

Cebu Pacific is expanding its use of enterprise AI through a collaboration with Thinking Machines Data Science and OpenAI, focusing on integrating AI into real business workflows rather than limiting adoption to isolated pilot projects.

The airline worked with Thinking Machines Data Science, an OpenAI Advanced and Services Partner in the Asia Pacific region, to identify high-value workflows, test AI solutions in actual operating environments, and establish governance and evaluation processes based on the risks involved.

The rollout of ChatGPT Enterprise has already produced measurable improvements across several departments. Legal contract review time dropped from an average of 2.5 hours to about 1.2 hours, while project intake and triage turnaround decreased from five days to approximately one day, with an estimated 80% reduction in manual review effort.

Engineering teams also saw reference-search times fall from 10–15 minutes to less than 10 seconds. Following the program, 86% of surveyed users said AI supported more than one-third of their daily work.

“At Cebu Pacific, we see AI as a practical way to make every customer’s journey simpler and our operations more reliable,” the airline said, noting that AI is helping employees solve problems faster, make decisions, and focus on higher-value work.

The airline is now preparing for the next phase of its AI strategy, including broader ChatGPT-enabled workflows, OpenAI API-based solutions, stronger change-management support, and potential agentic AI applications connected to enterprise data and systems.

The initiative highlights a growing enterprise AI approach in which organizations move from experimentation toward measurable workflow improvements, while establishing governance and employee adoption processes to support responsible scaling.

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