How BBVA is scaling AI from pilot to practice across the org
In Peru, one internally built assistant is now used by more than 3,000 employees, reducing query handling time from around 7.5 minutes to about 1 minute—an ~80% reduction.
- Agent or tool
- ChatGPT
- Topic
- DevOps & Infra
- Reported on
- Case study (OpenAI)
- Added
- 2026-11-11
Why it matters
Keeping servers and pipelines healthy is constant, detail-heavy work. Agents that can read logs and run routine fixes are a big help, as long as a person keeps an eye on what changes. It is one of 130 sightings filed under DevOps & Infra on Agent Sightings (number 51 by interest), and one of 145 involving ChatGPT.
How you could try it
Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into ChatGPT or any similar agent and adjust the details to your situation.
I want an agent to investigate and propose a fix, and to wait for approval before changing production. The tool in the source case was ChatGPT.
Tip: Try it first on a staging system or with read-only credentials, and require approval for anything that changes production.
Source
Read the original first-hand account on Case study (OpenAI): https://openai.com/index/bbva-2025. Our summary is a paraphrase; details are in the source.
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