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Operational Safety With AI: Chevron's Ellen Nielsen

> We use AI in many places, some areas where we use robots, for example, in tank inspection today. You can imagine that was very cumbersome having the human involved. Now we do this with robots.

Show: Me, Myself, and AI · Publisher: MIT Sloan Management Review + BCG · Host: Sam Ransbotham, Shervin Khodabandeh

Episode URL: https://sloanreview.mit.edu/audio/digital-twins-and-simulations-for-safety-chevrons-ellen-nielsen

Publish date: 2023-12-05
Duration: NAs
Default source credibility: HIGH — MIT SMR + BCG joint production. Named F500 CxOs on-record about production AI deployments. Academic/consulting co-brand keeps claims disciplined. Host has light BCG framing; guest metrics stay HIGH.

  • Chevron uses AI for tank inspection with robots, improving safety and efficiency.
  • Digital twins in refineries enable better planning and predictive maintenance.
  • Chevron’s AI initiatives include education programs to foster a data-driven culture.

Extracted quotes

# Credibility Speaker Org Timestamp Topic Quote
1 HIGH Ellen Nielsen (Chief Data Officer) Chevron 02:04 02-corporate-tools We use AI in many places, some areas where we use robots, for example, in tank inspection today. You can imagine that was very cumbersome having the human involved. Now we do this with robots. And we take basically the human beings out of these confined spaces. And that’s a combination of computer vision, you know, taking images, comparing the images, and take predictions on what’s the status of this tank and this equipment. Is it rusting? Does it need maintenance? Do we need to tackle it in a very predictive way so that’s operating in a much more reliable and safe way in the future?
2 HIGH Ellen Nielsen (Chief Data Officer) Chevron 03:39 02-corporate-tools We have a combination here of computer vision, of using citizen development, and then, of course, using these sensors in a machine learning, AI-based way to come to predictions and how they work.
3 HIGH Ellen Nielsen (Chief Data Officer) Chevron 11:06 07-adoption-challenges We have a digital scholarship program since a while. And actually, we do this with MIT, where we have cohorts going for a year. And they’re not coming out of one department. They’re really coming out of the whole company, going through a design engineering master in one year, which is really a tough thing to do. But they’re coming back and understanding the new technology, understanding the things, how we can use that differently.

Per-quote detail

1. Ellen Nielsen — Chevron (02:04)

We use AI in many places, some areas where we use robots, for example, in tank inspection today. You can imagine that was very cumbersome having the human involved. Now we do this with robots. And we take basically the human beings out of these confined spaces. And that’s a combination of computer vision, you know, taking images, comparing the images, and take predictions on what’s the status of this tank and this equipment. Is it rusting? Does it need maintenance? Do we need to tackle it in a very predictive way so that’s operating in a much more reliable and safe way in the future?

  • Credibility: HIGH — Named exec with specific production deployment detail.
  • Topic tag: 02-corporate-tools

2. Ellen Nielsen — Chevron (03:39)

We have a combination here of computer vision, of using citizen development, and then, of course, using these sensors in a machine learning, AI-based way to come to predictions and how they work.

  • Credibility: HIGH — Named exec with specific production deployment detail.
  • Topic tag: 02-corporate-tools

3. Ellen Nielsen — Chevron (11:06)

We have a digital scholarship program since a while. And actually, we do this with MIT, where we have cohorts going for a year. And they’re not coming out of one department. They’re really coming out of the whole company, going through a design engineering master in one year, which is really a tough thing to do. But they’re coming back and understanding the new technology, understanding the things, how we can use that differently.

  • Credibility: HIGH — Named exec with specific production deployment detail.
  • Topic tag: 07-adoption-challenges

Extracted 2026-04-15T00:07:01 via scripts/podcast_mine.py (MLX mlx-community/Qwen2.5-32B-Instruct-4bit).