ABOUT THIS EPISODE
Fun fact: Gauthier Vasseur is the first returning guest I've ever had on Asking Good Questions. We finished Season 1 with 38 subscribers (not a joke), the channel is over half a million now, and I told him on camera he might've had something to do with that. (My plan to pay him back is a bunch of Puerto Rican coffee, and he said "there you go," so I think we have a deal.) He runs the Fisher Center for Business Analytics at UC Berkeley's Haas School of Business, and his company, Data Wise Academy, gets everybody from the back office up to the executives doing real work with their own data in a matter of days.
I asked what his students are asking him, and it's the same thing whatever country or company they're from: is my job going away, and what should I learn today? He says everybody will be safe "upon one condition": can you pivot and evolve really fast? The old disruptions gave you a couple of years to adjust. He figures now it's more like 2 to 6 months. The morning we recorded, he'd talked to a very large energy company his team trained, and they realized a lot of the work was going away (he said flat out they could've fired people). Then they came back and told him they'd found a whole pile of work (prediction, clustering their own data) they'd never had time to touch.
When I asked what back-office people actually spend all day doing, he said "death by PowerPoint, Excel hell, and a lot of tedious manual data manipulation." His fix for the data part is natural language coding (he says hours down to seconds), and for the decks it's Markdown plus CSS plus an LLM. He asked a group of banking executives from Uzbekistan how their death by PowerPoint was going, and they said "Oh my gosh, death by PowerPoint is killing us." A two-minute demo had them jumping on their chairs.
Gauthier and I both preached "you must have clean data" for basically forever (in my case, through 25 years running interRel), so I asked him, and I can't believe I said this out loud, whether we're entering a post-clean data world. He starts with FAIR data (findable, accessible, interoperable, reusable). After that, generative AI builds a table that matches up your messy master data (and a human audits it), and plain old joins do the cleaning from there. Hand the whole mess to gen AI every day and you're burning tokens and getting a different answer each time. As he puts it, "it can do magic until it doesn't," and that's fine for a broad marketing campaign and not so fine for precise customer analytics.
He also told me about his time as a financial controller, when his team took closing the books from 2 months down to 3 days with a lot of SQL (no Python back then), and nobody lost their job. He's got plenty for IT, too, like spending $500 to $1,000 more per laptop so the people you trained can actually run their Python. (I told him I don't think anybody in IT goes "You know what I really love about life? Watching that database to see if it crashes.")
Gauthier is giving his keynote, "Beyond AI: Building AI-Capable Organizations," at the Caribbean AI Summit on Saturday, October 10 in San Juan, and then he's moderating the business AI panel. (I've seen him open some of his sessions with literal magic, so I'd get there early just in case.) If you catch him, buy him an espresso. He says he's a very cheap date.
I'm Edward Roske, and this is Asking Good Questions. New conversations with the people figuring out the human side of AI. If one of these questions stuck with you, subscribe and send it to someone who'd take the other side.
LINKS
Caribbean AI Summit (Oct 9-10, San Juan): https://CaribbeanSummit.AI
Data Wise Academy: https://datawiseacademy.com
Gauthier on LinkedIn: https://www.linkedin.com/in/gauthiervasseur/
His first AGQ episode (S2:E9, 2025): https://www.buzzsprout.com/2430929/episodes/17706388
RESEARCH & RESOURCES MENTIONED
"Navigating the Jagged Technological Frontier," Fabrizio Dell'Acqua et al., Harvard Business School (2023)
OpenAI Academy: https://academy.openai.com
Anthropic Academy: https://anthropic.skilljar.com
Good Luck, Have Fun, Don't Die, directed by Gore Verbinski (2026)
I asked what his students are asking him, and it's the same thing whatever country or company they're from: is my job going away, and what should I learn today? He says everybody will be safe "upon one condition": can you pivot and evolve really fast? The old disruptions gave you a couple of years to adjust. He figures now it's more like 2 to 6 months. The morning we recorded, he'd talked to a very large energy company his team trained, and they realized a lot of the work was going away (he said flat out they could've fired people). Then they came back and told him they'd found a whole pile of work (prediction, clustering their own data) they'd never had time to touch.
When I asked what back-office people actually spend all day doing, he said "death by PowerPoint, Excel hell, and a lot of tedious manual data manipulation." His fix for the data part is natural language coding (he says hours down to seconds), and for the decks it's Markdown plus CSS plus an LLM. He asked a group of banking executives from Uzbekistan how their death by PowerPoint was going, and they said "Oh my gosh, death by PowerPoint is killing us." A two-minute demo had them jumping on their chairs.
Gauthier and I both preached "you must have clean data" for basically forever (in my case, through 25 years running interRel), so I asked him, and I can't believe I said this out loud, whether we're entering a post-clean data world. He starts with FAIR data (findable, accessible, interoperable, reusable). After that, generative AI builds a table that matches up your messy master data (and a human audits it), and plain old joins do the cleaning from there. Hand the whole mess to gen AI every day and you're burning tokens and getting a different answer each time. As he puts it, "it can do magic until it doesn't," and that's fine for a broad marketing campaign and not so fine for precise customer analytics.
He also told me about his time as a financial controller, when his team took closing the books from 2 months down to 3 days with a lot of SQL (no Python back then), and nobody lost their job. He's got plenty for IT, too, like spending $500 to $1,000 more per laptop so the people you trained can actually run their Python. (I told him I don't think anybody in IT goes "You know what I really love about life? Watching that database to see if it crashes.")
Gauthier is giving his keynote, "Beyond AI: Building AI-Capable Organizations," at the Caribbean AI Summit on Saturday, October 10 in San Juan, and then he's moderating the business AI panel. (I've seen him open some of his sessions with literal magic, so I'd get there early just in case.) If you catch him, buy him an espresso. He says he's a very cheap date.
I'm Edward Roske, and this is Asking Good Questions. New conversations with the people figuring out the human side of AI. If one of these questions stuck with you, subscribe and send it to someone who'd take the other side.
LINKS
Caribbean AI Summit (Oct 9-10, San Juan): https://CaribbeanSummit.AI
Data Wise Academy: https://datawiseacademy.com
Gauthier on LinkedIn: https://www.linkedin.com/in/gauthiervasseur/
His first AGQ episode (S2:E9, 2025): https://www.buzzsprout.com/2430929/episodes/17706388
RESEARCH & RESOURCES MENTIONED
"Navigating the Jagged Technological Frontier," Fabrizio Dell'Acqua et al., Harvard Business School (2023)
OpenAI Academy: https://academy.openai.com
Anthropic Academy: https://anthropic.skilljar.com
Good Luck, Have Fun, Don't Die, directed by Gore Verbinski (2026)
This episode of Asking Good Questions is brought to you by Caprus.Ai.
Check how we empower the office of the CFO to harness the transformative potential of artificial intelligence (AI) and revolutionize their operations.
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