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Paul Daugherty spent 38 years at Accenture before retiring.
“I was there for 38 years until I retired last year, and it was an amazing vantage point from which to see the transformation”
Topic
Paul Daugherty
14 facts from 1 episode, in date order. These are what speakers said on the shows, each linked to the moment it was said. They aren't independently verified.
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Paul Daugherty says the first production system he wrote used punch cards on a mainframe.
“the first production system I wrote was in was in punch cards on a mainframe.”
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Daugherty says one organization he works with saw a 30% productivity increase and a 60% increase in net promoter score after adding generative AI to customer service.
“One organization I'm working with that had, uh, 30% increase in productivity and 60% increase in net promoter score and satisfaction”
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Daugherty says that even if AI were frozen today, large language models would drive five to ten years of business adoption.
“If we just froze AI right now, no more innovation, no more products, freeze it where it is right now with large language models”
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Daugherty says Accenture research now puts the share of work hours that generative AI can affect above 50%, up from an earlier 40% estimate.
“We've done some additional research, and, you know, you can you can peg it above above 50% now”
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Daugherty cites research that about 15% of organizations have made significant progress scaling AI.
“about 15% of organizations have made significant, you know, 1, 5 have made significant pro- some significant progress on scaling AI somewhere in the organization.”
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Daugherty says the average organization spends 50% to two-thirds of its technology budget keeping legacy systems running.
“the average organization still spends, you know, 50% to 2/3 of their budget keeping lights on on legacy rather than new capability.”
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Daugherty says robotic process automation was fragile and struggled to adapt to changes in underlying systems.
“RPA was we kinda had this problem of being a little fragile.”
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Daugherty predicts consultants will need to bring a foundation model pre-trained on client data and remodel the business live in the first meeting.
“you need to walk in with a foundation model with pre-trained on the client's data and in the CFO's office, be remodeling their business dynamically in the first meeting.”
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Daugherty predicts a physical AI and robotics moment bigger than the ChatGPT moment within roughly two to five years.
“We're gonna have a a a moment probably bigger than the ChatGPT moment around physical AI and robotics and what they can do.”
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Daugherty estimates that fewer than 20% of organizations practice responsible AI rigorously.
“Less than 20%, and that's probably a generous number, of organizations are really doing responsible AI the way I would characterize the need for it.”
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Daugherty says responsible AI requires principles, processes built into engineering practice, and tools and measurement of each use case's risk.
“you need 3 things. You need principles. Everybody's got that.”
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Daugherty says he advocated for responsible AI for about eight years, initially with almost no one listening.
“it was preaching totally into the wilderness with 0% listening for a long time.”
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Daugherty names crypto-based tokenization of assets, data and manufacturing as an underappreciated technology to watch.
“crypto as a general-purpose technology for tokenization, not just of financial assets, but of, uh, you know, other things, data, manufacturing”
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