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ABN AMRO Data Expo 2024 #2

Marketing OGZ
September 17, 2024
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ABN AMRO Data Expo 2024 #2

Marketing OGZ

September 17, 2024
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Transcript

  1. ABN AMRO @ Big Data Expo How to rapidly innovate

    with GenAI Wouter Gielen – GenAI product manager
  2. GenAI radically transformed how we deliver value (what, how, who,

    how much) Data science - insight - models (APIs) Product management - software AI products No direct users Output is number/test Data science teams Smaller teams End-users Front/back end IT Infra Architects Design Large teams
  3. We went from a small pilot to a full scale

    AI product team in < 18 months Fully rolled out two GenAI products < 9 months Manage a mature portfolio of 4 different AI products supporting 13k users Grew team from 5 FTE to 25 FTE on GenAI products Set up a dedicated change management program Reached over 7,500 people in internal talks on GenAI Reviewed over 500 use case submissions Won the Accenture Innovation Award
  4. We rolled out call summarization to all our contact officers

    From pilot to full roll-out in < 9 months 1000 users >10k summaries a week 8 / 10 user satisfaction 17-09-2024 | 6
  5. Smart knowledge base to search answers to customer questions 17-09-2024

    | 7 Find answer to question in a few clicks Automation at scale
  6. Investigate why customers call and how we can improve 17-09-2024

    | 8 Understand themes Deep dive For all teams
  7. Released ABN AMRO GPT for daily use of GenAI 17-09-2024

    | 9 10.000 users 60% weekly active users NPS > 60
  8. Work on big problems 17-09-2024 | 11 Work on big

    problems It’s a number game. Crowd source idea generation Stay connected to industry
  9. Work on big problems 17-09-2024 | 12 Work on big

    problems Problems we like: - Mandatory - Frequent - Growing - Costly - Are in the top 3 list of our main stakeholder - End users are really annoyed about
  10. Trust the iterative learning proces Master the lost art of

    building minimum viable products Write the specs Timebox the specs Cut the specs  What do we want to deliver as MVP  Only build stuff that contribute to the learning you seek  How fast can we deliver this?  Which specs can we remove  Any shortcuts we can take?  Don’t touch it anymore Write the specs t the specs
  11. Trust the iterative learning proces Do things that don’t scale

    If you can find someone with a problem that needs solving and you can solve it manually, go ahead and do that for as long as you can, and then gradually automate the bottlenecks. It would be a little frightening to be solving users' problems in a way that wasn't yet automatic, but less frightening than the far more common case of having something automatic that doesn't yet solve anyone's problems.
  12. Q&A