Beyond ChatGPT: Unlocking Enterprise Value in the Age of Generative AI
Paul Baier is the CEO of GAI Insights, a company specializing in generative AI strategies for enterprises. With over 25 years of experience in B2B sales and venture-backed companies, Paul has become a thought leader in the AI space. He previously worked at FirstFuel, using traditional AI for building efficiency analysis. Paul is known for developing frameworks like “Own Your Own Intelligence” (OYOI) and WINS, which help businesses navigate the rapidly evolving landscape of generative AI. He also leads weekly Gen AI learning labs and is actively involved in initiatives to grow AI talent in Massachusetts.
0:00 – Introduction
2:15 – Paul’s AI journey
4:30 – OYOI concept
7:45 – WINS framework
11:20 – Gen AI learning labs
15:40 – AI Blueprint for MA
19:30 – Embracing AI change
22:45 – GAI Insights initiatives
24:15 – Closing remarks
Episode Links:
Paul Baier’s LinkedIn: https://www.linkedin.com/in/paulbaier
GAI Insights OYOI: https://gaiinsights.com/own-your-own-intelligence
AI Blueprint: https://ai-blueprint-ma.com/
GAI Insights News: https://gaiinsights.com/news-1-0
GAI Insights Learning Lab: https://gaiinsights.com/learning-lab
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Full Transcript:
Welcome back listeners. On this week’s recording, we’re bringing you Paul Baier, the CEO of GAI Insights. Paul, welcome to HumAIn.
Paul: Thank you, David. It’s great to be here.
David: You’ve had a fascinating career journey leading to your current role as CEO of GAI Insights. Can you share with our listeners how you first became interested in AI and what led you to focus on helping enterprises navigate the generative AI landscape?
Paul: Sure, David. My professional career has been 25 years on the vendor side with venture-backed companies doing various enterprise products. I’ve always been in B2B sales. I spent five years at a company called FirstFuel, which used traditional AI to measure and detect building efficiency. That experience really helped me understand traditional AI.
When ChatGPT hit in December two years ago, I couldn’t believe it. I called all the AI experts I worked with, and they were blown away. It was clear that it was a transformational tool. We started figuring out how to use it for business value, not just as a cheat tool for kids in school.
David: You and your firm have coined some terms. One of those is the concept “own your own intelligence” or OYOI. Can you share why it’s becoming increasingly important for businesses in the age of generative AI?
Paul: It’s a whole concept around risk management that’s been around for a while, but it’s becoming more acute. As we’re all aware, big tech is increasingly a big part of the global economy. The top six vendors are bigger than all but two of the largest global economies.
We’ve seen a world in the last 10-15 years where all the metadata for our location has been strip-mined from companies and citizens for profits. Companies are realizing there’s a risk here, particularly as we move from automating routine transactions to automating cognitively advanced processes like drug discovery, stock trading, and oil exploration. These are real competitive differentiators for companies.
David: There’s another framework you’ve talked about, Paul, like the Wins framework. This is one that you introduced in the Harvard Business Review. Can you tell us more about how this is helping companies understand their exposure to AI-driven changes in cognitive work?
Paul: Absolutely, David. We think “knowledge work” is too broad of a concept. Everyone’s a knowledge worker. My doctor who does physical surgeries and my lawyer are knowledge workers. So we’ve defined a set of knowledge work that’s really focused on a particular type of digital work.
We call it Wins: Words, Images, Numbers, and Sounds. If a large part of your work or cost base is manipulating words, images, numbers, or sounds, you’re particularly at risk for disruption or opportunity with Gen AI. We apply this at the industry level.
[NOTE: The speaker continues to explain the Wins framework and its implications for different industries. I’ve condensed this section for brevity while maintaining the key points.]
David: Now, putting on more of your education hat, Paul, you’ve been running weekly Gen AI learning labs. What are some of the most surprising or impactful insights that have come out of these sessions?
Paul: We’ve been doing that for about a year and a half, with groups of about 3,000. We get 50 to 120 each week. The major things that surprised me are the consistency of how many times people come back. It really is attracting enthusiasts who want to keep learning and validate their learning from others in a voice-to-voice or video-based way.
About half the group is technical, and half is business. There’s a lot of interest on both sides in being in the same room. The technical people continue to tell me they know AI or they’re data scientists, but they’re very interested in what the business people are seeing in other use cases. The business people say they’re not technologists, but they really want to understand what the tech folks are seeing in terms of capability.
This marriage of understanding the business need and technical capability collectively in a very fast-changing environment is something that’s been surprisingly exciting for learners and continually needed because it’s changing so much.
David: Can you tell us about the AI Blueprint for MA initiative and its goals for attracting and retaining AI talent in the state of Massachusetts?
Paul: Certainly. I’m in Boston, and this is a volunteer group whose goal is to do practical, tactical mini-projects to help retain, attract, and grow AI talent. “Grow” means either through the education system or cross-function training.
We’ve implemented several simple but important initiatives. For example, we now have a list of all the AI in-person events, which we didn’t have six months ago. We’re building a list of all the colleges’ email addresses so we can contact students about events. We’re also organizing an AI career fair.
We find teams of volunteers who commit to doing projects that are 60-90 days long. We have monthly Zoom meetings where everyone reports their progress. There are about 15 projects running in parallel right now.
This is separate from Governor Healey’s $100 million AI task force, which is working on larger-scale projects. Our volunteer group of 850 people is a side card to the government’s initiative.
David: Paul, as we wrap up, I’d like to give you the opportunity to speak directly to our listeners. What’s the most important thing you want them to take away from our conversation today? And what’s one actionable step they can take to engage further with your work or the ideas we’ve discussed?
Paul: Thank you, David. I think the most important mentality is to “embrace the pace and embrace the change.” Gen AI is the biggest career accelerant ever, full stop. If you can embrace that, it’s really exciting.
One way to do this is to start figuring out tools that are relatively easy to use to show you where the world’s going. One that we like a lot is a browser extension for Chrome called chathub.gg. This allows you to ask a question and get answers from multiple AI models at once. It’s a great way to see how we’re moving from a Google-dominated search world to a much more fluid world with multiple options for getting answers.
To get involved with us, people can go to gaiinsights.com. We have a free daily email newsletter, a learning lab every Monday night, and our annual conference, Genai World 2024, on October 7th and 8th in Boston, which focuses on enterprise case studies that are in production.
David: To all of our listeners, Paul Baier, the CEO of GAI Insights. Thanks so much for joining us on HumAIn.
Paul: Thank you.