Report on GenAI and Adoption Rate – Techstrong AI Podcast EP38

Hello and welcome to the Techstrong AI Podcast. I'm Amanda Ani, and with me today is Cindy Hausen. She is the Chief Data Strategy Officer for ThoughtSpot.

How are you doing? Great. Thanks for having me on the show, Amanda.

Happy to have you here. So can you share a little bit about ThoughtSpot and what services do you provide? Sure.

So ThoughtSpot is the AI powered analytics platform for all your cloud data. We pioneered and patented this category that Gartner would call augmented analytics that now really the rest of the world is, is trying to do it, its natural language processing and AI generated insights on business data. Wonderful.

And so ThoughtSpot recently with MIT, I believe conducted a survey and can you share a little bit about this report? Who are you, uh, what were you analyzing and who did you survey? Yeah, I'm really excited about this survey because there's so much noise hype we might say with generative ai.

But what we wanted to do was focus on generative AI on the data and analytics use case. So this is not generative AI for social media posts, for example, or summarizing emails. It's really on data and analytics.

So we partnered with MIT, they surveyed over a thousand executives globally across different sectors, financial services, healthcare, insurance, CPG, and the, the findings were a little surprising to me. The one, um, that most surprised me is that already two thirds of organizations are putting generative AI to work against their data and analytics platforms. Oh wow.

So what does that mean to business leaders as they look at AI and how to implement it? So the biggest thing that it means is that we really as an industry been trying to democratize data and analytics at the point of impact for business people. And now generative AI makes that even easier, more possible.

So people don't have to learn hard to use tools or learn how to program in SQL or Python. That is part of it for the right persona. But for business people it's about being able to ask questions in natural language and then get an answer back that is further explained in natural language that really makes data less scary, more approachable, um, for everyone.

And I believe the report mentioned about the skillset of employees. Can you share a little bit about that and where are we as far as skillset when it comes to generative ai? Yeah, so skillset is something that every organization really needs to work on.

So now that we have made the technology easier, one thing that technology cannot solve is AI literacy and data literacy. People need to understand the difference, for example, in sales to customers versus shipped to customers, sold to customer and shipped to customer can have a very different meaning, um, and different languages. So focusing on the business definitions, that's what I would call data literacy.

And then the critical thinking, does this number look right? Does it pass the smell test? Is the data complete?

Might I have gaps in my data? These critical thinking skills are important for every organization to embrace. And did that survey say anything about hesitation to adopt this new technology?

And what is the mindset there? Yeah, so the biggest hesitation, this is a new technology. The landscape is changing really fast.

Hopefully all of your listeners are aware of hallucinations and they know the mitigation strategies, things like rag architecture, data completeness, and that is the biggest thing. So this is also where we see differences in the platforms. The degree of trust accuracy and transparency varies greatly, but this is really the biggest hesitation.

So what I'm always happy about is when a customer will tell me they have set up a responsible AI council and they're leaning in, but they're leaning in intentionally. What I never like is when people stick their head in the sand and say, we'll just wait until this matures because that is really at their peril. Yes, it is.

It seems everybody is trying to harness the power of AI and they'll be left behind if they don't, when it could have been a a useful tool. Yes. And the other question I have is, um, when it comes to, uh, return on investment, what tips do you have to businesses as far as seeing where they're getting their return on investment?

Yeah, and this is perhaps I would say also one of the most exciting parts of the findings from the report is that, so MIT divided this between the early adopters and those that are slow followers and those that are still taking a wait and see approach. Well, the early adopters, 12% said that they expect a 300% return on investment from making generative AI work with their data and analytics. That's huge.

And just about half estimate a at least a hundred percent or greater ROI, and that's a combination of productivity, data analyst, business user productivity, but also new revenues and improve customer loyalty. So that's the good news. How do you get there?

First off, take a baseline. What are your metrics today? And I often think of this in terms of leading indicators and lagging indicators.

So if I were to take a supply chain example, a leading indicator might be how many users do you have that can ask their own questions? How long does it take? If it's taking you three months to build a dashboard and you can get it down to seconds, um, or even days.

That's a huge productivity savings of doing more with less. Your lagging indicator will be those supply chain metrics. So it might be for example, on time and in full or um, aging up accounts, receivables, stock outs, things like this.

And so as you democratize data insights at the point of impact, then those lagging indicators will eventually follow. And you definitely want to be measuring both. All right.

Well if there was one key takeaway you could leave our audience with today, what would that be? The generative AI is just a technology and enabling technology, a powerful technology. But you do need the people and the culture to embrace this.

This is a generational lifetime shift in the way of working. And I don't want people to miss out. I want them to benefit from it.

Alright, well thank you so much for coming on our show today and talking about this report. Thank you, Amanda. Always a pleasure.

Yes, and thank you to our audience as well. Stay tuned. There's more.