Jon Krohn: 00:02
This is 5-Minute Friday on why CEOs care about AI more than other technologies.
All right. Welcome back to the SuperDataScience Podcast. We’ve got another Five-Minute Friday with Ben Taylor. Last week, Ben talked about how to sell a multimillion dollar AI contract and he talked a lot in that about selling to the C-suite. And so, my follow up question for you this week, Ben, is why do CEOs care about AI and not so much about other kinds of technologies?
Ben Taylor: 00:45
This is a really interesting question because they don’t care about a lot of other things. They don’t care about the hardware. They don’t care about the data layer or the database, but they do care about AI. And I think the reason they care is, they are getting some pressure from their boards. Their boards are asking, what’s your AI strategy?
And then the good executives understand that this can accelerate growth. It can transform a company. A business is made up of processes. Processes involve people in data. And so, businesses are really ripe for massive disruption with AI. And that can become very competitive for them in their landscape.
So I’m surprised how many executives really want this conversation. They want to understand how is AI going to impact their business. And a lot of people in the AI space struggle to communicate that and they overcomplicate it. And they tell them about how, like literally the how in the data science, which executives don’t care. They care about the what. What are you going to do and how am I going to measure it? And an AOC is not a way to measure it from a business perspective.
Jon Krohn: 01:56
Right. Yeah, that’s something I’ve been reading a lot lately. Various people on LinkedIn just posting to their followers about how today a typical data scientist will be presenting technical information like AUCs and explaining the vast majority of the way that they spend their time. And I’m guilty of this historically and hopefully I’ll be less guilty of it in the future. But speaking to executives, I will try to get them excited about how cool this approach is. But as you say, they don’t really care. They don’t-
Ben Taylor: 02:26
So cool has a role. And cool has a role because you’re convincing them of Art of the Possible, but you quickly have to get… If you can convince them of Art of the Possible, that will reduce the need for case studies, because otherwise they demand case studies for their business. I’m a big fan of Art of the Possible, but then you need to get to the rational close. But I’ve made so many mistakes here. I’ve given presentations to CEOs where I’ve missed the mark. And even my own CEO in the past to other companies, I’ve shown them iterations.
I tried these three things. They didn’t work. It’s like you’re trying to get partial credit, “I’m working so hard for you.” Any of these three things… They don’t care that… You’re showing them that you did three things that didn’t work to get to the fourth thing that worked. It reduces their confidence. That is part of AI, like these iterations are key, but you don’t need to share that with them.
Jon Krohn: 03:20
Nice. That is a great explanation and very exciting to think that the technology that lots of listeners are working on, that we’re working on, is the thing that business is most interested in today.
Ben Taylor: 03:34
And there was also a gap of storytelling. I think we’ve come a long way with better storytelling for the business. So you think of your classical feature, importance plots or [inaudible 00:03:43] predictions, prediction insights. But we’re only getting better, which is great, because we don’t need to necessarily convince the data scientist. We have to convince the domain experts that this is working, doing what they like, and they can critique it, which is great, because they have a lot more expertise than we do about that process.
Jon Krohn: 04:03
Yeah. And then something that I often get excited about is how we’re really at the beginning of this. Like the amount of data that we’re storing today is negligible relative to the amount of data we’ll be storing in five years and 10 years that we’ll be capturing on different kinds of sensors in the workplace. And otherwise, that allows us to be making substantial process improvements, efficiency improvements in organizations.
Ben Taylor: 04:29
Yeah, I completely agree. And I think another thing too that is really exciting that is we’re pushing more for is actionable insight. So any AI system that interacts with you or the business, if it’s getting your attention, think of push notifications on your phone needs to be actionable. The rain camera annoying you right now is not actionable. It’s someone’s walking down the hall or there’s something that is not… So as these systems get smarter, more actionable, it’ll be a great way to live.
Jon Krohn: 04:58
Sweet. All right. That’s it for today’s episode. We’ll be back with Ben Taylor yet again next week to ask him what we should expect from AI platform companies a decade from now. In the meantime, keep on rocking it out there folks and I’m looking forward to enjoying another round of the SuperDataScience Podcast with you, very soon.
