Episode Transcript
[00:00:00] Caroline Winnett: We get 3,800 applications for 20 spots. We're more and more looking at using AI to help us better understand that deal flow.
[00:00:10] Braydan Young: So a new metric we follow is like revenue per employee. Do we need to hire someone to come and do that? Or can we find a tool that can do that for us?
[00:00:18] Clint Lotz: You can fine tune to a granular level on what it is that's important to your outcome versus what's just noise.
[00:00:26] Elizabeth Gearhart: I put marketing in from day day one because that's what you have to do these days.
[00:00:30] Richard Gearhart: It came up with about 70% of the changes, but it saved me a lot of time.
[00:00:39] This is AI in Business with hosts Elizabeth Gearhart, podcast consultant, marketing expert, and PhD researcher using AI every day. And Richard Gearhart, entrepreneur, seasoned business owner and intellectual property attorney specializing in innovation.
Here's how real companies are using AI right now.
[00:01:00] Richard Gearhart: Now it's time for AI in Business.
[00:01:03] Elizabeth Gearhart: Yes, AI in Business.
So the purpose of this segment is to spread the word and give people ideas about how you can use AI in your business.
I am going to start with you, Caroline. I know you have a million different use cases, but I just want one, maybe your favorite one. What is one way you're using AI in your business?
[00:01:23] But, but it, we're talking about the business of Berkeley Skydeck, which is of course a university program, but we're using it for diligence for our companies, as all good investors are. So we get a, we get about 3,800 applications for 20 spots.
So we're, we're more and more looking at using AI to help us better understand that deal flow, not to pick the companies that, that's what we do as humans during interviews, but to help us understand that and to help us, once they are selected for an interview, to do some more research on that. So we've got a fantastic team at the Berkeley Skydeck Fund. They've got a fantastic team of Berkeley MBAs. These are very sharp people, I must say, who are helping us with, with this initiative.
Ask me in six months and we'll probably have more and even different insights and comments about it. But so I'd say we're really just getting started, but at the end of the day to pick a startup to invest in, it's humans talking to humans. You cannot substitute that.
[00:02:36] I just want to point out to entrepreneurs here, people interested in getting seen.
AI looks at everything about you on the Internet, every podcast, everything. And if somebody puts the transcript of the podcast on there, it reads the transcript. It looks at your LinkedIn, it looks at your face, it looks everywhere. So the more you can have a consistent message and talk about what you're doing, the better chances you are of getting a good profile on the AI. And I'm going to talk about that a little bit more later anyway. Oh, thank you very much. That was really a, a new way I hadn't heard before of using it.
So now I'm going to go to Braden Young. Braden, what is one way you're using AI for your business?
[00:03:20] Yeah, this is my third startup because I like the pain of 0 to 10. And the. So, so the, the very first two, we, we scale. One we scale up to help folks. The other one, we scale up to 700 people and the employees. And this one we. So a new metric we follow is like revenue per employee, which, which we did not track the first time around. And the reason we track that is because can we do we need to make this higher? Is it necessary? And so if we can find an AI that can do or an agent that can do that person's job that we know we need to hire, for example, entry level sales, like do we need to hire someone to come and do that or can we find a tool that can do that for us?
And if we can't, then okay, then like, then you know, we'll go and hire somebody. So that's a mantra we use internally a lot to make sure we can, we're hiring when it's necessary. And then like will this impact the metric of our revenue per employee? Yes, if you go out and hire.
[00:04:15] For sure, that's a great way to use it.
[00:04:17] So quick question, how do you come up with that number revenue per employee?
[00:04:21] I mean, it's one of those where like, it's what your ARR is and like divided by the amount of employees that you have. And like it was one that we didn't typically track in the past and it's our board asks for it now. I think it becomes one of those where like AI companies, like very pure AI companies, they love that metric. Like there's a lot of LinkedIn comments like we're a team of five and we do a hundred million in revenue. And so there's all those, you know, talking heads on LinkedIn, but it's one that we also report on.
[00:04:49] Clint Lotz, Track Star AI I know you're using AI, but what is one way that you're using AI in your own company?
[00:04:58] Within our own company, probably the most beneficial use case for us is data crunching, right? It's data Analysis. As we've grown and we've really pivoted to large enterprise clients, we have even larger data sets that we ingest on a daily basis.
And when our models are out there running, we crunch all the data that we receive. Not only just how accurate is it, how it's performing, but we're also ingesting all the signals from the consumers and how they're being impacted by this type of solution. In addition to, you know, what KPIs we're driving for our clients, our lenders. Right. And we really use it to build that kind of holistic story that and I think the AI is really good at that. It's summarizing, you know, massive data sets is it can within minutes tell me exactly what I'm doing for my client and how I'm affecting all their consumers in general. Right. And that is really what helps us tell the story for prospects and for investors as well too.
[00:06:05] That's great.
So what is your level of confidence then in this output?
[00:06:10] Well, let me first start off by saying the AI is only as good as the data it's trained on and it really depends on where you start.
And the beautiful thing about AI and the adoption over the last, say four or five years is it's really matured and it's created this ability for people to build their own type of small LLMs or on prem LLMs you can get very specific, you can fine tune to a granular level on what it is that's important to your outcome versus what's just noise. Signal versus noise is what they call it.
With that type of ability to really kind of comb through on a macular level, you can actually understand what's going on and predict what's going to happen in the future based on those trends. And so when you have that type of understanding and deep rooted elements of the AI under your control, that's what brings us the most confidence.
[00:07:09] Yeah, I've heard a lot of companies now are developing their own LLMs for in house use, feeding it their own data, having it be searchable, having new employees come in and the first thing they have to do is look at some of the data that's in there and learn the company.
[00:07:25] Yeah, sounds good.
[00:07:27] What about you, Richard Gearhart?
[00:07:28] Well.
[00:07:31] My most recent use of AI was to review a vendor contract, not a client contract.
I wouldn't put that into the AI data set because it's confidential information, but vendor contract and provide a redline version of it. And I would say that it came up with about 70% of the changes I felt were good ones. I had to refine it, but it saved me a lot of time.
It picked out a few things that I'm not sure I would have picked out without it.
And so it was a great aid and a great time saver. So.
[00:08:17] Well, I'm I'm helping people start podcasts, starting my own podcast too, and I view podcasts as a digital marketing tool. They're. You know, it's really hard to be the next like star, right? But if you use it to direct people to your business, it can be very powerful. And there's a lot of reasons, I'm not going to get into them.
But I put marketing in from day one because that's what you have to do these days, especially if you're using a podcast for business.
So I've been using I use Chat, GPT and I use Perplexity. I sometimes use Google Gemini, although it's not very responsive sometimes. But I use it to figure out the SEO value of the content I'm creating. Especially starting with the title. You know, what's a catchy title? What's the SEO of this title?
And I use the different ones. I don't know if you guys have seen this, but I used to get different answers from Perplexity and Chat, and now it seems like the answers are getting closer and closer together, like they're drawing from the same data sets more and more.
So that is kind of interesting. But yeah, so I use it for SEO. That's one of the main reasons I use it.
[00:09:26] You've been listening to AI in Business Use Cases from the Real world. A bit about our Hosts Elizabeth Gearhart, Ph.D. former formerly Elizabeth McNamara is a marketing executive, podcast host and AI strategy speaker focused on how businesses are actually using artificial intelligence. Today, she is the co host of AI and Business Use Cases from the Real World, where she interviews professionals across industries to share real, practical examples of AI in action. Beyond the Hype Elizabeth holds a PhD in analytical chemistry and began her career in industry before becoming a link licensed US Patent agent. She now serves as Chief Marketing Officer at Gearhart Law, an intellectual property focused law firm working at the intersection of technology, business strategy and communication. She is also the co host of Passage to Profit, a nationally syndicated radio show and podcast airing on 38 stations nationwide through the iHeartMedia Network. In addition to hosting podcasts, Elizabeth leads educational programs on AI podcast, podcasting and digital strategy for business owners and professionals, helping them understand how AI is being used today and how to apply it in their own organizations. Richard Gearhart Esquiner is a life sciences intellectual property attorney and the founding Partner of Gearhart Law. With over three decades of experience, he advises emerging biotech and pharmaceutical companies on patents, licensing and IP driven commercialization strategy.
A trained chemist, Richard formerly served as the head of the U.S. patent Group for Novartis and General Patent Council at CIBA Vision. As an active angel investor and Chair of the Investment and Entrepreneurship Committee at Rutgers Health, Richard acts as an innovation advisor, providing a firsthand investor perspective on risk valuation and growth within the academic and healthcare ecosystem. A prominent media founder and host, he co hosts the nationally syndicated radio show Passage to Profit and the AI in Business podcast, translating complex technology into practical insights.
Within his firm, Richard integrates artificial intelligence to enhance operational efficiency while prioritizing responsible and effective real world deployment. He holds a J.D. and is currently pursuing a professional certificate from the MIT Sloan School of Management in Artificial Intelligence for Pharma and Biotech. We hope you found this valuable. Join us again for more stories.
Because the future of business is driven by AI this podcast was recorded at the iHeart Studios in Manhattan as part of the Passage to Profit radio show.
