This podcast episode is sponsored by ChiefAIOfficer.com, offering training and certification through the International Association of Chief AI Officers. Interested in a new career or leveling up your value in the marketplace? ChiefaiOfficer.com can help. Welcome to this episode with Sunjay Chariot. We had the opportunity to go deep on enterprise level generative AI deployments, which is not something that we normally address here. We're usually looking at the SMB, maybe mid-market, but certainly not enterprise. Sunjay had the opportunity for the past two years to be the lead in a company that once he reveals it in the podcast episode, everyone will certainly know that company's name. We cover everything from how he got started, considerations that every business owner should be aware of before they hire quote-unquote AI experts to support their business in the exact areas where you should be focused on starting with the introduction of AI into your business. So get ready for a fantastic episode. Let's get started. Welcome to using AI Word. I'm your host, Chris Stable. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Today I'm excited to uh literally, I'm excited to have Sanjay Cherrion as our guest. He's the founder of 113 Labs, but as I think, as you'll find out uh through the rest of our discussion, his experience is um applicable to a lot of us. Uh Sanjay and I were introduced through a mutual friend. We had uh at Chief AI Officer, we had done a collaborative product with uh the folks at growthhackers.com. Um I met up with the CEO of growthhackers.com recently at a party in Austin for uh private equity and venture funds that were just having a social hour. And I was introduced to Sanjay, and when he shared um his experience with me, I was like, okay, nice to meet you. And then we further had the privilege of being able to uh share some seats on a panel recently with uh the portfolio CEOs from a private equity firm in Austin, which was a fantastic chance for me to learn a little bit more about uh what he's been up to. But this is gonna be a very interesting conversation uh that's gonna address a level of generative AI in business that we we really haven't uh talked about before. So I'm very excited. So, Sanjay, welcome to the call.
SPEAKER_02Thank you. I'm really glad to be here and excited to have this conversation with you.
SPEAKER_01Nice. So, you know, before the thing, I I said for sure, listen, we got to talk about what you've been doing for the past two years because it's sexy and it's uh and it really does establish the the credibility of what you're gonna be saying in the rest of the interview. So if you don't mind, um like just kind of share what the past couple of years, particularly with generative AI, has looked like for you.
SPEAKER_02Yeah, um uh the past couple of years, I've been at Nike, uh, and you know, everybody kind of knows knows Nike. And I've I've uh I specifically was in the tech technology strategy space as global head of technology strategy. And uh right when I got there, um this whole boom happened around generative AI specifically, like Chat GPT, uh, you know, in the December of 22, if you will. Um and I had been playing around with it myself, uh, being a little bit of an early adopter um in that space. And, you know, um, interestingly enough, uh Nike, the CEO was um, you know, being bombarded with questions from some of his uh his peer CEOs through conferences around this generative AI and what to do in that space. And um, I took on the the the the initiative of leading our generative AI strategy and charge in that space and figuring out now those early days, what do we do? Uh, how do we take advantage of this? Is this something that we can take advantage of, uh, particularly you know, across our our value chain.
SPEAKER_01Uh so what was the catalyst for them to get it, you know, to to really want to do this? Was it the release of Chat GPT 3.5 or had it been prior to that?
SPEAKER_02Uh I think it, you know, I think it's the consumer, the release of a consumer grade GPT uh in ChatGPT definitely, you know, spurred it on. But you know, I think more so what that ended up doing um at the kind of business level, at large enterprise levels, CEOs talk to CEOs, boards talk to board members, talk to board members. And, you know, there is a legitimately unlike some of the other hype cycles that we've seen with technology like blockchain or NFTs, I think a lot of you know operators were talking about how could we actually take advantage of this? Is this something real, you know, and I think some of that came from, you know, can this help with our product innovation and drive, you know, IP, drive, you know, greater value from that perspective? But I think what we quickly pivoted to is looked at is like how could it drive productivity in enterprises? So we were asking questions around, you know, how does this make our um our our people, our knowledge workers at Nike a force multiplier? At the same time, looking at it to say, you know, does it help in in our product in our product innovation process? And you know, looking at it from a perspective of productivity uh at an angle around being a force multiplier, you know, we looked at various, you know, um areas of the business, um, everything from sort of product design to, you know, um, you know, software development to um uh you know supply chain and uh other areas and started looking for use cases of where we can adopt this. Yeah.
SPEAKER_01So I I have to ask, did it enhance? Was it a force multiplier that you expected it to be?
SPEAKER_02Um I think so, very much so. I won't uh sort of go into like you know details around that, but I think that you know, uh definitely challenges in that's in that space because you know, you know, lots of people were using it on their own. Uh, but I think you know, we we saw it particularly in areas like in the design space, uh leveraging design tools, and you see it out there um in that in that space. But you know, we very cautious about it too, in in certain respects, like how would that you know impact um the design process, the innovation process, the the IP, if you will, which is still kind of like open questions, I think, in the in the general industry, right? Um, but yeah, the there's uh and then came the advent of like you know business corporate functions. How do we use this for the knowledge worker? Are there co-pilots that we could leverage from existing partners that uh the Nike had, for example, at Microsoft and leveraging some of that? But you know, but regardless of the technologies, like what what all companies are faced with is you know, how do we use these technologies to you know to drive more value in every day? How do we make things easier so that you know people could spend more time on more value-added, you know, uh parts of their job, right? Um, and so you know, how to use UAEI, the design space to curate ideas, but not lose the design and creativity, human creativity in designing a shoe or a shirt, for example, right? And so that's kind of like I think the frame that um that that we had uh and I think many companies are grappled with.
SPEAKER_01So let me ask, where did you go to learn this stuff?
SPEAKER_02Um, you know, then thus started a you know 18-month dive deep into uh you know into everything. You know, it I actually make I actually draw the parallels to the pandemic. You know, I'm I'm a I'm actually, you know, funny enough, I've got a uh background in computer science, but also in molecular biology. And I'm uh you know, I took virology courses in university, and so I I kind of like knew what was happening with the COVID pandemic a little bit more than the average person on the street. But at the same time, you know, we all flooded to Twitter, co COVID Twitter to figure out the latest data on you know, things like that. So similarly, as this was sort of changing uh on a weekly basis in terms of the advancements of large language models and you know the um the accuracy and precision of them and the new models that were being you know released by ChatGPT for the consumer, I was in you know, basically just you know in enriching myself with teaching myself this right away. That there's a number of free courses came out from Google, um, talking to people, talking to like uh thought leaders in the space, uh having beyond Nike, we have a lot of access to kind of thought partners from the various consulting firms, but also the various venture capital organizations in that space. And I just, you know, basically steeped myself in everything about this, um, uh from technical, as much as technical like I could, to kind of business transformation and the kind of results that you could achieve from this.
SPEAKER_01So, you know, I think anybody that's that's messing around with generative AI in their business, they they probably think that they're behind, right? There's just this assumption that, oh, this is, you know, other people are doing, especially with a narrative in the marketplace. What has your experience been with, I guess comparing where you are, and I would certainly consider you an expert at it at this point for sure, with the conversations that you're having with well, you're you're more of an expert than you might think you are, trust me. With the conversations that you're having with peers at other businesses, at the venture capital, like, like where are you see is are are they are they with it? Are they hip to it? Are they are they just discovering it? Like kind of where where do you see um the the professionals at?
SPEAKER_02Yeah, it's a great question. I think I think that there's I think it there's there's a like like many of these questions depends on where you are, what strata of company are you at, um, you know, where are you in the life cycle, uh, what pressures you're getting from various stakeholders, whether that be your customers, whether that be your board, um, et cetera. Uh, but I think the the story and the and on value is very much still um being developed, right? I mean, I think there's a lot of you know bias and sense for sense for urgency. And I think there's it's important to start experimenting and learning, but by no means, I think, is the value case you know clear-cut yet. You know, I can I can sort of put it to the as the technology is changing, if you look at this from a step back and look at a macro level, Sequoia has a great white paper on the value of AI. And their their thesis is effectively like, you know, for the investment that we're putting in globally and from a macro level, it's not generating and it's not slated to model out in terms of generating the revenues yet. But um, you know, I actually think the value of generative AI is more on the productivity and cost saving side right now than it is on revenue generation. I think that will come. And I think there's an opportunity there, significant. And um uh, and as we see the the technology change and we the models be much more um precise and accurate, and we move to even um uh you know autonomous agents and agent, what they call agentic AI, I think we we may be seeing more value. But I think the opportunity for this technology in the business space is around driving automation, uh, automation of tasks that you know um we shouldn't be doing uh in the kind of as a knowledge worker, things that should be at our fingertips, rather and allowing us to move to more insight and more creativity and more um strategy development uh in these in these various businesses. And so I think that is the opportunity, and I think there's some very clear-cut use cases in that space.
SPEAKER_01So, based on your experience and obviously the conversations you're having on a daily basis with others um on the journey, what are some areas where you think that most companies should like it's low risk, uh low resource requirement to deploy generative AI, high potential impact?
SPEAKER_02Yeah. Um, so if any of your companies, and I and look, you have to take uh what what I'm saying in terms of stratification of the company level and size uh in terms of the value, right? And the more you're spending in these areas, obviously, the more value you can with some of this. And you have to really look at the business case in terms of investments. And by the way, that's a big learning that I had. Like really, we we at Nike looked at across the value chain at Nike and came up with, you know, about a little bit over a hundred use cases, but we really prioritized down to 10 to 15. Um, and then even prioritize more based on investments in business case at that time. And that's something that's dynamically changing in terms of the cost of compute, things like that, when you factor that into business case. Yeah. But some areas that are kind of low-hanging fruit, software development seems to have empirical evidence now that you can actually drive savings with, you know, co-pilots for software development. And we're seeing, you know, some of the data in general from the industry come out that um, you know, senior software engineers are really liking this, um, these co-pilots. They're helping with, you know, um generic kind of level one type of coding projects uh and making things go faster. Uh and so that's that's an area I think, you know, right off the off the bat. A second area I think is, you know, I'll I'll start kind of like general knowledge worker productivity and getting first drafts, particularly when you have writing use cases. And you can extend this out to more specialized writing in a business like legal drafting, for example, or product briefing drafting, right? Or marketing briefed brief drafting. And the models are getting quite good, especially when you couple them with training on proprietary data to that company, you can get some pretty good second and third level drafts of writing. And that just makes things go a lot faster uh in a in a company, in an enterprise setting. So those are those are some areas that I think are pretty low-hanging fruit that companies can you know figure out how to implement some of this these technologies. Even you know, even smaller companies leveraging some of these best of breed uh tools off the you know that are coming out right now can can I think generate some significant force multiplier type of productivity improvement.
SPEAKER_01So uh obviously you're uh many steps ahead of somebody who's listening to this and is like, okay, we're ready to do something, we just don't know what. You mentioned that you guys went to a process to develop uh 100 plus potential pilot projects. What what would you recommend to somebody who is at that stage to where they're like, we're we're ready to go, but where do we start?
SPEAKER_02Yeah. I you know, I think there's a couple things. Number one is this shouldn't be a technology-led um discovery process. Uh what do I mean by that? Typically in an organization, the tech, you know, even though this is very promising technology, in order to get the kind of adoption you need at the end of the stage, you need to really start with some people who understand the business. Um and the and particularly the business workflow that you're trying to like transform or, you know, for lack of a better term, automate. Um, and I think, you know, one of the things that you should do is think about having kind of a squad and empowering from the top kind of a business leader to talk to other business leaders in that space to figure out where to map their business workflows or processes and figure out where can AI or gender of AI really add a lot of value. Um, you know, where are the hotspots that are kind of where you've got where you can marry and match the the use case with the technology that is coming out there right now. Um so that that I think is a is a kind of important, you know, first step in terms of and second step of identifying who those business champions are and then spending time with the business to like map out what those use cases are. And then you you end up coming to a use case and developing a bit of a library. And then it's a it's a situation of like understanding um across kind of three categories, broad categories in my mind, how you analyze those use cases for value. Is this something where the technology can drive in the sort of three years it can drive um productivity improvement? So not necessarily taking costs out, but you know, it'll make um that team faster and more productive and allow them to focus on value add. That's one. Is this a case where typically you could actually drive cost savings? You don't need as many people because you've taken that step, you've replaced it with the generative AI or AI, and therefore you don't necessarily have that cost anymore. And I've seen this you know happen in like you know, third-party costs, particularly as a company is sort of X, you know, outsourcing something that's third party, um, you can actually drive some of the cost savings that way. Um and that's that's hard cost savings. And I think it matters a lot, especially to the to the to the to the company from a from a labor and or sg and a perspective. And the third area is revenue um uh increase, right? Revenue opportunities. And this is where I think we're seeing a lot of promise and opportunity, particularly in the digital commerce side, e-commerce side, where you've got conversational search that's driven by AI that that you know can be implemented on commerce websites to have better and more accurate search functionality, or you know, um more virtual conversations with you know a shopping assistant, for example. And those are things that could increase the conversion of you know customers buying products, buying your products. Yeah. And I think that's like the third area. It's a little bit, I think it's still immature, and I think we're seeing you know more and more tech every day uh improve in that area. But I think uh I think those are the three things that you would look at and you would assess those use cases along those three dimensions, broadly speaking.
SPEAKER_01You know, you brought up a good point, um, and it you know reflects on my personal experience. When I first heard about, I'd heard about ChatGPT 2 and things like that, and I was like, I wasn't that interested, didn't see an application for it. I was a business development professional, I you know, was operating at a strategic level, not at a uh tactical, and it seemed like there was a lot of tactical application. So ChatGPT 3.5 comes out November 2022, and my first thought was this is going to be a huge opportunity for somebody else. I'm not technical. This is, you know, it's like it's artificial intelligence. And my exposure to it had been in the context of machine learning and data science and things like that. And it just wasn't, and it took a minute before I realized that. And I I think companies may be seeing that, but my concern would be that companies would say, Hey, chief technology officer, we need you to lead generative AI. And in my opinion, that's the wrong move. And you kind of referenced that at the beginning of your three points just a moment ago, where you said it it's not a tech-led situation. Um kind of share share your perspective on on the pros and cons of having a business expert versus a technology expert lead the the efforts within a company.
SPEAKER_02Yeah, I I I I'm I feel pretty strongly on this, which I I I I sense you you're in the same ballpark here in terms of thoughts. You know, the the hard part in in implementing this top technology um is sustaining and getting the adoption and usage. And therefore, in those three you know, value categories I mentioned yesterday, capturing that value. Um that's still gonna require humans in the loop, and it's gonna require people who leverage and use this. I mean you talked about your your your case, and as you were talking and thinking, man, I felt similarly, but um, I started using ChatGPT personally to like you know make just life more productive, regular life, not what's at more productive. And um, and then I I see that now in my business life also as a as a tool to make it much more productive. Um, but but I but I but I think that you know in in enterprises and companies, uh dependent despite the scale and size, this is not something that necess that should be driven from if you are really caring about the end-to-end value, it's not something that should be driven from the technology organization. Um I think the technology technology organization plays in a very important part in this because what we haven't talked about is actually the technology to make it happen, integrating it in a safe way, in a secure way, having the right art garbage, choosing the right technologies. But to me, it's not necessarily it's going to be similar to like the enterprise software. It's not about choosing the technologies, but what outcome do you want for the business? And I think you really need to have something like a chief AI officer who is much more of a um, you know, business uh who understands business, who understands workflow transformation, who understands kind of value creation cases, and it a lot is able to mobilize the organization around an initiative that's really going to drive that value. The technology is just, I think, uh like you know, really accelerates the ability to do this, much more so than um enterprise SaaS did for you know for enterprise over the last like two or three decades. Um I think that, you know, and I think if I can sort of expand just a little bit more on that, is that I think what Enterprise SaaS did was create you know large data sets or systems of record, but it didn't necessarily integrate it all together. And I think now with uh AI, particularly agentic AI, you have an ability to turn to take your HR data, your finance data, your you know, you know, services, met services, metrics data, you know, legal data, corporate functions, combine that and have agents communicate with each other. And actually the workflow that you had people you know talk into, that especially that that lower lower level order workflow where people may be in spreadsheets and you know on Emails, that is now you know automated. And now you can have different conversations. You know, you can have strategic conversations about finance, strategic conversations about talent management. And um, and I think that's that's what this technology is able to do. So you do need a technologist to make sure that the tech stack is there, and that's right. But this is very much an initiative that you know was going to really drive transformation in the organization that needs to be led by somebody who's a business leader, who under who has depth of technology, who has, by the way, who has depth of technology, who can call um, you know, who can understand quickly and figure out how to translate and work with the CTO's office or the CIO's office to implement that technology that's needed.
SPEAKER_01That makes sense. So if you were going to go into a company, um what what would be a a department or a role that you might be like, these people tend to be very good at leading that deployment from that chief AI officer kind of paradigm? Yeah. I think an ops person, is it a what is it?
SPEAKER_02I, you know, I'm I'm a little bit of biased last 10 years I've been in in operator roles. I think, you know, understanding deeply the operations of a particular business function is important. I think that typically what you see at larger organizations is you have transformation offices or transformation people. That will be a fertile ground to hunt for these people and upskill these people from an AI perspective. I think the other area is kind of like operations. Um, you know, typically in other organizations, maybe in in a, you know, when you sort of go down the stack and strata, uh, you have chief operations groups or or operations folks. Those are areas where I think they have some technical capability, but they also really know the business very well. They have good relationship management expertise, they're very metric-driven and metric-oriented, um, uh, and they live and die by by those metrics. And I think those are people who can who can help um and be leaders in this new space.
SPEAKER_01If you're enjoying this episode and want to learn more about how to start using AI at work, we've made it easy for you. For just one dollar, you can have full access to the Chief AI Officer community, which will give you additional training, custom software, daily training calls on AI tools, using AI automations, getting more from your chat GBT sessions, and the business of being an AI consultant. Simply go to chiefaiofficer.com forward slash insiders to accelerate your AI journey. Now, back to the episode. You know, this that's good. One of the things that uh, you know, we we certify chief AI officers in our program. One of the things that a comment that I get regularly is I'll say, what else have you studied? And people will reference a few of the courses, particularly from universities, well-known uh universities that have remote learning. Um, and I'll ask them, like, that sounds amazing. How was it? And the comment seems to be that they they're trying to teach them a lot about machine learning and LLM architecture and things like that, as compared to um developing a perspective to evaluate your business operations with an understanding of the capabilities and limitations of generative AI and where it can kind of not even specifically or tactically, but thematically fit into, oh, and finance, they could probably do this. And so do you think that it's, I don't know, how important would it be for this individual? Let's say you go into a company, they say, we're ready to do this, Sanjay, we need your help. You you find the individual, the perfect candidate for this internally within the organization to kind of be your proxy inside if you're gonna be that outsider. Um, how important would you say it was for them to understand that side of generative AI in particular?
SPEAKER_02Uh the the the tech the technical side of that, are you saying?
SPEAKER_01Yeah, like like what what what they would go like I'm not gonna you know crap on MIT, they're a fantastic institution. However, their their generative AI course for for leaders, my evaluation of it was that it was kind of technical. Yeah. Um and again, for me, that was a personal um uh impediment, like, oh, I'm not technical, therefore I'm not gonna be good at at generative AI. We'll come to find out. My understanding of how to you know scale businesses was the exact skill set that I needed to be able to learn these things. And I'm I'm kind of wanting to address, because again, we don't have people at your level um on the podcast regularly. It's it's it tends to be SMB environment. And for those who are listening that are operating at that enterprise level, I I want to do as much as I can to have them have that aha about like, oh, I can do that. Oh, this isn't uh a big lift kind of thing.
SPEAKER_02Yeah. I I think that you know the the um adult learning programs that are coming out now, they're coming out in droves. UT Austin has one that actually is very much affordable compared to the other ones like Duke and MIT. Um look, I think that if you you can get really deep into the technicalities of neural networks and large language models and GAN technology and rag architecture. But at the end of the day, from a business perspective, in terms of what you're trying to do, that that level of depth is not necessary to understand. Like when you're working in a team environment, um, you know, you can lean on your technology co uh colleagues around around that. But more importantly, I think more importantly, I think you have to sort of understand what your role in that organization is. If your role is to leverage AI to pivot your product in a way that um you know makes sense and or or helps with driving greater customer greater growth, you might need to go deep into the into that technology to figure out where that technology is, um, at what stage, what's coming, you know, and and and to in order to integrate it into your product, right? Um and that's that's typically a lot of these tech organizations. If you're if you're a digital product, technology leveraging that, I think is you know, you may need to get technical. But if you're more on the operation side and you want to leverage this technology because of its promise in um, you know, uh transforming your workflows, taking out costs, um, driving new revenue generation, um, you know, there that level of of depth is is a little bit shallower on the technology side. And you should really more focus around, well, how are you gonna get the adoption? You know, how are you gonna, you know, what partner should you choose? And what, you know, how are you gonna remap this process to figure out how you're how you're gonna get the technology to take over some of that process step versus um versus the type of technology that you use. That's not really sort of sort of necessary. So I like that that's my my take on it. Yeah. Yeah.
SPEAKER_01We're very much aligned on that. Now, one of the things we talked about um was that you've got the exciting opportunity in your career to be able to uh use the word pivot, right? You're going from um an internal role to somebody who is able to advise multiple companies from that more strategic environment. And I'd like to talk about that. I mentioned at the beginning of this, I introduced you as the founder of 113 Labs. Um, share with me kind of the direction that you want to take with that.
SPEAKER_02Yeah, absolutely. Um so 113 Labs, 113 is a bit of a uh, you know, uh a riff on the idea of one plus one equals three and it drives synergy. And I think that there's a lot of um, you know, there's a lot of uh um uh interest in this space, obviously in generative AI, but at the same time, I think that it's a bit scary for a lot of people and a lot of companies. And I think that um there's a there's a certain level of demystification. It feels like we've been talking for the last like five, 10 minutes. What kind of expertise do you need in this and can I do this myself? And you know, having lived this, I think that you know, companies, regardless of your size, don't need to spend um a lot of money on expensive management consultants or for that matter, um, expensive technology in order to start getting results here. And one thing that I'm really interested in is you know, how do you um, you know, upskill people in your organization so that they can start taking advantage of, so that they can lead this? Because what what I'm really, you know, you know, concerned about is like how this is gonna impact um the workforce. And I think that, you know, as with many other technology transformations, uh what we want to kind of like avoid is um people not like taking this technology and like looking at the next set of jobs because it's not just about reduction and forces that we're gonna see. I think we're gonna see a whole new um, you know, uh type of job take place, humans in the loop, and we're gonna be able to like benefit from this because we're not gonna be spend time, you know, doing mundane, tedious tasks. So, how do you take the the people in those organizations and upskill them and make them self-sufficient? And so what we're trying to think about in 113 Labs is how do you bring some of the strategic thinking, uh, core sort of strategic skills, apply them in AI, and co-deliver projects to get squads in these companies actually rolling up their sleeves and doing this work and kind of empowering them with our experiences. And uh, me and two other colleagues have started, you know, on the early adoption train and in some in some big brands, and we've got results, and we're coming together and putting a methodology together to help teams and companies do this themselves, and quite frankly, like like take like not not have us, not them have not have them relying on us or any other external consultants to make this happen. Um, and that's kind of like the the the general thesis that's forming right now. Um, and and we we we think we have a pretty unique co-delivery approach that will help um um help to sustain the adoption. Because a major part is you know, once you've got the technologies implemented, you know, how do you think about you know the new world and how do you think about the these teams adopting them? And one one thing that's really interesting that we've been talking about is you know, we this is probably a way to kind of create the next generation of leaders in these companies, and then that will trickle down into the organization. And and and that's that's kind of like our our vision. And I think that's it's a it's a bit um uh part of the purpose of what we're trying to do with one one three, creating that synergy of one plus one equals three.
SPEAKER_01So for you guys with one one three, you walk in the door, and the first focus is going to be on uh the strategic upskilling of the decision makers and the executive team.
SPEAKER_02I think it's first figuring out like, you know, where in the company can we actually uh deliver value, right? Um and and and but equipping the a set of a set of leaders, much like a you know, uh a squad or a set of business-oriented leaders with some technology, a technical savviness to lead that. Like, you know, show them how to create a use case library, show them how to derive uh an AI business case and you know, make some difficult decisions or easy or simple decisions, so you know, um, right away. And then um help them with the kind of uh AI upskilling training and literacy and governance that you you need. I think there's this is a new space. And I think that um, you know, there's a lot of uh early adopter um uh um benefit and learnings that that these companies can actually implement. Um and the uh the the idea is like, you know, how do you then you know upskill these individuals and get them into a level of depth in AI, where to your point, it's not necessarily a deep technical knowledge set, but how do they use this and apply this in their everyday work uh and in the work of their colleagues?
SPEAKER_01You mentioned a number of times, and we haven't talked about it, and I know that it's very important, especially for the larger companies who um are particularly uh risk averse, but it's the the usage um policies, the usage arrangements that they've got combined with that training. Do you have a particular, I don't know, perspective on how a company should approach that side of things?
SPEAKER_02Yeah, um very much so. And this this is where I think um uh it can get technical, but not but not necessarily uh an understanding of the technology in terms of how it works, but rather how it's applied. So, for what do I mean by that? There's a lot of open source large language models that companies can um avail of and their technology organizations can help you know get access to. Well, you want to make sure is that if you're a company that is developing IP and leverages that data, or there's strategic IP around your business, when you're interacting with these open source large large language models, you don't want um your data to be committed in the open source. I mean, uh you know, a tenant of open source technology is it's available to all. Um but there are ways architecturally, you know, from a technology perspective, to create a if you a walled garden, if you will, where that that data is still trained. Uh, you're using that data for training, but it's not committed to the open source. So, you know, this is the this is this is what happens technically, but effectively what you're trying to do here is like you're trying to look at data and security around that data in a new way, particularly you know, using these large language uh open source models. And I I reference that because people, companies are not going to be able to invest in creating their own foundational models. Well, remember that most companies are not gonna be able to invest in their own foundational models. And when you want to take advantage of that scale, you have to use something that is cost efficient. And so, you know, the the security and creating the right kind of guardrails is important. That's the first thing. The second thing is, you know, teaching your um people how to use AI and what data to use in training and what not, how to write prompt and what kind of you know data you should include in prompts and what you should not. Um uh and so like having the right kind of um literacy around AI for the company, I think is important because that also will help, you know, in the implementation, the safe implementation of that, along with some guardrails, um, uh, but also in in more effective use of of um uh of the AI.
SPEAKER_01So is that something that you guys would assist a company with, or do you kind of let them figure that out on their own on the on the guardrail side of things?
SPEAKER_02Yeah, we we have starter kits in that space that you know that provide a good kind of starter kit um around guardrail usage and prompt engineering. Um uh, you know, that that that but it's really you know empowering these individuals to sort of expand on that in their particular environment and and build off of it.
SPEAKER_01And then as far as um the AI literacy, what what time commitment, maybe not dollar amount for upskilling your your team, but how much time would you recommend for a client team to spend on a daily, weekly, monthly basis getting the day-to-day users tuned up on how to use it day to day?
SPEAKER_02Yeah, I I you know, this is this is a great question. I think that you know we're living in a time where this is not something that's gonna be a lunch and learn uh, you know, at a company or um uh necessarily kind of like dedicated uh training and that's it. This is really about experiential learning. And I think we're going to, you know, if you if you release this technology in a way um that is you know with the right kind of security and the kind, right kind of guardrails that we were talking about before, I think that the best way to use this is to learn. And I think we're gonna see new use cases pop up and iterations. And you know what? There's this product brief that I'm using, I'm using this tech technology to write this product brief. There's probably a better way as if we train this on you know the last five years of product briefs, for example, um, you know, and prompted it this way. So that experiential learning, I think, is much more powerful than didactic learning and training environments that we've seen for regular um for historically for other software. And quite frankly, the user interfaces on these new generative AI technologies and tools are so you know self-learning. Accessible. Um accessible and self-learning. I I I really, you know, I tell people we're in this 1996 moment, and that kind of dates me. I'm thinking about Netscape and you know, the internet and the uh the accessibility through websites of of information, but um there's something different here. It's that information's already curated, it's already um analyzed, it's already performed, put into a way that that makes sense. And then with agents, we're we're actually, you know, we're actually not doing the kind of lower level work. And so I think this is very, a very defining moment. Um, and I'm I'm one that's very skeptical of a lot of technology hype cycles, but I've seen the value in this. And I think that's the the the learning by doing is is very much um uh a tenanteer.
SPEAKER_01I'm I'm particularly interested in how there is some concern by the users about what they might have heard some doom and gloom stuff, right? And as somebody like you and I, we're we're very familiar with these tools. Um, and we know that at this stage, AI is not marching in like the Terminator and taking jobs. However, people who are just hearing the Oprah special with Sam Altman or like like those sorts of things, there is concern because it's um it's the unknown, it's a new paradigm, and anytime there's there's something like that that shows up, the uncertainty can be unsettling for the the mass of the teams, right? How are you suggesting that companies uh manage the narrative from a change, introducing this change without necessarily causing a lot of fear or uh resistance?
SPEAKER_02Yeah, it's a it's a it's a great um it's a great question. I think a big um a big issue uh in enterprises. Um because, you know, as I talked about, so there are those three those three concepts of value, um uh, you know, productivity improvement, cost savings, and revenue generation, there are going to be situations where um you know the old way of doing things is no longer uh no longer in existence. You're gonna have the tech or in some cases robotics, you know, uh or robotics enhanced with AI going to take that over. That is inevitable. Um I think that uh that is something that you know the the the that we're gonna have to figure out how. I think I'm I'm one who kind of looks at it from more of a optimistic perspective where um you know how can you use this to create new sources of value, this technology, new sources of value? So far we've been talking about like you know, automating and taking existing work and things like that. That's interesting, but I think what's even more interesting is can the technology be used to create new sources of value, new products, uh, new ways of doing things, like completely. Um, and it's those areas that people have to kind of move to or migrate to uh in terms of leveraging and learning and using. And um, look, we've seen this, we've seen technology shifts and we've seen you know macro movements uh you know of uh of jobs and labor markets move. I think this one has more promise. Like let's look at healthcare, for example. We are um we are in the midst of a labor shortage. Um not enough nurses um, you know, to withstand or to be able to support rather um the growing uh and longer living population. Um voice AI and AI navigators to help with navigating people through um healthcare uh options, uh voice and AI to help with you know answering questions and providing kind of first order level support that you would go to to a pharmacist or a nurse or a nurse practitioner is a way, is a new source of value. And it addresses labor shortages. And I think we're gonna see more of that um happen in the market. Um, but you know, there there is going to be a lot of change, and we're gonna see a lot of it's how you it's how you approach this, it's your mindset, it's you know, operating. I've got three kids and I'm constantly talking to them about growth mindsets versus fixed mindsets, and part of that is that mindset, and we have to um we have to embody that in our in our day-to-day work as well when it comes to this technology.
SPEAKER_01Yeah, that's a part of the deployment uh framework that I think needs to get dialed in because um, you know, my concern would be that if I were going into a company and I didn't vet the individuals who are participating in the at the pilot project level for their like comfort level or fear level of AI, that I might get some false negatives on the results because an individual who didn't didn't see it that way, had the fixed mindset versus the growth mindset, might I mean they're they're not incentivized to do what they think. Think might be obviating their role, right? Like it's just not necessary anymore. So that's an area that I have a particular interest in. If there was some magic words or something, but I haven't found them yet.
SPEAKER_02I don't know if there is a silver bullet for that, but um in you know, spending 25 years in the technology space and being involved in digital transformation, you know, one of the tricks, and maybe it's an old trick now, um, that I was taught by one of my mentors, um, is actually, you know, using those individuals and making them the leader of the initiative. Love it. You know, uh it's oftentimes the naysayers are the ones who are you know questioning, well, how would you do it if you wanted to get this kind of outcome? And engaging them in that way, and then putting them in that leadership is to say, look, you're gonna run this initiative or this squad right now, and this is what you're doing. How would you do it? Here's the technology, but again, it's not about the technology. If we're trying to achieve this outcome and you have these enablers, how would you do it? And um, you know, I've I've done that before in my career. Um uh in fact, I've been the the naysayer who was who was like who was picked off like that on one of these initiatives, and it starts getting you thinking about in a different line, in a different mindset, right?
SPEAKER_01I think that's a fantastic. I hadn't even considered that and uh am eager to test it. So, Sanjay, as we get to the end of this episode, I I want to make sure that here's what I know is that there's a lot of companies out there that are looking for advice for somebody just like, hey, just do it, right? At all levels, everything from I just need a couple of questions answered to we don't even want to get into this, you're the expert, handle it. Um and they're not having an easy, there's it's an inefficient marketplace. There's not, you know, an upwork where I can go and I can find the experts necessarily like I could with WordPress or you know, product design or any of that stuff. What would you how would you, if you were in a business owner's seat right now who is interested in doing this at any level, whether it was a small to medium business, mid-market, all the way up to enterprise, what would be what would you look for in that quote unquote expert to come and help you?
SPEAKER_02Yeah. Um, well, I I would look for practical experience, like have they done this already? Sure. Uh, you know, versus kind of a talking head and and and somebody who's kind of on you know on Twitter, looking at like Twitter, have they done this before? Um, have they, you know, have they been in the trenches? Um the the second thing I would look at is, you know, um, are they proposing you know and uh value right away? Like are they giving you sort of some actionable you know ideas to go after? Um, you know, I'm I'm I'm advising a couple of different boards right now that I'm on, uh particularly around their product, um, and like thinking about this. And it's it's interesting how even like CTOs and and COs, this is new for them, and trying to figure out the the linkage of the business value. They're much more focused on like you know, talking to vendors and getting hearing what Microsoft is selling in AI or Google or AWS, uh, but there isn't that sort of linkage. So I I would sort of understand like how how can you like drive operational business value? That was that's the second thing I would look for. Those two things I think are are kind of like for me, if I was an if I was a CEO or board member, I'd be looking to, you know, kind of some level of um uh of practical experience with this technology, uh so it so it builds some bona fita. And um, and second, like time to value. This is not something that should be, you know, um, you know, a 16-week consulting engagement and you're given a report. Interesting. But you need to like, you know, get in there and do this. Um I would I would add the third thing, uh, you know, get somebody who's if you're looking for this help and advice, somebody can get your people engaged and get a squad or a team around this to start implementing. Uh the the you know, you don't this is not this this information um is not something should that should be kind of housed in some kind of subject matter expert. This is something that has to be, you know, day-to-day. And you gotta you you as an organization have to kind of build this muscle internally and let it diffuse in the rest of the organization. Uh, and and there there's a there's an argument to have a chief AI um you know officer and or a squad or a team that that will help diffuse that. So I think that's important. Those are three things to look for.
SPEAKER_01So uh obviously, if those aren't present, those are red flags. Would there be any other red flags that you would advise the business owners to be looking out for? Um for that expert that they're hiring?
SPEAKER_02Yeah, you know, like uh red red flags are kind of like, you know, uh deep investment in the technology first. I gotta buy the whole tech stack.
SPEAKER_01Good point.
SPEAKER_02Yeah. You know, I've got to sign up for you know the this these kind of seats. Um, you know, uh look, I think you're gonna have to spend you know investment in technology, but I think it's you know, understanding the business value, the you know, having at least a high-level case of if we invest this, this is the kind of return we want. And by the way, we gotta have those business units on the hook. They're gonna they've got to be bought in, right? We're gonna invest this, we've got to be bought in. So, you know, as opposed to like, okay, if we can set you up with you know a thousand seats with this license of co-pilot for this, you're gonna see value soon. I I think that that's uh that's a little bit of a vertical night to me. Yeah.
SPEAKER_01Yeah. I heard a very similar uh perspective. Um, somebody was saying, uh, you know, do is it worth it for us to get all these co-pilot licenses? And the answer that I heard that made the most sense was if you don't train the people how to use it, it's not worth it. If you train the people how to use it, heck yeah, it's worth the 20 or 30 bucks per month if they're using it, right? So that was a fantastic answer. Now, um, for individuals who are like they've like what they've heard and they're not necessarily wanting to strike out on their own and figure this stuff out and do what you had to do two years ago and and you know get the information wherever you could, if they wanted to reach out and connect with uh 113 about some solutions, what what does that process look like for them?
SPEAKER_02Um happy to happy to connect with them. I can I can you know leave leave you my contact information and and and connect with folks um you know as as they as they please. I'm happy. Look, uh this is not some kind of like you know knowledge that I want to sort of uh uh uh you know uh keep to myself. I think that the more and more people kind of like, and I'm happy to sort of share even my kind of like personal um you know uh knowledge uh gating plan around this and the the websites and the people podcasts and the the the papers that I I started going deep on. I went I went through some significant rabbit holes, but um yeah uh but uh but uh it was very interesting and I think very necessary. But happy to share my contact information with your with your listeners and and connect for sure.
SPEAKER_01I'd love to be able to give them that and also um any place on social where you seem to have your uh where you shine the brightest, I guess I'd love for them to be able to follow you because I think what you're doing, especially from where where you're coming from with it, um like you've been doing this for a couple of years in an environment where it really mattered if you did it right or wrong, right? It wasn't just an experiment kind of thing, it had it had major impact. And there's not a lot of people that, and I talked to a lot of people in this space at all levels, there's not a lot of people who have done that. And you referenced this earlier. I used to be one of those guys at those at the big consulting firms that got paid a lot of money. And and I was a little surprised at how much they were charging for how little I knew. That's just the big secret, right? And I I think that it's important for companies to know that if they have the big budgets, you're at least not getting somewhere up that up that chain of command in those consultancies, somebody knows something. It may not necessarily be the person sitting in your office today, though. With you guys, that's not the case. It's you are that person that it would have gotten rolled up to if there was a big situation because you've been there and you figured it out. And that's that's uh uh like you said, I mean, the the experience that an individual brings to the table on this makes it the learning curve isn't discovered on the client. Yes, it's already been handled. And I think that that's that's a best case scenario.
SPEAKER_02That's a really important point what you just said there, Sputley, that the learning curve is is not at the client. And and because it's so new, like that's I mean, look, nothing to I I used to, I was at Accenture for over a decade, and um nothing to take away. They do have experts who are good, but this is so new that um it really depends on, like you said, who's in front of you and how deep they are gone. And uh the the the the end value of clients who are deep into this is still very small on the grand scale of things. And um, you know, there there's there's ways that you can you can benefit um you know in this space without necessarily investing significant amounts in big brand consulting firms. Um I can tell you like this has been a fantastic thing when we were you know when we were deep into this, um I I I actually called um six or seven consulting partners to come and tell us what they knew about this space. Uh because I was developing a primer uh for on it. And you know, it wasn't it wasn't much different from RT's you know at that point in time. Now look, they've invested a lot. I'm not taking anything away from them, they're great terms. Uh but um uh this is in a new way democratized uh the technology democratizes it itself for you to use. Um if you've ever used of any consumer grade, you know, uh uh tech AI technology, whether it be Perplexity AI or Chat GPT or the various now slew of software that's available to the students. We haven't even talked about that, but um uh you know, to to kind of high school and college students, um, it's becoming very mainstream. Crazy. Yeah. Yeah.
SPEAKER_01The future's exciting. Yes, Sanjay, thank you so much for taking the time, and I know that you're busy, and um, I'm gonna provide all the contact information for Sunjay and 113 and the show notes, and I look forward to uh hearing big things about what you guys are up to. Thanks, thanks. Thank you, everybody. Thank you. Thanks for tuning in to using AI at work. Don't forget to subscribe for more conversations about how to use AI at work. And a special thank you to our sponsor, Chief AI Officer, for empowering businesses with AI education and training. Visit their website for a free AI readiness assessment and AI strategy guide to help you get started using AI at work. That's www.chiefaiofficer.com. Well, thanks to our producer, Evan DeSonnier, for making this episode possible. Follow us on Twitter and handle UsingAI at work and visit www.usingai at work.com for free resources to help you harness AMI in your role.