Where the Human Versus AI Sits

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Julia Nimchinski: Alignment. Jason Aporowski! Nick, Mehta! Welcome! How are you doing.

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Jason Napieralski: I’m doing great. How are you?

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Nick “Mehtaphysical” Mehta: Good to see you both.

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Jason Napieralski: So should we just jump in, Julia.

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Jason Napieralski: So I. This is my 1st moderating that I’ve done, and I’m not very moderate, so I don’t know how well I’ll do but I’ll just. I’ll start by introducing myself. So my name is Jason Naporelski. I am a former big tech. Exec so worked for Google, worked for Amazon, worked for Oracle, and am now recovering from that.

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Jason Napieralski: And I just started a new consulting company called the Alpha Initiative, and the entire purpose of this company is to help Ceos

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Jason Napieralski: understand, grasp and start to use AI. And the reason why it’s at CEO level is that that is the person that needs to understand it the most and be able to implement it throughout the business. I think, as well as I’m focused on helping what I would call real businesses, not the kind of business I’ve been a part of before. So construction companies and and things like that that are

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Jason Napieralski: you know, just starting to understand what this has to do with it. So that’s that’s what I’m working on. And Nick, I I

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Jason Napieralski: I your resume is 3 and a half miles long. You look up. You are central, casting for a Silicon Valley executive, as a matter of fact, is, was Silicon Valley written for you or about you. I’m not sure.

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Nick “Mehtaphysical” Mehta: Yeah, totally. I was that the the cheesiest, most annoying guy in the the show. What is that guy’s name? I’m that guy. Yeah. So. Yeah, no, totally that when you said stereotype of Silicon Exec Valley executives, I was like, that’s definitely not a compliment. But I’m just kidding.

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Jason Napieralski: I’m glad you say that. But anything else you wanted to mention about your background. I know you’re a CEO of Gainsight, which is, you know a bona fide unicorn, I think, at this point. But anything else you want to mention about yourself in context of this conversation.

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Nick “Mehtaphysical” Mehta: No, I’m except I’m just absolutely obsessed with AI in a way that’s probably unhealthy. So I’m happy to talk about any of this stuff.

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Jason Napieralski: So we’re focused here on Customer service roles within AI and specifically around your company does a lot of work that with that so? You know, I’ll kind of jump in with the 1st question, and and just ask you, how is AI transforming?

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Jason Napieralski: You know the day to day work of Csms right now? You know, given today’s technology, I think it’d be interesting to kind of focus on that first.st And then how is it changing. You know the skills and the the types of things you’re looking for in Cs people right now.

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Nick “Mehtaphysical” Mehta: Absolutely. So the 1st one we can definitely dive into this more. You know, we, we’re definitely at the center of all this because we’re just obsessed with it. Meet every company all the time, but also doing a lot in our own technology, stack around helping people use AI in driving value for their customers as well as a better experience for their employees.

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Nick “Mehtaphysical” Mehta: And you know, 1 1 way, I think about where it’s like where it’s happening today, and where it’s like coming a simple like 2 by 2 matrix, right? So one axis is is this in a technology AI usage for internal productivity, effectiveness, meaning employees using internally? Or is it something people are exposing to their customers?

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Nick “Mehtaphysical” Mehta: And then the second is, is it a mature use case? Or is it more of an emerging, which is what you were alluding to? So just to give you some examples from each of those, so a mature internal use case. Obviously, you know.

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Nick “Mehtaphysical” Mehta: write me an email summarize this document. You know things like that right? Those are like very straightforward one. That’s, I think, becoming more and more mature, and I would argue the most valuable thing in probably business, but all in usage of AI, but also.

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Nick “Mehtaphysical” Mehta: even as individuals, is a deep research which is a feature available in Openai pro as well as in Gemini, and maybe some others as well, and it’s an agent that you’ll go in instead of like the traditional query response of like a Openai 4 or 3. It’ll like it’s a longer running agent to run for a few hours, and you can go and give it an open, ended research task.

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Nick “Mehtaphysical” Mehta: So, for example, one thing, like an example of something that one of our Csms used, he said, Okay, here’s a document of our product functionality.

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Nick “Mehtaphysical” Mehta: Here’s a document of what the client said their goals are. They actually kind of given us like a very detailed presentation of the goals, and I want you to go on the web. Look at all the information with this client news, etc. I want you to look at these documents I’m gonna think about for a while. Come back to me with an integrated document, how we should pitch our value to this client.

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Nick “Mehtaphysical” Mehta: and it was awesome, and it took, you know, it was just like something. Somebody would have spent all this time and not done nearly as well. So that’s an example of an internal, more and more mature use case. And then the internal, more emerging use cases.

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Jason Napieralski: Hey, Nick, can I stop you there for just I just want to question you on that last point. Do you think that this puts Mckenzie out of business.

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Nick “Mehtaphysical” Mehta: I had lunch with the partner of not Mckinsey, but another big one of the other big ones, and he’s like, no, I don’t think it does. I think what it does, though, is it makes it so. The work that analysts would do is not, doesn’t need to be nearly as much. That’s what an analyst would do. But nobody hires Mckinsey to get that report. Then they want to talk to that partner.

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Nick “Mehtaphysical” Mehta: But now interesting is, I can imagine a world where there’s some challenges this one which I’ll describe, but where you’re like Mckinsey or Bean, or Bcg. Or whoever has senior people, and just way less junior people. And the client mainly is interacting with senior people.

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Nick “Mehtaphysical” Mehta: because all that administrative stuff is done by AI. There’s a big problem which is. Well, then, who are the future senior people? Because all the senior people used to be junior people. So that’s a different problem. And I think I think Brett was alluding to this a little bit and on that internal use case. What’s interesting, the more mature internal, the writing of content, the research, etc. What today most people are just using the Llms themselves, right? Like individuals, are just in companies using them and doing awesome things with them.

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Nick “Mehtaphysical” Mehta: But what’s interesting is like, oh, all of this products people are using are building them into. Think about like when you’re on a Zoom Meeting. And now you have like transcription, and follow up tasks and recommendations on the sidebar, and catch me up on the meeting, and it you could, before there used to be apps that you would use to do those things. And now it’s just built into zoom. So, for example, you know, gainsight. Now, our products have all the email writing summarization. All that built in none of that is novel. I mean, God like, that’s like so

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Nick “Mehtaphysical” Mehta: obvious now. But it’s just built your workflow. And so I think some of the internal AI usage is gonna eventually, like as it matures, it gravitates into the products people use already versus the emerging ones where you’re seeking out new technologies, or you’re using the Llms creatively yourself. So as an example, like, we bought a company that’s called Staircase.

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Nick “Mehtaphysical” Mehta: And it’s essentially like uses Lms. To analyze all your communication with your customers and pull out all this information about like who they are and where there’s risk. And all this is really, really cool. And that was a startup.

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Nick “Mehtaphysical” Mehta: And we bought it. And now it’s just gonna be part of our product. So it’s just gonna be like more more mature as it goes. And so I think there’s a lot of emerging internal use cases that largely about analyzing data, because we all know, like Llm’s 1st class

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Nick “Mehtaphysical” Mehta: job is, you know, language right? Large language model. But they’re getting better at analysis, you know, most people hopefully tried like, I’ve got a spreadsheet. Help me figure out the meaning of this, or like something that happens all the time. Everybody knows I’m in an internal meeting, and somebody’s presenting a slide that was so poorly designed. And I don’t understand the graph at all, because the axes aren’t labeled, and I just take a picture, and I just give it to Chatgpd and say

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Nick “Mehtaphysical” Mehta: what is happening here. It gives me the full analysis, right? And so I think there’s these emerging use cases that over time become more mature. So there’s a flow. Right? Things start out new and novel, and November 30, th 2022, or whatever Chat Gpt came out, and it was super novel to be like.

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Nick “Mehtaphysical” Mehta: finish the sentence. And now it’s like, No, that’s like so easy, right? But it flows in as it matures it gets built into the existing products people have, I think people are going to constantly now be iterating, trying new things and then hoping they merge in. Now then, there’s the external side

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Nick “Mehtaphysical” Mehta: where more and more mature use case is. I’m gonna give my customer some more self service capability through AI self service chat, you know.

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Nick “Mehtaphysical” Mehta: instead of searching a documentation site, just ask a question like you would chat gpt stuff like that right? Gainsight makes some products there, and there’s another one out there and then the emerging customer facing use case meaning like you’re giving it to your customer. Is all the agentic workflows. So like, you know, we have our conference in 3 weeks. And

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Nick “Mehtaphysical” Mehta: we have this like genetic workflow around automating the entire process of driving a renewal for a company like the renewals like you have to like. Communicate with your customer and get some information and great great use case for an agent. And so we actually using

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Nick “Mehtaphysical” Mehta: Microsoft’s agent foundry. And we built this super awesome agent that does that. But those are emerging like that agent we have is an alpha. It’s not like a totally mature yet, but it’s real, you know. And so I think we’re gonna have that world where there’s always emerging technology. And it just will flow in over time into the mainstream products. But it’ll start out as these research projects. And that’s why you see, companies doing so many proofs of concept on these emerging technologies.

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Jason Napieralski: Yeah. So interesting question for you. You’ve seen these emails. See the recent one from Fiverr. You saw the one from Duolingo. You saw these CEO emails have you sent?

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Jason Napieralski: You sent a CEO email out like that? Yet?

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Nick “Mehtaphysical” Mehta: No, I think those are great like, they set the tone, and, you know, help people understand? I actually shared those emails. I was like, yeah, this is what’s happening. I think people just know it. Like, I say, it is slightly differently. I’m like, Look, I care a lot about your career long term. And it’s not just about gainsight. Long term. What I care about is, you know, you guys being employable way past gainsight makes me super happy when somebody gets a great job after working here. And the

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Nick “Mehtaphysical” Mehta: truth is, when people can judge whether it’s right or wrong, whatever it’s you’re not gonna be employable, like, literally, as a knowledge worker. You’ll be unemployable very soon.

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Nick “Mehtaphysical” Mehta: and I even have a friend who runs another company. Similar size gains. It’s a few 100 million revenue and friend is similar size company, and he’s like, when we do an engine. It was really interesting. They do an interview for engineers, and they have 2 interviews. One is, write some algorithm with, you can’t use AI, and they probably have some way to verify that or they trust them. And then the other one is, write an algorithm with AI,

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Nick “Mehtaphysical” Mehta: and if you don’t pass both tests, you can’t get a job.

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Nick “Mehtaphysical” Mehta: So if you don’t know how to use in the case of engineering cursor, or github, or whatever copilot. You will not be able to get a job at that company, and I think that. That’s why I tell our employees look, I care about it for gainsight. I want, you know we’re going to be successful. If you guys know how to use. AI. I care about even more for your future employability, and I don’t think it’s exaggeration at all. And in some ways it’s a self fulfilling prophecy. Companies start doing those memos, and they freeze headcount.

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Nick “Mehtaphysical” Mehta: And then they’re like only the best of the best. And then, like the people that are the quote best. The best are the ones who know you how to use. AI, it’s just a fundamental thing

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Nick “Mehtaphysical” Mehta: more as fundamental as knowing how to use email.

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Jason Napieralski: Right? Right? So you you also mentioned in the last what you just said there was some I really want to kind of dig on is you are releasing, or you’ve got some alpha stuff that’s coming right. Lots of it, I would imagine, because that’s what AI enables you to start prototypes and things really fast. So one of the problems that’s happening in the gaming industry is slop.

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Jason Napieralski: So all this AI generated slop coming out so like games after game after game, you know. You could see steam is just filling up with just slop, because people can vibe code whatever they want and throw it up there. Right? I really feel like that’s happening in AI right now. And I think Google is the biggest victor or biggest

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Jason Napieralski: person that’s doing this wrong in it. They’re releasing stuff every day. That is Pre Alpha, you know. So we used to write it back. You, you’re you went to computer Science school, and you remember it used to be, you know. Alpha, Beta, right, gold master release candidate. And then, you know, we we print the thing, and now it’s it’s pre pre Alpha! Just throw it out there. Put an ex post and and get somebody to say that they just vibe coded. You know the Declaration of Independence, or whatever

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Jason Napieralski: do you? I see this as a risk factor, at least especially for early adopters.

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Jason Napieralski: particularly in my world, where I’m working with companies that are working in real businesses is that they’re like, okay, they hear this. They’re scared to death, and they want to adopt AI as fast as they can, because they want to survive and they want to compete. But then they do with this half baked stuff, and it kind of hurts their mentality.

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Jason Napieralski: and they’re going to take a step back right now after the deep seek moment. Right? There’s been a very big, like exponential path of releases and everything. Now everyone’s kind of taking a step back here and looking at how this matters. How do you? How would you advise other Ceos that have been are getting burned on these things at this point. Just stay the course, keep going, keep trying new things. Wait until things are more baked before you implement it? Or what is your advice?

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Nick “Mehtaphysical” Mehta: I think such a good question, and I think it’s not an easy one, and probably why you have your consulting business helping people think about the nuances of the pros and cons. And I do think that, like we’re in a world where going too fast has risk and going too slow has risk, and they’re both significant. And so people are really having a hard time. So I think.

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Jason Napieralski: That’s always been the case. What? What is different now, Nick, like? It’s always been the case that going too fast and too slow are always bad, but what is now.

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Nick “Mehtaphysical” Mehta: Speed. It’s like the speed and the existential nature. And the you know again, all of us are have biases one way or the other, whether they believe this pace of change and all that. I think it’s just gonna continue to grow at a level that is unimaginable because the thing that’s happening is we’ve never had technology that can make technology and they can invent technology. And it will and it’s starting

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Nick “Mehtaphysical” Mehta: and and so we’re going to be in a world where we will truly have that level of you know I’m not saying Take off. And AI takes over humans or something I’m not talking about that. I’m just saying the level of innovation is going to grow insanely fast. However, I think that part of the brakes and accelerator thing is the nature of your industry.

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Nick “Mehtaphysical” Mehta: Is it an industry that is not suit is like very entrenched, not super competitive. And there’s a lot of regulatory risk and privacy, risk and other legal risk.

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Nick “Mehtaphysical” Mehta: Don’t go too fast, right like, what’s the benefit of going too fast, like I don’t want my

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Nick “Mehtaphysical” Mehta: Pg. And E, which is like the low power company in California. I don’t need them experimenting with using AI to run the power plant

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Nick “Mehtaphysical” Mehta: right like I don’t, don’t. We don’t need that right? But if you’re in a highly competitive industry, which, by the way, interesting enough, all tech companies are, you have to, because the other company is going to, and you are going to absolutely be beaten out if you’re not constantly accelerating. And so I think the thing and what happens is in highly competitive industries. There’s less risk

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Nick “Mehtaphysical” Mehta: because the risk is much more you go out of business than it is. You get sued, whereas at Jp. Morgan, or Pg. And E. Or Pfizer. The risk is much more you get sued or you get whatever worse than it is, you go out of business. Pfizer is not going out of business tomorrow, you know, but honestly, like a lot of software companies, a lot of knowledge oriented companies can go out of business the next 5 years if they don’t move fast. And so I think part of it’s the nature now. But I think the other thing you said Jason, is so important

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Nick “Mehtaphysical” Mehta: as individuals. You’re right. Some people try these things like, Oh, this is not made ready for prime time, and then it’s like sets them back. And I think that’s a different thing, which is a human mindset shift, which is basically we are in a permanent beta because we are using. I think most people know non-deterministic technology, at least at a level of

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Nick “Mehtaphysical” Mehta: the way we look at under the covers. It’s still deterministic. But it’s like there’s no way for us to understand that determinism they call that computationally irreducible like we can’t understand how it works. And so, therefore it’s always going to be weird and always going to make mistakes. By the way, humans do, too. We don’t always say that, but it’s true.

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Nick “Mehtaphysical” Mehta: And so we are going to be in a world forever where there’s going to be a bleeding edge. And it’s going to be a weird, bleeding edge. And it’s gonna have lots of problems. And I tell our employees, if you, you know, if you’re in these dynamic industries, or if you want to manage your own individual career, you should constantly be frustrated by that.

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Nick “Mehtaphysical” Mehta: So the other. Yesterday I 2 things happen. 2 things happened, and like within our course, I I was like, let me give deep research as a feature, as you know very well, of multiple alums, and it lets you go run a research task that’s not like an instant response. It’s a batch. It’ll go around the web and stuff. And I ran a decent. We were in a slack thread about what’s the addressable market for some new thing we’re building, and they’re like we should look at Gartner or Forrester. And I just like said, do deep research and figure this out and got us an answer like

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Nick “Mehtaphysical” Mehta: 10 min right? And that was magic. But then, like later on, in an hour later, I do presentation for a company. We had a great 1st quarter. And I wanted, like a little graphic of all the awesome things that happened.

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Nick “Mehtaphysical” Mehta: And although image generation in chat, TV is better, it’s still, text rendering is really annoying, and I was like, this is so annoying, but you know what.

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Jason Napieralski: So annoying. I’m so worst.

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Nick “Mehtaphysical” Mehta: A month from now, or 2 months from now. I’m gonna try it again.

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Nick “Mehtaphysical” Mehta: and or maybe a week from now. And I think that’s a subtle thing. Sometimes, like historically, people be like, Oh, this isn’t ready for time. Time. I’m not gonna try it. It’s like, No, I’m gonna keep trying. And so if I give people advice, it’d be like, keep trying it. And if you’re not frustrated, you’re not trying it enough.

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Nick “Mehtaphysical” Mehta: And that’s a hard change. Humans aren’t used to that.

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Jason Napieralski: Yeah, it is. And my, and you mentioned mindset a couple of times, and I think that that’s something that’s being left on the on the floor right now is that that the mindset of the leadership needs to have a much more open view of what possible, what the possibilities are, and that that’s when I spend my time with the Ceos. That’s I spend a lot of time with that alone before we even start digging into what the AI is of being open to being, to be getting things wrong and to making mistakes and experimenting, and that’s what it lets you do.

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Nick “Mehtaphysical” Mehta: And that’s a good point. You asked something I didn’t answer, which is the personal skill set of employees, and I think that comes back to this, like.

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Nick “Mehtaphysical” Mehta: you know, part of it is insane curiosity like you should. The people that can be successful are the people that are going to want to try things not actually for any reason other than they’re interested. And, by the way, this is definitely the most interesting time like humans have ever had like, it’s just so crazy.

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Nick “Mehtaphysical” Mehta: And so you’re like, constantly like yesterday, I mean, love it. This shows you how much of a problem I have, and I’m too obsessed. It’s like 1130 Am. 1130 at night. I’m like coming back from the vet because my dog got things fine now, and I’m like in the drive through, because I need dinner yet, and I’m asking chat, gpt voice, mode.

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Nick “Mehtaphysical” Mehta: My side hustle is trying to. I love science and physics and stuff. I’m like, what would Immanuel Kant have thought of

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Nick “Mehtaphysical” Mehta: quantum physics? And I had like a 20 min conversation about it right now I tell you that story partially, because that’s a ridiculous example of how nerdy I am. But like also it’s just curiosity. It’s like, Oh, that’s cool. Let me ask like, can it do? By the way, it’s really good at things like that? And I’m like, Can I? Can it do it, you know, try things like, try constantly trying new things. People aren’t used to that curiosity. And then the other one, I think, ties to the frustration point, which is great where it’s like, okay, I’m going to keep trying.

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Nick “Mehtaphysical” Mehta: And it didn’t work. But I’m gonna try again. Tomorrow. I’m gonna try again the next day. I think those 2 skills which have always been important. They’re becoming vital.

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Jason Napieralski: Yeah. So let’s bring it back to customer service a little bit. Because this is this is a burning question that I have. So your brand, and many other brands are very at least publicly, very human focused, you know. You want to bring the human back into the interaction. You want to make sure the human is super powered. You want to have

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Jason Napieralski: a human involved, and that’s been kind of the way you’ve gone forward. But given our our path here, and having inevitably AI. Agents, are going to be more involved in the customer service stream. How do you square that circle of having this brand of being, you know, the best human thing versus, you know, delivering AI in the way that companies need it.

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Nick “Mehtaphysical” Mehta: Yeah, I think I think that’s a really good question. I don’t think we all fully understand the answer yet, but I think there’s a couple of things. 1 1 is like, what is AI, not yet fully great, at which is like it’s human relationship building, right? It’s not great, it’s not. And it’s even unclear. What that even would mean, like an AI is building relationship with you. But then, then, on the other end, should it just be an AI, too, is AI building relationship with another AI. That stuff like is still pretty science fiction, right?

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Jason Napieralski: South Korea has entire generations of women that have AI boyfriends.

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Nick “Mehtaphysical” Mehta: Well, that is, that is the companion thing which is obviously not business topic is, there’s no doubt about that. And but in a business relationship context. If you’re in sales or customer success or something like that, you still have a lot of value, because that’s the thing people really want. And I’d argue

882
02:21:56.040 –> 02:22:16.790
Nick “Mehtaphysical” Mehta: they may want it more, because the everything else being digital will create like it almost feels so good. It’s kind of like. When we had when Covid was in the thick of it, and it was like you get to have your 1st in person, like meeting or coffee, or whatever it’s like, Oh, my God, this is so great, right? And we’re gonna have some feeling like these, human interactions are gonna be really valuable.

883
02:22:16.790 –> 02:22:38.709
Nick “Mehtaphysical” Mehta: And one of the things that prevents the human interactions. And us having that time is that we do a lot of rote stuff, you know, updating data, you know, sending information out blah blah. And so the more we make that self service, or automated or AI driven the better. Now, what’s interesting is, people have tried to do this for a long time. Pre AI! Right like, we all know

884
02:22:38.710 –> 02:22:51.669
Nick “Mehtaphysical” Mehta: you go to. You call some customer service thing you have like an 800 number, and it’s like 7 h before you talk to human right? Or you go to a website. And it’s like, Hey, you try to get the phone number. It’s like, no, we want you to navigate this Byzantine.

885
02:22:51.670 –> 02:22:53.600
Nick “Mehtaphysical” Mehta: FAQ thing first, st right?

886
02:22:53.600 –> 02:22:55.780
Jason Napieralski: Right. I love entering my information 27 times.

887
02:22:55.780 –> 02:22:57.110
Jason Napieralski: That’s the best desk.

888
02:22:57.110 –> 02:22:57.860
Nick “Mehtaphysical” Mehta: That’s the best part.

889
02:22:57.860 –> 02:22:58.290
Jason Napieralski: But yeah.

890
02:22:58.290 –> 02:23:07.749
Nick “Mehtaphysical” Mehta: It’s so fun. And and we created these self service technologies, Ivrs, websites, whatever. And they suck pre AI.

891
02:23:07.930 –> 02:23:34.649
Nick “Mehtaphysical” Mehta: But what’s interesting is they can get quite good post. AI. We have to be careful and thoughtful, because again, like just like you said with employees, if you put too much out there, and it doesn’t really work well. The customer then gets cynical about it, and then they don’t use anymore. So we have to pick our shots even more, I think, for customers. You have to be a little more careful than with employees, because employees are a little more resilient to try things. And so there, though you can say you know what these chat these use cases can be done through a chat.

892
02:23:34.690 –> 02:23:41.139
Nick “Mehtaphysical” Mehta: these ones can’t. I was talking to one of the vendors that, like the CEO of a vendor that makes one of the big ones for like support software.

893
02:23:41.480 –> 02:23:56.540
Nick “Mehtaphysical” Mehta: And he’s like, Look honestly, if you’re a B to C customer A, BC vendor. And you’re trying to like you know. Update your subscription for your like, you know, clothing, subscription, or whatever support through AI works really? Well.

894
02:23:56.966 –> 02:24:14.470
Nick “Mehtaphysical” Mehta: For those basic things. Update my password, update my credit card information. Where’s my shipment? And he’s like they get 80%. AI resolution rate, meaning AI can solve 80%. But he’s like, when you go to b 2 b like a company sell another company. These things are complex, and he’s like 20% is good.

895
02:24:14.790 –> 02:24:41.589
Nick “Mehtaphysical” Mehta: And so what that means is don’t like force your customers into the 20%. And like, even if it’s not a fit like. Give them that optionality. Let them get to a human quickly things like that. And so I think that’s the thing. Be careful. The human part of this still matters a lot to the customer, and is still really important in b 2 b, because the situations are pretty complicated. AI can assist. It’s still not ready fully to do everything.

896
02:24:42.140 –> 02:24:57.739
Jason Napieralski: Yeah, that’s a really good point. I think that there’s 2 unforgivable sins that I see right now in AI implementation for customer service. The 1st one is slapping on an Llm. Bot onto your web page and having the Llm. Bot have no idea what it’s what web Page is on, or what.

897
02:24:57.740 –> 02:25:00.160
Nick “Mehtaphysical” Mehta: Oh, dude, that’s the worst. Yeah, I see that.

898
02:25:00.450 –> 02:25:14.969
Jason Napieralski: That’s the first, st and if anybody’s done that, fix that now like, run a notebook, put all your data in there, make sure that the Llm. Understands your business, but the second one you mentioned it, and I think is, is not done well, and I think there’s a lot of room for improvement is is the handoff.

899
02:25:15.010 –> 02:25:37.589
Jason Napieralski: And so, you know, early and often don’t let the customer get frustrated and start swearing at that chat bot before you hand it off to an agent. And then the other thing that I think happens is is hand it off to somebody that can that is empowered to fix and and improve things, or make a sale, or make an appointment, or whatever don’t set, don’t hand it off to the lowest common denominator. Rep. If you do have a handoff from AI.

900
02:25:37.590 –> 02:25:40.960
Nick “Mehtaphysical” Mehta: I love that. That’s a great idea. Yeah, that’s that’s awesome.

901
02:25:41.080 –> 02:25:41.570
Nick “Mehtaphysical” Mehta: I.

902
02:25:41.570 –> 02:25:42.010
Jason Napieralski: So we’re.

903
02:25:42.010 –> 02:26:06.390
Nick “Mehtaphysical” Mehta: Oh, go ahead, I said, one other comment that’s related, and I’m not trying to make a commercial for you, Jason, but I will say, like this is the biggest human change management exercise ever. And so I think for companies, what’s going to be interesting is the technology matters like, you know games. That is all this AI technology. You can buy developer AI technology for Microsoft or Slash Github or cursor, or whatever. But

904
02:26:06.470 –> 02:26:22.970
Nick “Mehtaphysical” Mehta: changing people’s behavior takes like human change management. Consulting all these things, probably what you’re helping your clients with. I just take developers an example. The Roi of developers using AI is off the charts. And yet you got a lot of organizations where they’ve given licenses to everyone.

905
02:26:22.970 –> 02:26:41.319
Nick “Mehtaphysical” Mehta: and you have like 2030% meaningful use. I don’t mean like they use it every now and then. I’m like truly using it. And the other people, it’s like you’re not going to get there just by like giving them access. You need change management strategy. Like, it’s weird because I think consulting in this area is going to be really important.

906
02:26:41.500 –> 02:27:02.509
Jason Napieralski: Yeah. And thanks, for I do appreciate the commercial Nick. But one of the things that I kind of Trojan horse in my engagements is one is, I get people interested with the AI because they have to do that. That’s an absolute burning pain, right? But this, this the second thing. And we talked about it already is almost as important, or equally, or maybe more important is fix the mindset.

907
02:27:02.510 –> 02:27:12.509
Jason Napieralski: Think about this, you know. Think about how you’re how you’re approaching it. But the 3rd one and this is something I learned very well from Amazon and have kept it through is that you need to

908
02:27:12.510 –> 02:27:25.559
Jason Napieralski: make sure your culture is designed to be able to handle this. So to be able to handle the change management needs to have a culture, a core team a singular mission. And you know, the bullshit needs to stop. Now.

909
02:27:26.770 –> 02:27:47.900
Jason Napieralski: we’re getting real. And I think that that’s an important thing that I think a lot of companies, particularly ones that haven’t really paid any attention to culture like real companies. They’re like, wait a minute. We don’t have the right culture to be able to take this next path. So that’s that’s equally as important. So all 3 of those things work together to get this going. But it’s all so so fresh.

910
02:27:48.690 –> 02:27:53.169
Nick “Mehtaphysical” Mehta: I love it. That’s awesome, so good to connect with you. Thank you for having me in this. In this event.

911
02:27:53.440 –> 02:27:54.760
Jason Napieralski: Yeah, thank you. Julia.

912
02:27:54.940 –> 02:28:03.360
Julia Nimchinski: Thank you so much, Jason, and thank you so much, Nick, and let’s just make it a little bit more commercial for 1 min, and Nick went to conference.

913
02:28:03.520 –> 02:28:05.590
Julia Nimchinski: Where should our people go?

914
02:28:05.900 –> 02:28:23.419
Nick “Mehtaphysical” Mehta: Yeah, totally. So we have a conference called Pulse, which is the conference for kind of everything customer related in Sas. I know many of your Sas companies. That’s May 27, th 28th in Vegas. So it will also be fun. It’s also all game side events, are we? That’s our thing is making fun. So it’s a

915
02:28:23.420 –> 02:28:41.649
Nick “Mehtaphysical” Mehta: themed around wicked the movie. So I will. Certainly I would be the wizard on stage. But you know it’s very logical, tied AI the whole events about using it’s everything Jason just asked about in every use case all the tracks are using AI for scale and automation with a whole bunch of stuff we’re showing, releasing this agentic approach to some of the workflows and

916
02:28:41.650 –> 02:28:46.306
Nick “Mehtaphysical” Mehta: all these other AI Oriented products. So yeah, may 27, th 28.th If you just Google

917
02:28:47.076 –> 02:28:51.960
Nick “Mehtaphysical” Mehta: or chat Gpt gainsight pulse, you will see the Conference registration online.

918
02:28:53.390 –> 02:28:53.919
Julia Nimchinski: Thank you again.

919
02:28:53.920 –> 02:28:54.929
Jason Napieralski: Good to meet you, Nick.

920
02:28:54.930 –> 02:28:56.529
Nick “Mehtaphysical” Mehta: Thanks so much. Bye.