Ep 263: Securing Your Business Future with AI

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Bridging the AI Gap: Harnessing Artificial Intelligence to Transform Your Business Future

As the business world continues to evolve, the pressure to integrate Artificial Intelligence (AI) into business strategies and operations is growing. Parallels can be drawn to the dot-com boom where companies faced a similar pressure to go digital or risk being left behind. Taking a proactive approach to integrate AI into business transformation strategies can be a significant game changer. However, discerning the practical and achievable AI solutions is key.

Navigating the AI Journey

Feeling the need to adopt AI or fear of missing out (FOMO) is not uncommon among businesses, especially with the rapid advancements in AI technologies. The key to success lies in making informed decisions, and not just betting on the latest trend. AI should not be seen as a one-fits-all solution. Instead, businesses should focus on customization and domain-specific training to increase AI’s effectiveness and adaptability to specific needs.

Protecting Jobs and Economic Implications

AI, like any technological advancement, has its ethical considerations. The debate on job protection varies across different economic systems. Finding a balance between protecting the vulnerable and shareholder interests is paramount. With job redundancies being an unfortunate reality of business sustainability, strategies such as the Universal Basic Income (UBI) could potentially address short-term disruptions.

Embracing the AI Gold-Rush

Ironically, the rush to secure a foothold in AI is reminiscent of the gold rush. Large corporations are pushing aggressively to gather data and build smarter AI systems. However, this approach has seen resistance, leading to bans on certain AI technologies and even the development of restricted proprietary AI.

Investing in Ethical AI

As companies ramp up investment in AI, it is critical to maintain a balance, especially amid external pressure to reduce staff for higher share prices. Despite the reported low return on investments (ROI) from AI initiatives, there has been success with specific-purpose AI enhancing business processes. Herein lies the need for ethical AI deployment, keeping in mind positive ROI and jobs.

Employment and AI: Adapting to Change

Despite fears of job losses due to AI, it is not all doom and gloom. AI is likely to spur the evolution of jobs, with new opportunities emerging for human supervision and AI training in specific domains. While some roles may become obsolete, others will take shape, requiring a shift in skill set. Ultimately, it’s about humans and AI working in tandem for greater productivity and innovation.

AI’s Limitations and the Road Ahead

AI isn’t without its limitations. There are significant hurdles currently impeding the road to true Artificial General Intelligence (AGI) including lack of ‘DNA memory,’ challenges with information not available online, and issues related to societal acceptance. Additionally, AI systems need to better handle the ingestion of video content and the deciphering of information from video transcripts.

In conclusion, securing your business future with AI requires a calculated and ethical approach, focusing not just on AI integration but also keeping a close eye on its impact on jobs and the economy. As the saying goes, pick the right battles and walk that AI journey wisely. With the right guidance, AI can propel your business into a promising future.

Topics Covered in This Episode

1. Pressure to Adopt AI in Businesses
2. Coping with Uncertain AI Environments
3. AI’s Ethical Implications and Perspective on Job Protections
4. Balance and Ethical Consequences of AI Deployment
5. Future Shifts in Job Roles

Podcast Transcript

Jordan Wilson [00:00:16]:
There’s so many uncertainties in today’s day and age with AI. I would actually say one of the few certainties is we don’t know what’s coming next, How the, you you know, the next large language model or the next version of the next big AI, how it’s going to impact, our businesses and our careers. And although we don’t have all of the answers, one thing we do here at Everyday AI is we bring on very smart people who can help us understand what’s next. So that’s what we’re gonna be doing today is talking about how you can secure your business future with AI. I’m excited for today’s conversation, y’all. Thanks for joining us. If you’re new here, my name’s Jordan. I’m the host of Everyday AI.

Jordan Wilson [00:00:59]:
We’re a daily livestream podcast and free daily newsletter, helping everyday people like you and me not just learn AI, but how we can all leverage generative AI to grow our companies and to grow our careers. So thank you all for joining us. And if you haven’t already, make sure you check out your show notes. So go to, and also go to your everydayai.com and sign up for our free daily newsletter where we will be recapping today’s conversation. Alright. Before we get into the topic and we talk about, yeah, what is how can you secure your business future with AI, let’s go over the AI news for today. So first, ad funded AI chatbots for news are going to soon be a reality. So Axel Springer and Microsoft have just announced a partnership to develop AI based chat experiences, advertising technologies, and cloud services.

Jordan Wilson [00:01:49]:
So this collaboration will advance Axel Springer’s AI activities and potentially change the way that people consume content online. Hey. I hope you guys still show up here even after this. And if you don’t know, Axel Springer is a very prominent digital publishing company based in Germany known for its various brands and publications. So this new partnership will focus on developing AI offerings and chat experiences to better engage users with Alex Springer’s journalistic content. The chat service will be monetized through advertising using Microsoft’s advertising chat ads API. Also, this partnership reflects this growing trend of major tech firms signing deals with media companies. Talked about that with OpenAI in the Financial Times the other day to distribute their news and license training data for AI systems.

Jordan Wilson [00:02:32]:
I think these big companies are trying to get ahead of the inevitable lawsuits that are gonna be coming. Alright. Next piece of AI news. The US government officially doesn’t want AI starting a war. It’s good to know. Right? So a senior US official has urged China and Russia to declare that only humans and not artificial intelligence should make decisions on deploying nuclear weapons. The US has made a strong commitment to human control over nuclear weapons and believes China and Russia should do the same. There’s been recent discussions between the US and China on nuclear weapons policy and artificial intelligence, kind of first talks in a while.

Jordan Wilson [00:03:09]:
China has called for a no first use treaty to be negotiated between the major nuclear powers. However, right now, there’s been no immediate response from the Chinese defense ministry, ministry, to this new US official statement. Alright. Our last piece of AI news for the day, Sam Altman, has shared some of OpenAI’s future plans in an exclusive interview and a panel yesterday. So Sam Altman, the CEO of OpenAI, shared his vision for AI tools becoming more integrated into daily life, potentially surpassing smartphones and usefulness. Yeah. I think that’s a safe bet there. So a couple key takeaways.

Jordan Wilson [00:03:44]:
Altman envisions AI as a super competent colleague that knows everything about our lives and can perform tasks for us. He also said that he believes the future, AI may not require new hardware, but new device would be super beneficial. And as you know, OpenAI is facing a lot of challenges in finding enough training data for their models, but Altman remains hopeful that a solution will be found. In an unrelated panel discussion at Stanford, Altman said some things like, you know, hey. GPT 4 now is the dumbest, model. He said, you know, that that we’ll ever use. He kind of said it was embarrassing, but also something I picked out is he said that they may just burn up to $50,000,000,000 a year building AI and but he said it or building AGI, artificial general intelligence, but he said doing that would be worth it. So an interesting, some interesting takes there from OpenAI CEO about the future of AI.

Jordan Wilson [00:04:36]:
And speaking of that, that is today’s conversation. So, what what do we need to know about securing your business future with AI? I think it’s an important discussion and don’t worry, you’re not just gonna listen to me, mumble on. So let’s go ahead and bring on our guest today. I am super excited to have on the show, Luv Tulsidas, who is the founder and CEO of Techolution. Love, thank you so much for joining the Everyday AI Show.

Luv Tulsidas [00:05:02]:
Hey, Jordan. Good morning. Thanks for having me on.

Jordan Wilson [00:05:04]:
I’m excited for today’s conversation. And, hey, if you’re joining us on the podcast, I just have to point out love has one of the coolest setups and backgrounds. Just saying. You know, but, hey, Luv. Can you tell us a little bit about what you do and a little bit about Techolution?

Luv Tulsidas [00:05:19]:
Yeah. Techolution is a company that I founded back in 2015. We’ve been doing digital transformation, whatever that means. That definition changes over time until last year where we went all in on AI. So what we do now, we build custom AI solutions for our clients, mostly enterprises, mid to large enterprises, and some selective startups that we decide to work with. So customers, come to us with ideas, business problems. So we take that idea and turn it into AI and robotic solutions that’s generating ROI, in in the real world. So with that said, you know, I know you also run a consulting AI consulting company.

Luv Tulsidas [00:06:04]:
So you’re actually in the frontline working in the real world with customers like we are. And I can tell you, I don’t see AGI anywhere close. You know? I think AI is in its infancy right now just like the Internet and computers were back in 2000. It’s exciting, especially being in, the space that we’re in. But I’m gonna challenge Sam Altman and say AGI is not gonna be, in at least our lifetime. Next year, I could sit here. You could make fun of me for being wrong, but, at least that’s what I see right now.

Jordan Wilson [00:06:39]:
Oh, man. I love it. So I I already have so many follow-up questions on this, but, you know, hey. To our to our livestream audience, thank you for joining us. If you do have questions, here for love, you know, make sure to get them in now because I can already tell today’s conversation is is going to be a great one. We already have hot takes. I love it. But but, love, you know, one thing that you just said there is you kind of, your your company who’s, you know, a very, very large company and working, with a lot of clients made this, kind of decision recently to to focus more on AI.

Jordan Wilson [00:07:10]:
I’m curious, what led to that decision? And, you know, looking back at it now, you know, I I’m sure it wasn’t an easy decision, but, are you happy that you made kind of that shift to, you know, really focus most mostly on AI?

Luv Tulsidas [00:07:25]:
So, I’m extremely happy I made the shift early on. Fortunately, I grew up with a passion for AI, and my passion, for AI was well before I even knew what it meant. Remember Knight Rider? Did you watch that as a kid with Michael Knight? For most people, he was the role model. For me, it was Kit. I love Kit, and I always wanted to build Kit. But, anyway, so back in 2015, you couldn’t really make money building an AI company. You get little sprinkles from innovation departments, and you can really, do what I was trying to do. Right? So we went with what we knew, cloud, building apps, modernization for enterprise, and all that good stuff.

Luv Tulsidas [00:08:08]:
But, towards the tail end of 2022, even before OpenAI was as hot as it was, I could see that digital transformation was saturating. And as you know, in tech, we have to innovate every few years. That’s why I called, the tagline for my company is called innovation and innovation changes over time. So we went deep. We were investing. And if we didn’t do that in 2023, we’d be in big trouble right now, like we were during the early days of COVID because, everybody’s budget, every enterprise now is not talking about, hey, moving to the cloud or modernizing this app. Everybody’s like, what are we doing with AI? Let’s go. We have middle managers we talk to who are like, hey.

Luv Tulsidas [00:08:54]:
I don’t know what to do with AI, but the board is telling my CEO that we have to do something with AI because everybody feels I don’t know about you. I feel like I’m old enough to remember 1999 and 2000. That’s when I was starting my career. Right now, it feels just like that when the Internet and computers was coming for the world, and, that’s where we are with AI. And I’m excited. I’m excited. If I hadn’t made that transformation, which, by the way, I followed, the ten secrets that I was writing in my book. I was wrapping up my book last year, and I found myself having to put it in practice to transform my company just to survive.

Luv Tulsidas [00:09:32]:
And we’re in the tech business. Right? Now let me tell you another little story that’s interesting. Are you from a tech background or you’re in an engineer or what what’s your what’s your

Jordan Wilson [00:09:42]:
I would say tech ish. Right? So so not traditional tech, but I’ve worked around technology, you know, for the last, you know, 10 years.

Luv Tulsidas [00:09:49]:
See uh-uh I’m a tech bro. We learn how to do business so I love engineering writing code even though I haven’t done that for for a few years now And, just literally last year, we built a tool that wrote a very old code in c basic for a big customer of ours. We wrote it in Python and figured out what the C basic experts could not figure out, wrote the unit test case, built the UI, and deployed it, and I was like, damn. If you think you’re gonna make 6 figures programming, man, think again. So now I tell nieces and nephews, don’t look at me and go, just jump into a comm sci program. Now there’s a place for comm sci majors, but I think the people who just came in for the money learn programming. I mean, it’s already a difficult market, right, since big tech have been laying laying off, and AI has not even kicked in yet. So things are about to change in a big way.

Jordan Wilson [00:10:49]:
You know, and, gosh, so many things again, love. Like, I feel I should just be, you know, peppering you hot seat 32nd questions, but, you know, one thing that you that you said there that’s, you know, really, really interesting to me is all of these companies are are kind of looking at each other. You know, the CEO with the board member, you know, probably high ranking employees. Everyone’s saying, like, we need AI. We like, we know we need it, but what’s next? How like, how to do it? So I’m curious with with with the clients that you’re working with, the companies that you’re talking to, are they more excited about leveraging generative AI? Are they more confused? What would you say in general is is kind of the pulse of these companies that are, you know, coming to you and just being like, love. Like, we need AI. Like, how like, kind of encapsulates, you know, the the feelings of the business world, at least those coming to you right now.

Luv Tulsidas [00:11:39]:
So I think it’s a good combination of FOMO, because they know all the companies, the big companies, Kodak and Blockbuster, that got disrupted. And so between FOMO and also having a business need, because, you know, we have a major labor shortage in this country, especially in midscale jobs. Right? And we also have major inflation. So a lot of customers are coming from a place of hurting, suffering, having to answer to their shareholders. And, also, with the mid managers don’t know what to do. Right? Like, how do we get started? What’s possible? What’s not possible? Because they know it. Not everything’s possible. Right? There’s a lot of vaporware out there.

Luv Tulsidas [00:12:22]:
Right? But I I actually watch one of your guests say, hey. OpenAI’s new store sounds great. There’s a lot of excitement, but how much valuable stuff is on there? I actually saw that video yesterday. And and it’s true. There’s a lot of that going on, but there’s a lot of, real stuff also happening. So I think the the big secret that everybody’s trying to figure out right now is what are bets that are not worth taking unless you’re big tech. You could keep going with 1,000,000,000 of dollars for a decade. What’s practical? What’s achievable? And there’s, there there’s a little bit of both.

Luv Tulsidas [00:12:58]:
And those who figure out the truth make the right bets, I think are the ones who are gonna win. And that’s what everybody is after right now. Yeah.

Jordan Wilson [00:13:05]:
Yeah. So, I mean, let’s let’s just skip let’s just skip to the answers then, you know, and and we’ll we’ll circle circle our way back around. So, you know, for those companies that are very feel, you know, feel uncertain about, you know, their their their future business. They feel uncertain about, you know, where this technology is heading. How can they secure their future with AI? What what are you telling companies right now who are coming to uncertainty?

Luv Tulsidas [00:13:30]:
Yeah. I’m gonna say something that might be controversial, especially if you have, listeners from big tech. So, a lot of Big Tech would want you to believe that their large neural network models, whether it be an LLM or in computer vision robotics, will, work out of the box, will fix their problems out of the box. If that were true, then I wouldn’t have a business today. You probably wouldn’t have a business. You just turn it on and go. Right? The truth is that, it doesn’t work like that. There’s a lot of customization that needs to happen.

Luv Tulsidas [00:14:03]:
Now a lot of projects from the beginning, if someone knows what’s possible, could tell you this is a long shot. It’s not gonna work. But these things are very possible. Right? Like, right now, Jenny I is a lot more possible than some other AIs that you might see. That’s why it’s very, very possible. But out of the box, right, can you just turn on ChatChipt and have it do customer service for your business? Probably not, and you might be afraid about what it’s gonna say. So companies wanna still keep control. And I will say something about Jenny I, what I’ve noticed.

Luv Tulsidas [00:14:35]:
What most companies want, they want the conversational power and the reasoning power of LLM, but they don’t want their knowledge and their opinions. They want it to know about their business, whether it be sales, your product, your services, and all the depth of that. And they want it speaking their brand tone, not someone in in in San Francisco who set the brand tone of of of the LLM. So how you take it from that to this? And it’s not binary. I equate it to this way. Right? If you’re trying to and mostly AI today today’s AI, what we’re trying to solve today, the AI is different from the AI that’s, been applied in, companies for more than a decade now. The previous version, machine learning and data scientists, were mostly hired to do advanced analytics, to look at the past and forecast the future, and do that as accurately as possible. And this is not something that humans have ever been good at.

Luv Tulsidas [00:15:33]:
We weren’t born to do that. Right? But today, it’s kind of a, it’s trying to automate, things that humans have been the only ones that are able to do it. Because if computers were able to do it, I guarantee you there’d be a software or a robot doing it already, and that’s been the challenge. But now AI is getting closer to being able to do that. But the approach, you’re trying to teach it a human skill. Right? But you’re trying to teach it, not the way that humans learn. So how do we learn a skill? Like, if I wanna be a heart surgeon, I wanna be even a plumber. Maybe I go to school.

Luv Tulsidas [00:16:08]:
I learn from the literature. I do some lab projects. And do I just go out there and do surgery on people? No. I apprentice under an expert in the real world, and that’s where I learn things that don’t exist in the lab literature and on the Internet that I can only learn from that expert. And that’s the gap in AI today, and that’s the gap that we are working on filling. So you don’t wanna go start your own school. You don’t wanna go train your large neural network model for the most part, unless you’re big tech and you can afford it. So you hire a college grad, which is a large neural network that big tech has built, and then you apprentice it under your domain experts, and you wanna keep control of that.

Luv Tulsidas [00:16:48]:
So it’s not like, hey. Get rid of the humans. Bring in the the the chat CPT, and it’s gonna take over at that approach, doesn’t work. But for some reason, there are many people who want you to believe that’s how it’s gonna work. But being in the field, I know you do this too. That’s not how it’s working.

Jordan Wilson [00:17:06]:
Yeah. And you know, on on that topic and, you know, for for for our live audience, don’t worry. I’m gonna get into AGI. I I see a question or 2 here about it already, but do you see then, the future, you know, and I know there’s always fringe cases and every company is different. Right? You gotta throw those, disclaimers out there. But do you see many human jobs in the near future almost as apprentice, you know, apprentices of AI. So whether that’s, you know, humans overseeing, you know, customized personalized agents or just, you know, humans kind of training, you know, different AIs on their specific vertical, their, you know, domain expertise? Is that where we might see a lot of human jobs in the future?

Luv Tulsidas [00:17:46]:
Alright. I’m gonna bear with me. I’m gonna answer that in a in a roundabout way. So I, you know, started a tech company doing innovation. I have a family, wife, kids. Those are very difficult things to do in life, and I’ve done very difficult things. But I spent 3 years writing this book, and this is the most difficult thing that I’ve done. As an engineer trying to be a writer and trying to be as accurate as possible, it’s called the 10 Secrets to Succeed Faster Innovation.

Luv Tulsidas [00:18:14]:
When I was done with this book, I said amazing. It really upped my game in communication and writing, but I will never write a book again. And then I find myself in the spot with AI where actually I don’t even feel as bad for the enterprise leaders. They’ll figure it out right, but it’s the students, the kids that are graduating high school and they’re being told go learn programming even if you hate it, go learn it. There’s money And I’m like, no. No. No. No.

Luv Tulsidas [00:18:40]:
Wait a second. You you can’t see what I’m seeing. I could see what AI is writing. It’s writing code better than any average or below average programmers there. There are many of them out there. I could tell you this. Right? So I decided to write a second book. So what I’m about to re tell you is literally what we’re gonna talk about in the next book that we’ll be releasing later this year.

Luv Tulsidas [00:19:00]:
I think it’s so important. A lot of people wanna know, is my future secure with a AI, and how do I secure it? So the answer to your question is, yes, there will be a lot of disruption. I could tell you any programmers, writers, a lot of these white collar jobs, that where especially people are average or below average, and ChatGPT or Gemini or any AI can do better, those jobs are gonna be disrupted. No question about it. Right? Especially if people are overpaid, for sure. Now, yes, there will be a disruptive pair just like we’ve had with every major technological revolution from the steam engine to the Internet, and then new jobs will emerge. What you’re doing today is not a job that existed 20 years ago. Right? So I’m I I truly believe new jobs will emerge, but, I think there’s still a role for programmers, people who are problem solvers, people who can go out and meet with customers and figure out what problems they have to then partner with the AI to solve those problems.

Luv Tulsidas [00:20:02]:
I don’t think AI is gonna be able to do that and I don’t think anybody will accept some Sam Altman’s AGI. Imagine an AI comes to your office and start asking you questions. You’re gonna wanna talk to it, at least maybe in Japan, because, you know, they love animes and stuff like that. But I think in America and most, western countries, we’re not gonna accept anything that makes us feel threatened by it. That’s just how we are, you know.

Jordan Wilson [00:20:28]:
Well, let’s let’s just get there right now. So, you know, and and, you know, just if you’re listening on the podcast, don’t worry. We’ll we’ll throw in a link in today’s newsletter, for Love’s books. So you can check that out if if you want. So, Woozy here with a great question. So thanks for this, Woozy. And anyone else on the live stream, get your questions in now. But, you know, speaking of AGI, artificial general intelligence, I mean, we’ve heard, you know, Sam Altman and, you know, Meta, you know, so so so the biggest companies, that that that are $1,000,000,000,000, you know, $1,000,000,000,000 companies, they’re all working openly, toward AGI.

Jordan Wilson [00:21:02]:
So so woozy here asking, what’s the big the biggest obstacle blocking AGI in your opinion?

Luv Tulsidas [00:21:10]:
Yeah. So okay. So, think about how now we all agree today’s AI is trying to learn human skills. Right? The math, the the calculation, all the memorization, the things we weren’t good at, software, traditional software has been doing that for a while. Right? So today’s AI is trying to learn human skills and do it as good first and then maybe, hopefully, better someday. Now think about how long we took as a human species to get to this level of intelligence and capability. Right? So the biggest problem with AI today, it doesn’t have DNA memory. Right? So if you have LLM, it knows about this information, but it doesn’t know about, computer vision yet.

Luv Tulsidas [00:21:53]:
Maybe it’s learning. Right? And it doesn’t know about a lot of history, and it doesn’t know about things that are in the real world that’s not on the Internet. Because AI can only today, AI can only learn things that is in a database or on the Internet that’s been documented. It cannot learn all the things that as human, we know how to pick up. We know how to explore, how to be good journalists, good investigators, and go figure it out. And AI is not able to do that, and I think there’s gonna be a lot of challenges. First of all, as you know, we have a bottleneck right now for GPUs in the world. Right? Let’s just start with that.

Luv Tulsidas [00:22:32]:
Right? So the infrastructure is not ready for the level of AI that you need to do AGI. Secondly, you’re gonna need a lot of maturity. And remember Elon Musk’s, Neuralink project?

Jordan Wilson [00:22:44]:
Mhmm.

Luv Tulsidas [00:22:45]:
Right? That was attempting to give AI, this concept of a DNA so it doesn’t have to learn again and again. And, how did that work out? You know? So so, I think there’s a lot of technical challenges, and also you’re gonna have are we gonna accept it as a species? It’s great to have Chat GPT write content for you. It’s great to have it write programs. But if it’s going to threaten to take over and re replace the human species, are we going to accept that? I don’t know. You tell me.

Jordan Wilson [00:23:19]:
And you know, you bring up an interesting thought here and and I’ll I’ll I’ll go ahead and offer a a counterpoint to this. So, you know, about which which I I I definitely agree with. Right? You know, yes. AI can only learn things from a database. You can only learn things that’s document, that that’s documented. Right? And and separately, I think that there’s there’s a huge, data quality problem, especially, in in in text. Right? With with what today’s, you know, current large language models are ingesting and scraping off the Internet. But, you know, in a time now when people are putting out, you know, a lot of original content via video.

Jordan Wilson [00:23:55]:
Right? And and they’re sharing their their thoughts, their expertise, their creativity on video. And we know these large language models are now, ingesting, you know, all of these videos and and turning all of this knowledge into their, you know, next models. I guess, what’s what’s your thought on that? You know, are are you, maybe saying that these models aren’t going to be able to decipher enough of this. Are they not gonna be able to, you know, turn transcripts into knowledge, connect the dots? You know, what’s your thoughts on kind of that, disparity?

Luv Tulsidas [00:24:27]:
Yeah. I mean, look, Sam Altman, Google wants window take it all. Right? Sure. Right? And that’s why they wanna encourage us, push this, get all information so they could build the smartest AI and win, win the game. Right? But as you know, government bodies, enterprises saying, woah. Woah. Woah. Woah.

Luv Tulsidas [00:24:47]:
Hang on a second. Do not. They’re banning the use of of ChatCPT. They’re banning the use of Gemini. Now these companies have gotten smarter. They built enterprise versions with d n NDAs where you can’t, learn from my data and share it with everybody else. So a lot of this information that’s fragmented out there in proprietary database, most of them are not even in proprietary database. They’re in the brains of the humans that are doing that job.

Luv Tulsidas [00:25:15]:
Right? So, yes, if it’s in my best interest, I’m gonna go put it on the Internet if I can make money. But at some point when I realized what I’m putting it out there to the AI, I think you’re gonna see an emergence of a lot of custom proprietary AI that, only my AI has access to my intelligence. You’re gonna have to pay, subscribes. Why would I give it to Sam Altman or Google so that they can put me out of business? And by the way, what a lot of people don’t talk about, there are massive, massive lawsuits that are currently brewing against or being built up against Sam Altman. Forget the Elon Musk being, you know, feeling bad for making a really bad business decisions. He put a $1,000,000,000, doesn’t keep control on the board, and now they get to do what they want, and he’s sour about it. That’s a different story. But think about New York Times saying, hey, ChachiPT, you learned all the stuff from my website, my content, and I didn’t get paid for it.

Luv Tulsidas [00:26:17]:
And that’s just the beginning. And the more companies start losing business, now we’re gonna be thankful for our frivolous legal system over here, and you’re gonna see a lot of lawsuits. People are just gonna go down and say, yeah. You know, OpenAI, Microsoft, Google, take it all. Right? So I think there’s a lot more resistance and battles that are gonna come, and I think you will see and we are we this is what we’re doing for a living. We’re building the kind of AI for companies that only their AI has access to their data. And, they are going out of their way to make sure that their proprietary data that gives them an edge is not being transferred over. So it’s gonna get really interesting and good for us.

Luv Tulsidas [00:27:02]:
Right? If window doesn’t take it all, then we got a job.

Jordan Wilson [00:27:06]:
Yeah. Yeah. Love it. I think you bring up great points and, you know, anyone that listens to the show knows that I that’s how I, you know, a 100% believe. I think I bring up the, the New York Times versus OpenAI case at least once a week knowing that’s the big domino, to fall that will probably set off dozens, if not hundreds, of large scale lawsuits. That’s whole another, conversation for another day. But but, love, I I I do wanna hit rewind a little bit, and and get back to this point, you know, because I could I could go off on a tangent. We could talk AGI and robotics all day.

Jordan Wilson [00:27:34]:
But, you know, when it comes to, you know, business processes, right, and and getting back to, you know, how businesses who maybe are don’t know what they should be doing with AI. I think a great place to start is start with companies that have done it themselves. Right? So you talked about even your own company’s kind of, internal transformation. So which, you know, is really related to this question here from Harold. So, Harold, thanks for this. So saying, love, I have seen the AI within Fortune 5 100. I’ve seen the estimated savings from those initiatives. So, Harold asking, have you seen actual improvements yourself with your company? And then if yes, what departments and uses?

Luv Tulsidas [00:28:16]:
Well, great question. And, I’ll start by saying, did you know that less than 1% of AI initiatives today is generating ROI? But everybody is patient because they know it’s an investment, and they’re expecting ROI. Now. Yes. Absolutely. I mean I could tell you I could tell you stories about what we’re doing for customers that have brought unbelievable ROI, but this is what I call specific purpose AI. When you’re not trying to build AGI, you’re trying to build a very specific purpose AI. And, I don’t wanna, you know, violate my NDA and tell you what we’re doing for customers, but I’ll tell you what we did for ourselves.

Luv Tulsidas [00:28:54]:
Right? For example, right now, since we became a any company, we’re seeing a big, big surge in business. Right? We kind of flatline with cloud and digital transfer. Big surge of business. Now we we do a lot of custom development. Right? The statement of works or not. Your run off the mill template that they have to be customized. And guess who’s writing our statement of works and proposals today? It’s our AI. We’ve actually built a custom AI that’s ingesting, a recorded call or a a transcript of a call and turning it into a proposal, and it’s doing it better than a lot of human beings.

Luv Tulsidas [00:29:31]:
That’s 1. We are about to roll out a sales agent. Wait. Go on our website. You can ask questions about what Tech Elusion does. It replaces that first meeting that salespeople have. We have a lot of engineering that are happening. So we we are building our own product that writes code.

Luv Tulsidas [00:29:51]:
We call it AppMod AI. Mostly doing modernization right now. But what it it’s built for enterprise, which means that, you know, if you go to chat CPT, you could say, hey. Convert this code snippet or write me this code snippet. Fine. But in the enterprise work world, you got coding standards, you got compliance. So our tool takes all of that stuff into consideration. It learns for your enterprise, keeps the data private.

Luv Tulsidas [00:30:13]:
We’re using that to write enterprise grade code today. So there’s a lot of I would say so today, we have probably about 500 employees. I stopped counting. Right? But we have about a 1000 AI colleagues, today already, right, in the company. And that didn’t replace human jobs. It was just instead of hiring new people that we couldn’t find, right, that next level, engineer, AI came in and kinda fill that gap. Right? And that’s already, I would say, there are more AI employees in the company than there are actual employees, and nobody’s lost their job, by the way. Right? There’s a lot of growth opportunities for those that make the right move in the near future and I think it’s extremely extremely.

Luv Tulsidas [00:30:57]:
It’s a very exciting time if you’re doing the right thing, but if you’re sitting on the sideline saying, hey, what’s gonna happen and you know. I don’t know. We’ll see what happens. Right?

Jordan Wilson [00:31:08]:
Yeah. And and and love, I wanna zero in on that because I think what you said there is extremely important, you know, when we get into ethical AI. And, you know, it sounds like, you know, what you’re doing at at Techolution, you’re doing it the right way. However, you know, I I I shared this on our big 1 year, you know, anniversary show. So, if if you’re listening out there and haven’t, tuned into that one, I think it’s important. But, you know, the a lot of the biggest companies, in the world, you know, your your $1,000,000,000,000 companies, your your fortune 100, They’re investing 1,000,000,000 of dollars into building their own AI or 1,000,000,000 of dollars into, you know, AI startups. But yet they are hiring less. They are laying people off.

Jordan Wilson [00:31:52]:
And, you know, some companies, even IBM as an example, said, hey. These 8,000 jobs, nope. Those are AI. UPS, these 12,000 jobs, nope. We’re getting rid of those. They’re going to AI. You know, you talk about doing it in an ethical way. Right? Like saying, no.

Jordan Wilson [00:32:05]:
Hey. We’re not gonna lay off. We’re gonna grow, you know, with these new AI employees. So how can companies find the balance, especially public companies who maybe have, external pressure to maybe reduce AI. And and maybe if they do find ROI in AI implementation, you know, they might say, okay. Well, we can cut staff now, which is gonna make our our share price jump. How can those people who have to make those hard decisions, how can they deploy AI in an ethical way?

Luv Tulsidas [00:32:33]:
Right. So ethical is a very relative term. Right? So if you’re from, let’s say, a communist, socialistic based economy, ethical means protect all jobs at all time. But if you’re in a more open, capitalistic economy, ethical means, probably do what’s best for your shareholder first, but also make sure that, the most vulnerable part of our society is taken care of. Right? So we have a safety net. So a little bit of that balance. And I believe more in the latter. Because I actually wasn’t born here, I immigrated to this country and if I believe in socialistic, type of principles, I would have gone to Europe or perhaps Russia, right? I came to America because, I like it, but I also believe there should be you should take care of, of people’s safety net.

Luv Tulsidas [00:33:30]:
So something we may have to consider if we stop the race and say you can’t I mean, even before AI, companies have been laying off people. Right? Because and I get it. As someone who runs a company, right, I was an employee for many years at a company, and I used to think differently. Now that I run a company, it’s like this. Right? If you don’t lay off, you might have to shut down your company. So you might lay off a 100 people, but you’re saving 900 jobs by doing that. Because once you run out of cash flow, you don’t have a business, everybody’s gone. So I get that practical aspect of it.

Luv Tulsidas [00:34:02]:
But I think where where honestly ethics really comes in is, I believe that there will be short term disruptions. We may have to consider some AGI. I don’t know. Not AGI. Sorry. UBI, universal basic income. Andrew Yang talked about that a lot during his, previous, campaign. A lot of people talk about it.

Luv Tulsidas [00:34:24]:
And and I think I think it may be something that we consider because there will be a lot of short term disruptions. No question about it right but as a human race if you go back in time, every time we talked about, hey. You know, the Internet software before that, the industrial revolution. Yes. How many people work on the farms? Not that many. Right? But how’s unemployment doing today? Are we all on the street? Not far from it. This is probably one of the most prosperous times that humanity has seen, except now we’re enslaved by by this. Right? We’re enslaved by this.

Luv Tulsidas [00:34:58]:
Right? That’s our bigger problem today. It’s mental health, how much time you’re spending on the screen, are we living as humans, are we becoming one with the technology. But I think what AI is gonna do, it’s gonna free us from having to be in front of a computer, from having to do the things that we do not like doing anyways. Right? For me, what I’m doing today, building tech, even if you didn’t pay me, I’d be doing this. Right? I love doing this. But I could tell you there’s a lot of people doing tech, not because they love it, because there’s money in it. And if they had they won a lottery, they would say, I’m out of here. Right? I won a lottery.

Luv Tulsidas [00:35:34]:
I I mean, I’m running a good business. I don’t have to work as hard as I am. I’m doing it because this is my passion. Right? So I think people will be forced to go follow their passion. And what’s gonna end up happening because today, a lot of bottlenecks with innovation is because you can’t hire good enough, Python engineers. You can’t hire enough good JavaScript engineers. You can’t hire good enough mathematicians. You can’t hire good enough whatever the skill may be, lawyers.

Luv Tulsidas [00:36:00]:
And, you know, lawyers, if you hire a legal firm, they got their own agenda. With AI taking away all of that, sort of average or below average kind of performance that you’ve seen from humans who have different agendas, it’s gonna enable us to go innovate, solve climate change issues, solve, discover cures for diseases because we will be forced to go innovate, figure out things that is not documented, and bring it back to the AI and work with the AI to take humanity forward. So I think you will see a renaissance of innovation coming soon because AI will force us to be freed from doing jobs we don’t like to do anyways. Right? And, the on the bright side, on the bright side, I think that we might end up passing over. We might be forced to pass over a better version of the future with AI. And for me, the most exciting part is interstellar travel, maybe, within reach at this point if we keep innovating and moving faster than we’ve ever moved before. So I think short term, yes, there’s gonna be disruptions. We need to figure out how to manage it, how to make sure not too many people, end up suffering because of it, but long term, I think this is a very, very exciting time to be living in this world.

Jordan Wilson [00:37:21]:
Wow. You know, I don’t I I don’t know if you all can hear it out there, but I am pounding so hard on my keyboard, just notes and insights. I think today, has been one of the most insightful conversations that I that that we’ve had here on every day in a long time. So so with that, love, as as we wrap up today’s show because we’ve talked about everything. I mean, we’ve talked about, you know, ethics, the future of of jobs. We’ve gone through an acronym soup in a good way, talking the ROI of AI and AGI and UBI. Right? But, you know, when it comes to that one most important takeaway, if a business leader is out there listening and they’re saying, how do I just secure my business future in this wild world of AI? What is that one takeaway that you give to them?

Luv Tulsidas [00:38:07]:
I would say, I would say there are 2 steps. 1st, figure out what battles you wanna take with AI because that’s where success and failure begins. You pick the wrong battle, you’re gonna be wasting a lot of time and money. That’s step number 1. What to do with AI, pick the right battle. And actually this book, it has a great, some great tips on how to guide you on, what I call picking your wow factor for the zeitgeist, the snoozeitgeist that we’re in right now. Right? Secondly, I would say, you know, you you mentioned that earlier. You wanna, make sure you do it the right way.

Luv Tulsidas [00:38:44]:
There’s a good way of doing AI, and there’s a bad way of doing AI. Right? It’s not, I mean, today, you you know, if you look around, how much automation do you have around you? Right? Well, people might say a lot, but if you think about Hollywood movies from the eighties, seventies, we’re far from that level of automation. And a big part of it because, we’ve not been necessarily doing AI the right way. So figure out how to do it the right way, set up a center of excellence. And as you said earlier, there are many thought leaders of AI out there that are giving advice, charging a lot of money for it, but you don’t want thought leaders. AI is something living and breathing. You want what I call living leaders, people who’ve done it, done it successfully. They could show you what they’ve done, and, I would hire them as a coach.

Luv Tulsidas [00:39:34]:
I just watched the movie recently for the 5th time. Remember Karate Kid? Make sure you find your right mister Miyagi to coach you on how to win the AI battle.

Jordan Wilson [00:39:46]:
Wow. So much, just great insights. So many great insights, today, from you, love. Thank you so much for your time, your expertise. We really appreciate you coming on the Everyday AI Show.

Luv Tulsidas [00:40:01]:
Awesome. Thank you, Jordan. This was a lot of fun.

Jordan Wilson [00:40:04]:
And, hey, everyone. As a reminder, so, so, so much we covered in today’s show about securing your business future with AI. If you missed it, maybe you’re out walking your dog or on the treadmill. I apologize. People say, oh, you know, this is my 30 minutes on the treadmill. Sometimes I keep you on for an extra, 8 or 10 minutes. Today’s one of those days. So make sure you go to your everydayai.com.

Jordan Wilson [00:40:26]:
Sign up for that free daily newsletter, which myself, a human, will be writing right after this. Thank you for joining us. We hope to see you back tomorrow and every day for more everyday AI. Thanks, y’all.