Everyday AI Podcast – An AI and ChatGPT Podcast - EP 496: How Real Businesses Are Actually Winning with AI

Episode Date: April 3, 2025

Still experimenting with AI?Cool. While you tinker with prompts and pilot projects, real businesses are stacking wins—and actual revenue.They’re not chasing shiny tools.They’re building unfair advantages.They’re automating what matters and scaling faster than their competition can.And no, it’s not just Big Tech.It’s manufacturers. Retailers. Healthcare companies. Real people solving real problems—with AI that works today.You’ve got two options:🛑 Stay stuck in “research mode”✅ Or see how the pros are doing it and steal their playbookAjay Malik—former Google exec and CEO of StudioX—joins us to share how real businesses are crushing it right now with AI.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Want to ask Ajay or Jordan a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:Role of AI in Business CompetitionStudio X's AI Platform for BusinessesChallenges Businesses Face with AI AdoptionReal Applications for Top Line Growth with AIImproving Products with Predictive FeaturesIncreasing Bottom Line with Operational EfficiencyAI's Role in Automating Repetitive TasksEnhancing Business Operations through AIAI Steering Committees for Continuous EvaluationSpecific Metrics for AI Success in CompaniesTimestamps:00:00 AI Surpasses Turing Test03:48 AI Milestones and Product Updates09:54 AI-Driven Revenue Strategies10:38 AI Enhancing Product Usability14:36 Automate Repetitive Tasks17:33 "Unlearning Manual Task Habits"22:45 Maximize Productivity with AI26:40 Embracing AI's Rapid Business Shift27:44 "Identify Business Pain Points Together"31:09 Leading With AI in BusinessKeywords:Generative AI, Large Language Models, Enterprise companies, Smaller businesses, Increase top line revenue, Increase bottom line efficiency, Real businesses, AI platform, AI adoption, ROI versus hype, Supply chain management, Predictive analytics, AI voice control, Embedded inspection, Retain customers, Operational efficiency, Repetitive tasks, Automated processes, Google, Skill differentiation, AI assistant, AI augmenter, AI-enabled products, Sales opportunities, Knowledge management, Error reductionSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live and Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. Let's be honest.

Business is a game. There's winners. There's losers. It's a nonstop competition. And I think especially with generative AI and large language models, that holds truer than ever. You know, now all of a sudden you have enterprise companies that are struggling to keep up with everything that AI offers.

And then you have smaller business. that are maybe a little bit more nimble in competing on grander stages that they never thought, all because of how you can use AI. So today we're going to be going over, you know, not just how you can increase top line revenue and increase bottom line efficiency with AI, but how real businesses are actually winning. That's what it comes down to. Business is a game. And if you want to compete, if you want to win, you have to use AI the right way.

And that's exactly what we're going to be talking about today on Everyday AI. What's going on, y'all? My name is Jordan Wilson, and I'm the host of Everyday AI. This is your daily live stream podcast and free daily newsletter, helping us all not just keep up with AI, but how we can get ahead and use it to grow our companies and our careers. So it starts by learning on our daily podcast and live stream. I have a great guest for you today.

I'm going to introduce here at a couple of minutes. But then it actually happens when you leverage. it. All right. So that portion starts by going to our website at your everyday AI.com. While you're there, you can sign up for our free daily newsletter. That's where we're going to be recapping the most valuable insights and more information from today's conversation, as well as giving you the 101 on everything else happening today in the world of AI. So this is how you can leverage it to get ahead to grow your company and your career. All right. So I'm excited about that. But before we get started, some days we go over the AI news.

Today is one of those days. So let's give you the quick outlook. So first, a new study has shown that AI has passed the Turing test. Wow. Okay. So a new study by UC San Diego's Language and Cognition Lab found that OpenAIs GPT4-5 convincingly passed the touring tests being mistaken for human 73% of the time. So the touring test proposed by Alan,

Allen touring in the 1950s, evaluates a machine's ability to exhibit human-like intelligence by having a human interrogator distinguish between a machine and another human in text-based conversations. So GPT 4.5 from OpenAI excelled under persona prompts, where it adapted specific identities like a cultural, savvy young person, achieving a 73% success rate without, personas, its win rate dropped to below 50% at 36%.

Other AI models underperformed. Even OpenAI's GPT40 only scored a 21% versus 4.5 that scored that 73. And, you know, Meta's Lama as an example, you know, didn't get to that 30% mark either. So for this test, 300 participants were tested in eight rounds, tasked with identifying which conversation partner was human and which was AI. So yeah, the majority of humans were fooled by GPT 4.5. So yeah, a lot of people are now saying the touring test has been officially passed. This is one of those things. There's always going to be arguments, right? It's like, oh, when have we achieved AGI? Oh, when will AI pass the touring test? Well, it looks like at least

according to this study, a lot of people are saying it just happened. All right, a couple other bullet point updates for you. There's too much news, right? So rounding this up here in AI. product updates. So chat GPT announced that their new mega viral GPT40 image mode now takes longer on purpose to give you better results while generating images. Notebook LM, my favorite AI tool, now has an option to find new sources from the web in addition to grounding it in your own data. Don't forget about that new mind map feature they shipped last week. Pretty mind boggling. Microsoft co-pilot rolled out new voices for its AI voice mode. And we are supposed to be getting a new, highly anticipated version 7 from Mid Journey.

So if Mid Journey does drop that V7, we'll make sure to cover it in today's newsletter. All right. A lot more on those stories and everything else in today's newsletter. So make sure you go check it out at your everyday AI.com. All right. Let's get to winning. Let's get to winning with AI. It's what businesses, you know, I think for the most part, for three years, they've been

trying to figure this out. It's an ongoing battle, but today I have a little help with great guests. So live stream audience, please help me welcome to the show. Ajay Malik, the CEO of Studio X. Ajay, thank you so much for joining the Everyday AI show. Oh, thank you for having me. Very excited to be here. All right.

Hey, I'm excited. And I always have to give a special shout out because this is a live stream. It's unscripted, unedited. So, you know, in my time in Chicago, it's 7.30. But Ajay joining us from San Jose. So 5.30 a.m. got to shout him out there. So real quick, before we get into this topic, Asha, can you tell us a little bit about what you all do at Studio X? We have an AI platform with multiple applications and we help businesses adopt AI in their business, either to improve their top line or help with their bottom line.

Okay. Perfect. And give us an example. A company, you know, comes to you or they, you know, use the Studio X platform. What's the main problem they have going in and what's that main. issue that you all are trying to solve. Very good. So, you know, AI, a lot of hype out there. And, you know, like, they are, like, everybody wants to win with the AI, as you said earlier also, right? Everybody is focused on that, but they really sometimes don't know how to start.

Okay? That is one thing. Second thing is within their company, they have this fear. Some people are like, oh, AI is going to take my job, right? AI is or AI is, oh, everybody else is using AI. I have to use it. So, you know, they do not have abilities. to distinguish between the ROI versus Hyde.

That is one of the biggest things they start with. Like, where do I start? And how do I win? How do I use it? How do I succeed? And that's where they start. And then we start helping them like how and where distinguish them, talk to them, show them the examples.

We have customers, Fortune 500, small companies, midsize, all kind of companies. So we help them give them examples how others businesses, similar businesses are using to help them decide. Love it. All right. And hey, as a reminder, live stream audience, thanks for joining us. Get your question in if you have one for Ajay. It can probably take a couple at the end. So everyone joining us on LinkedIn, and Marie and Brownwin, thanks. And on YouTube, Sandra, Michelle, everyone else. Thanks for joining us. If you have a question on how your business can actually win with AI, get it in now. So, Aj, let's start at the end. How do real companies actually win with AI? Let's give us. way the answer is now and then we can dive in. All right. So you know what? The real companies focus on real problems. Real winning comes with real problems, real quantifiable. You know, there is a lot of hype, as I said earlier, and there is a lot of fluff. Oh, you can change the world. And you know what?

Everybody wants to change the world, which is a good thing. I do too, right? But the key thing is, how big is your bite? Can you chew what you are biting? It's like this. Are you going to solve, if you have to solve one problem, you can say, oh, I will eradicate malaria. Another could be like, hey, I will find a better medicine for malaria rather than eating five days consecutively. You eat two days. And you know what? So you can decide and focus on the smaller problem so that you can execute it, implement it. And that's what the companies who are successful AI doing it.

Okay. And they are keeping their focus narrow, very narrow. Like I am focusing on improving what? And you know, by having a very clear focus, almost like a micro focus or nano focus, you know, that this is what I want to achieve. Hey, I want to improve my supply and demand management. I want to change this, that, you know, fix.

Pick a small problem, small section of a problem. That's what the companies are doing or not big, companies who are successful. And, you know, picking the application. Let me give you some examples of application, right, for improving the top line. What can you do? For top line, you can do like, hey, make your product. smarter, like have some kind of predictive alerts in the product. You know, like your car, right? My car has an engine light. When it is on, I am like, oh, I have to go to mechanic right now.

Right? You are scared, right? Can I continue driving? Do I have to rush today? What do I do now? Because the orange light is on. But just imagine if there was a blue light in the car, which was like, hey, you should go to mechanic in next four weeks. That is much more relief. And making your product something like this, adding features which else, that's the idea. So let's talk about each of those two things. So, you know, kind of this, this top line and bottom line, right? Because I think everyone is always looking at measuring the ROI of AI. And, you know, my hot take is don't. But, you know, everyone needs to, right? So I think bottom line is maybe a little bit easier. But when we talk about top line, right, in increasing revenue, you know, you kind of

talked about, you know, the example of predictive analytics, right? Like, that's a great one. But maybe can you Give us a couple examples or use cases of how businesses should be looking at AI on the top line side, specifically ways that you can add revenue with AI. Very nice. So top line is all about like adding new line item when you are selling something or charging premium pricing and justifying it. Right. So you know what everybody is talking about like for operations, Microsoft co-pilot or every application which can help. But just imagine the printer you are selling, right, or a device or a device or

product you are selling came with a co-pilot. Imagine that, you know what, you are working with a small printer and you are stuck, how to deal with it. It has some alert, small window screen, problems. But imagine I could just do a QR code, go on my phone, and now I can talk to the printer and, hey, what's wrong with you? How do I fix this? Right, making the products much more usable and people will like that because it will make the product more usable, right? Or having something like inspection, you know, like a vending machine. Okay, so vending machine, there is a lot of motors inside it and just imagine if there was some microphone

some camera inside it which is listening to the sound and watching and monitoring everything and it can tell oh the machine needs oil change machine the elevator is not working think like this so the AI using AI to make your product valuable the product becoming

much more useful much more reliable for your customer that is where you add value right whether you can add a voice control interface you can have embedded inspection in the product Or even, you know, like simple things like lead management, you know, personalized lead sending. So anything that can help you find more customers, retain more customers, those applications,

hundreds of applications, and many are very easy to implement. It's just about focusing on them and thinking how it will help your customers. Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI Assistant. now live in the Adobe Firefly app, the all-in-one creative AI studio. Powered by Adobe's creative agent, Firefly AI assistant lets you start with your vision, just describe what you want, and shape the outcome as it takes form with the assistant.

The assistant orchestrates multi-step workflows, drawing on 60 plus pro-grade tools across Adobe Creative Cloud apps, including Photoshop, Illustrator, Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible so you can refine, redirect, or take over at any time. You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly.adop.com. Yeah, a good question here from Monica in the audience.

So, you know, you kind of talked about Ajay, kind of this concept of like, hey, with AI, don't focus on eradicating malaria. Focus on, you know, the smaller steps, right? So I think that was a good way to talk about starting small. So she's asking what are some of the smaller problems your clients have solved with AI? Smaller problem. One of the problem voice control, like one of our client. they make welding positioners, okay, and the welder is using them. Now the welder is using them.

Normally, welder was going to a machine and pressing, display, connecting the buttons, touching a lot of things. And he's welding. And in the middle of things, they have to change the machine, rotate the part they are welding. It is work and they had to go and gloves, remove gloves, touch the machine, come back. It was operational problem. And all that did is added in their helmet, they have a Bluetooth, and now they can talk. to the machine so that they can say, hey, machine move up two inches, move down, rotate, tilt, things like this, they can say, that's the thing, just focused on a very small thing,

but it immediately solved the problem for the welder, it helped it, so now they can sell the product at a higher price. Think like this. So you need to add some small thing like this and or having a something like, as I said, the example was real actually, the vending machine that is one of our customer. We put a microphone inside the vending machine and it is listening to the sound and it listens like if the machine is making you know like your cars make sounds when the brake is going bad like you hear that sound and you know we need to do something same thing machine is listening to the sounds inside and hey everything is moving smooth no new sounds so it means the elevator the motors everything is work that is the thing think very very small tiny

problems inside your product to help or tiny experiences inside your for your product like so many of these examples are are hitting home for me a jje i'm like squeaky breaks. Yeah, I'm listening to that all the time. And like the printer, it's like, yeah, why aren't printer smarter? Like, why, you know, like, why do I have to, you know, spend two hours every single time I'm at my mother-in-law is fixing her printer? Why can the printer fix itself? My gosh. But, you know, maybe let's get back to bottom line, right? And maybe we can, you know, ping pong across. But, you know, I think this is where a lot of companies start, right? increasing efficiency, improving outcomes, right?

Just making things better with AI for the humans that are spending time, right? I think sometimes these use cases or examples of winning with AI on the bottom line or maybe obvious. But let's talk through maybe give us two or three examples of what are those bottom line wins for companies with AI. All right. So bottom line win is all about where you spend a lot of time. or where it is very repetitive. You are doing things like, you know, I do every day this thing. Okay, what are those things?

You know, when I was working for Google, my boss said one thing, hey, anything you do more than three times? Should be automated. Why are you repeating it? You know, and that's something very simple. Like, what are those things I keep doing again and again? And am I really applying myself?

You know what? There is a fear, genuine fear in operational efficiency. you know, is the operational efficiency going to work on take my job? Because, you know, I made things so automated and now they don't need me. If you are not adding value directly and you were just repeating and doing the work, I think you will get eliminated anyway. That's how it will happen in the world. It's sad, but it is how it will happen.

But if you were using AI, you were making your job better so that the company gets more out of you because you are doing things better. You are things people have not done and that's what it is. And in operational efficiency, think about what are the things that take most time for you? They are repetitive. They are boring, right? More prone to human errors. Look at those things and you can solve them.

I give you some examples, okay? Knowledge in the company. Documents are everywhere. Information, contact, all information, product specifications, features, history, so much data. And you know what? Suddenly the sales guy says, hey, hey. did we do this? Have we solved this problem? Have we sold this product? What was the quote we gave last time? You know what answers are there in the company data? But to finding those answers can take

time. You know, there is some study I saw 27% sales opportunities are lost because they did not have information at the right time. And it takes time to respond. And when you take time to respond to a customer or prospect, prospect finds another vendor in that time. That's the thing. Or, you know, what, engineer, a new engineer has joined, he wants to do something, she wants to do something. They don't know how to do it. And they don't want to ask every day, hey, how do I do this? You know what? You train them for first two weeks. They don't learn everything. Having that bot, having that AI agent assisting within the company, providing whether it's demand forecast, whether it is things. Or I give you another example. A factory, well, we, they have factory,

they have a lot of machines going on, right? Hundreds or thousands of machines working. Machines are very good. everything like they bought it in 90s. These are not IoT machines. Now, one machine stops working or is like weaving the fabric wrong way or machine is packing the coffee wrong way or some application like that. How do you know there is a supervisor or there is somebody on the floor checking constantly looking out, right? Just imagine if the computer camera can do it and alert you, hey, that machine is not working. And that is an operational efficiency achieved inside your business just like that. Yeah. And I think a lot of great points there. But, Aja, I, I want to rewind to something you said at the beginning of that answer there.

Right. So, you know, you said at your time at Google, your boss said, hey, what are you doing, you know, more than two to three times a day or, you know, these repetitive tasks, right? And I think sometimes there's this narrative that I always like to get in and try to correct, right? Because everyone's talking about, you know, upskilling and reskilling and all these buzzwords. And I always say you need to learn to unlearn, right? And because we've been learned and we've been rewarded for doing these, you know, manual tasks over and over for decades, right?

So, you know, I'm curious because it can be hard to give away agency to AI. But, you know, going back to that two or three things, giving you away to AI, what are those two to three things, either you or your team, you know, as a large language models started to surge in capabilities? What are those things that you started to give away? The key thing is we used to, you know, like I will tell you this, two years back, we made a company policy. And the company policy was skill is not a differentiator. Okay.

Very important point. Because, you know, we get too hung upon, I know something or he knows something, she knows something. No, you can all find it. Everybody has a employee named chat, GPD or cloud or whatever you use, okay, and use it. use that to do better. And the moment you have that, if somebody gives you a problem, you can solve it. Don't think, I don't know about it. I have never done this before. No. You know what? We are no more, you know, like Google search. I Google search, I always call the six cents. Okay, I tell you, we have five senses. We all know that. The six cents, because, you know, suddenly all the

information is accessible to me. I can find the answers. I type something, I get the answers, whether it's nearest pizza or some knowledge or how somebody has done something. But now with AI, AI is the seventh sense. I actually don't get just the data where I look at the results. There is somebody else looking at the data providing a response to me, how I can do that. Right. So use that AI to do your augmented. AI is your assistant.

AI is your augmenter. And then AI is the skill. So all we have to do is how to use AI, how to apply AI. And so, you know what? The things like, you know what, social media posts, no more. It can be done by AI, right? And AI creates all the images, the posts and post them. You can do some things without effort, right?

You can write coding. Oh, coding is so much better with AI, right? Testing, so many things, test case, and every use case really helps the company day by day. And you start using them and certainly people feel a lot more productive. I tell you, I feel, I know it may sound like a big number, but I think I am individually 25 times more productive than I was. And it's just because using AI so much more. You know what?

I tell you, I thought AI will make my life easy when my work has increased. I am working so much now because I can do so much. It's like a non-stop because I have an assistant who thinks a permanent full time. You know, the only time I am like, oh, the cloud is down or chatypt is down. So, okay, let's me take a break. Okay. That's how it runs. It's so funny,

actually, because I was just talking about this with my wife last night. And even for me, it's hard. It's hard because, yes, I'm more productive than ever. I'm learning things faster than ever.

But I'm also forgetting things faster than ever, too, because I don't know if the human brain is designed in a way that now we can retain and actually use all this knowledge, the way that, you know, that we always had, right? I think we have access to too much great information too quickly, but that's another story for another day. But I want to get back to what you said.

Skill is not a differentiate. I love that. And I think we have to call it out more. I've been a little more brash with it. And I say your knowledge doesn't matter anymore in the age of AI, right? So with that and, you know, in your example for your company, skill not being the differentiator, okay. So how do you, you know, flip the script and how do you,

in your team, then focus your human time. If skill is not the differentiator and it traditionally has, what is then, how are you spending that top line and bottom line human time to win? You know what? So this is how it is. I give you a formula. Okay, whenever you are doing a task, say it takes 100% it's a task. Then the first 15% is done by human. What I'm going to do, defining it and using even AI to brainstorm it, but it is about defining it and that is your task. That is the task. We do a good job in that 15% and then let AI do another 70% how to write the code about it, how to do whatever you need to be done by AI in that task and it does it.

And then last 15% to cross-verify and making sure. So you focus on your top line and bottom line. And for our company like the things which we want to achieve, hey, this was my good. goal and how do I achieve that. That is for each employee's job. Each person, think, think like this. And this is for everybody. Use AI for the first 15% to define and making sure you are in the right direction of what you want to achieve. Okay. And then let AI do the work. And then last 15% is AI doing it or not doing it exactly what I want. And this way, I am more productive because now I'm spending like 30% of my time on the task and 70% AI is doing it. Now I can do it.

lot more. My velocity is a lot more. And hopefully I have more time because I'm telling you, time is becoming even more shortage because everybody is like, it's excitement. Because now I can do so much. It's like, you know what? Oh my God, I can do this. I can do that. And you are continuously running faster now. Just look up you can do that. That's how I see. Yeah. So, so, you know, good, good question here from Kimberly. So Kimberly, thanks for this one. And so she's asking, you know, you kind of mentioned this earlier, right? Like companies trying to bite off more than they can chew when it comes to AI. So she's asking, have you ever seen companies bite off more than they can chew too early?

And then how did or how should they correct this? Very common. You know what I say there are top three problems with AI. When people are time to implement businesses, they start the number one problem is starting to big. Second problem is they ignore their data reality. And third is they focus, they chase the trends. Hey, what others are benefiting. These are the three problems.

They do that. And I'm glad Kimberly is asking this question. You have to course correct. Don't be afraid to course correct. Course correction is the most important thing humans can do. And like you are talking to Claude and asking it to do something. And then suddenly it's not working, then just start a new chat. It's okay to start a new chat.

In my own personal life, I have done that. You know, like that whole saying that, oh, changing the horse in the middle of the race? Please do. Please do. Please do not keep going on that house. Change it. If you made a wrong decision, you can actually recuperate, you can fix it, you can do something much better, faster. People do that mistake. And you know, whenever you realize, oh my God, it is like not milestones. You should, you know, like as I was telling you earlier, you should have a picture. Okay. This is the way. Have a picture. You know, like the before and after picture for weight loss like hey i was like here 260 pound and i'm like now eight pack and i'm like

looking fabulous okay but there are it doesn't happen overnight there will be like hey somewhere my weight will be lost to another goal there are milestones in the journey monitor your journey do you are you hitting your milestones are you moving towards to the goals you wanted to achieve and if not immediately course correct and instead and then immediately say okay guys we are not going to work on the whole thing let us see which parts of the real problem we want to solve this is the whole big use case which we wanted to solve we are not going to automate everything and make everything a i let's fix and then person says oh you know what we spend two weeks in finding all the information when customer reports the problem okay in the whole six-week process for solving the problems okay

let's just focus on that micro problem and it's okay and you know what you will have wins and then i tell you in one year six months or nine months two years i don't know know the time frame for your problem and to end problem you will solve it but pick that micro problem and if you have started big change the horse stop it and move to the smaller part which is miserable if it is not miserable if you cannot quantify what you got out of it stop that's that's so good right and uh i love that advice a jay and in kind of how you tied that into you know kind of swapping out the horse in the middle of the race because you know when we talk about winning with AI, you know, when I kind of started the show off by saying like, hey, business is a

game. But I think sometimes, right, because traditionally the way that, you know, tech innovation has gone, you know, you generally plan things out, you know, multiple quarters or maybe even multiple years in advance, right? So we've always thought of these games, the game of business being a very long run. But with AI, it's hard to do that, right? If you take, you know, two weeks off, you know, from using AI, it feels like, you know, you're from the 70s. It's like, wait, how does this work? Right. So how do business leaders, how can they, you know, I guess find that balance of being

present in quote unquote playing the game and winning with AI, but also being like, yo, is this horse, do I need to swap this one out? How do you do that? All right. I think every business owner already knows what is good for them, what they want to achieve, and what is hurting them. They already know that. Actually, you know what?

Just have one meeting with your staff or with the team or everybody and all hands. All right. And just discuss, hey, what are the key things where we are wasting time or what happens again and again? And ask those questions. You have to think like this. And then come up with those specific metrics for success. That, hey, it would be nice if we could do this.

It would be nice if I could do this in finance. It would be nice if my product did this. It would be nice if my customer support had this. Because AI is usable in many, many departments. Don't get hung up on where you want to use. Don't start with the idea your neighborhood. Don't start with the idea that you just heard on a podcast. Focus on your real problems.

Always focus on that. And always have a re-evaluation, continuously ongoing re-evaluation of what you are doing. I would say have some kind of an AI steering committee or something in. your business looking at it, always looking at it, what we are achieving, and be specific. How much processing time we have saved in last three months by doing AI? How much conversion rate has changed? You know, be so measurable. Be very, very specific.

If you are not very specific, you will fail. And if it is not, you know what, no hard feelings. Don't say that, hey, whatever you were doing is wrong. No, it's not like this. It's like, you know, sometimes we get so, oh, it will improve the efficiency. It will improve the revenue. We should do this. It will just change the game for us.

No. Focus on how much change and how will you measure, how much game is changed. If you start having that thought process, forcing yourself to write it. And you know, a lot of coaches and everybody says this. If you cannot measure it, don't do it. And that is the key thing in the AI also. And if you identify, see something, you are making progress, but not. How I say it in my company, I give you the number.

Everything, you know, but do not use sentences. I always say that people laugh at me. I say, I don't want a Shakespeare answer. I need numbers. Make sure your answer has numbers, digits, zero to nine. If your answer digits, you are not using digits, it's not moving. The needle is not moving right enough. Love that.

Another piece of great advice. So, Ajay, we've covered a lot in today's conversation from, you know, different use cases on winning with AI. on the top line, different use cases of efficiency and performance gains on the bottom line with AI. But as we wrap up today's conversation, you know, what's your one most important, most actionable piece of advice for business leaders out there who are like, hey, my team, my company, we've been playing the game, right, and using AI. But we're a little stuck. What's the one takeaway for them to actually start winning with AI today? I would say the same thing.

which I said earlier, start small. Think big, start small, scale fast. That signal also. Think big, start small. Okay, always start a small, miserable application. Pick a small thing which you can say, oh, we did it and it works. Have those small, successful moments given by AI. Do that.

And you know what? And as a leader, it is your responsibility. If you are the business owner, if you are the manager, if you are the person who is driving, it's your responsibility to lead with AI, force people that, hey, what are we doing today? You know what? Today, when you go to work, have this question, what I am going to do using AI or what I will do AI in my job or how I will use AI in business, not in a big way, just as small. Even if it saves me 10 minutes a day, think of those applications.

Even if it gives you accuracy for one small item every day, think those. That is what it is. Love that. Can we get that on a t-shirt or something? You know, start small, think big, scale fast. Love to see it. Ajay, great conversation today. So thank you so much for taking time out of your day to join the everyday AI show.

We really appreciate it. Thank you so much. Really enjoyed. All right. As a reminder, y'all, like that was raining, just raining great advice on our head, just dropping. moments of truth on us when it comes to leveraging AI. So if you missed anything, don't worry about it.

Yeah, you can go rewatch, re-listen. But what you need to do is go to your everyday AI.com. Sign up for the free daily newsletter. We're going to be recapping today's conversation and a whole lot more. So make sure you've learned now go leverage with our free daily email newsletter. So thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks y'all.

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