Thriving In The Digital Age: Manuj Aggarwal and Future of AI in Business

Summary

In this episode, Manuj Aggarwal, the CIO and founder of TetraNoodle, discusses the challenges and opportunities of adopting AI in various industries. He emphasizes the importance of educating decision-makers about AI and its potential impact on their businesses. Manu also highlights the need for companies to have a strong technological foundation before implementing AI. He advises companies to focus on the 20% of their operations that generate 80% of their revenue and to prioritize low-hanging fruit for AI implementation. Manu predicts a future where AI and humans coexist, with AI assisting and empowering humans in various aspects of life.

Transcript

Joe Crist (00:02.229)
Hello everyone and welcome to another exciting episode of Thriving the Digital Age. Joining me today is Manuj Aggarwal. He's the CIO and founder of TetraNoodle. Manuj, thank you so much for joining us today. Could you the audience a little bit about yourself?

Manuj Aggarwal (00:16.523)
Thank you so much for having me excited to be here. Well, I'm one of the leading experts in the field of AI. I have four patents in AI. I've been working with AI for about 20 years now. One of the projects on AI that we delivered got special mention from President Obama and Bill Gates. Yeah, we have done a lot of impactful work in healthcare, education, real estate, logistics, many different industries.

And it's been a lot of fun. We have impacted over 10 million lives with the technologies that we have built. And yeah, we look forward to continue to make more impact with this technology now that everybody seems to be on

Joe Crist (01:05.483)
Yeah, and that's great. Obviously you are one of the leaders in the world when it comes to the AI and innovation, right? And since you have touched so many industries, right? And that AI is now growing at the rate as well, between like investment capital, the amount of companies starting up and really leveraging different platforms and not just in generative AI, but other areas as well. What challenges do you see

not just AI itself, but for the industries who are using

Manuj Aggarwal (01:36.843)
See, the first challenge is like, even though AI has been around for a long time, but this iteration of AI wave is pretty new. And so when something like this happens, the biggest challenge is, of all, people talk a lot, but they don't know much about the technology. So there's a lot of fear about it. There's a lot of misinformation about it, especially people who are in the decision -making capacity, like

know, C -suite executives, CEOs, people who will write the check to start adopting this technology. So since they don't know much about this technology, they are confused. They generally hesitate to say, OK, you know, it's time for us to invest in AI. So so first thing is educating them, telling them what this technology means for their business, how it can help them grow, how it can make them competitive, because make no mistake.

people who actually don't use this technology and wait for several years before it becomes mainstream, most likely they will face a very stiff competition from others. And most likely they will not be competitive at all. So the idea is to start early and start taking baby steps towards full adoption. Second thing is, obviously, once they decide that they want to implement AI,

We find that their technology that they are using currently in their businesses, it's quite ancient, quite old. it's almost like, you know, you don't even know how to ride a bicycle, but you are buying a jet engine. And, you know, that doesn't really help you at all. So the idea is to...

first come to the table and say, okay, the jet engine is where we want to go. What are the steps we can take from going from a bicycle to a jet engine? And then coming up with that roadmap and putting in place those steps to get there. So this is what we do. This is what we specialize in. But when people have a tendency or like, you know, they have an expectation, okay, I'm ready to implement AI. Now it can do everything for me. It's magic. No.

Manuj Aggarwal (04:01.739)
If your foundation is not as strong, adding a layer of AI is not going to really help. It's not actually going to save you a lot of money or time. But if you put the right foundations in layer by layer by layer, then you become like 10 times more competitive. Your costs come drastically down and your customer experience goes through the roof.

So that's the disconnect between the expectation and reality.

Joe Crist (04:37.424)
You brought up a really good point too. My experience in the consulting industry, we work on lot of clients adopting new technologies, whether it be through monetization or digital transformation in general. One of the biggest challenges is actually having literacy in that area. Not understanding how AI works or understanding how blockchain works or understanding how cloud works or really understanding what it is. It becomes really difficult for decision makers to really make informed decisions when they just don't have the background.

Manuj Aggarwal (04:50.559)
Yeah.

Manuj Aggarwal (04:57.513)
Yeah.

Manuj Aggarwal (05:06.571)
Got it, got

Joe Crist (05:08.477)
I've seen programs out there that will be like, whether it's through Wharton or MIT, where it's like an executive level education on how to do this stuff or how it actually works, but still it's really difficult to obtain

Manuj Aggarwal (05:21.233)
Yeah, I mean, you know, we can take all kinds of courses. Let's say again, you know, using the same example of riding a bicycle, I can take all kinds of courses on riding a bicycle. But until I actually ride the bicycle, I'm not going to learn anything about

Joe Crist (05:39.115)
Absolutely. Another issue I've seen in that space too, when it actually does come to decision makers, when they do implement technology, they're so far removed from the actual implementation that they don't really understand the challenges organizations facing when it comes to that adoption and even the utilization of

Manuj Aggarwal (05:52.885)
Correct,

Joe Crist (05:58.867)
Yeah, so what are some of reasons, like you're seeing that it's really hard for like executives to like really just start adopting AI other than just like not knowing? I mean, it's as constant as you're falling.

Manuj Aggarwal (06:09.631)
Well, mean, you know, it's a human nature. don't, humans don't like change. Humans like to be secure and certain. And when something unfamiliar comes across us, this is how we have evolved. We have not evolved to trust the new shiny object. We have learned, we have evolved to find safety in what is known at this point. And there is a very famous theory as well, like a very

scientifically validated theory, it's called diffusion of innovation, which explains that whenever a new innovation comes along, only about three to 5 % of the human population, they gravitate towards adopting it. They are the risk takers. They are the people who will line up at the Apple store when the new iPhone comes around or they'll buy the new Tesla or whatever. But what happens is once they

have a good experience, then they share it with their friends and family. then about 13 .5 % of the human population, they become the early adopters and so on and so forth until you have laggards and late adopters and whatnot. this is nothing new. This is not a new phenomenon. Every time a new technology is introduced, this is how people

that technology and embrace that technology in waves.

Joe Crist (07:40.391)
Absolutely. mean, I've been an early adopter most of my life, but the thing is too, it's great, everyone asking for recommendations as well. It's like, hey, how'd you feel about that? But the same thing with a lot of companies I see too, especially industries that are really regulated, right? They want to see how it impacts other people. And the big challenge I've seen is when they do this is they're losing their competitive advantage as well, because it's like,

If they're the shiny new toy that actually may help them, they're waiting for basically all the other kids to get it, play with it, make sure it's safe, and then they'll invest in it. But because of that, like the amount of risk they take on by just simply trying to avoid risk just increases exponentially.

Manuj Aggarwal (08:21.739)
Yeah, absolutely.

Joe Crist (08:25.769)
Yeah. So you mentioned to the, another big challenge was when it comes to. You know, actually having really the infrastructure and technology in place, right? He's a lot of systems, a lot of companies are running right. They're, they're legacy systems that don't really create the foundation that AI really needs to, operate in a way that's really beneficial.

What kind of challenges do you see when it actually comes to like what companies are like whatever companies actually using that make adopting AI like even harder or what could they be using instead?

Manuj Aggarwal (08:57.225)
Well, mean, a prime example is, know, a of, a lot of departments are still running on spreadsheets. So for example, let's say your sales department or operations department. And, and typically we see that, you know, these are companies who have been in the business for like two decades, three decades. And as you, as you can imagine, like as they were growing, there was not a lot of technology infrastructure being added as they were growing.

as the team grows, they try to look around and say, okay, I need to like run the business. What is the, what is, how can I make this happen? So they fall back on the least common denominator, which is spreadsheets. And then, you know, those spreadsheets have been like, you know, modified and used for years and years and years. And now it has become their second nature to like just manage the whole thing on spreadsheets. Now what happens is let's

You know, as an executive team, you want to know, okay, let's say you have like 50 employees and they are working in multiple departments. But in order to manage the company well, you need a holistic view of what is happening. Okay. You know, how's marketing doing? How much money are they spending? How many leads are they getting? How many leads are getting converted to customers? How are we serving those customers? Are they, you know,

Are they repeat customers or they are churning? Are they bringing new referrals? A lot of these questions are happening in the minds of the people at the top so that they can make the right decisions. But if the data is fragmented, it's living all over the place, it's duplicated, they don't have the right information, then AI is not going to fix that problem. AI is basically an engine that needs data as a fuel

to drive it. But if the data is not complete, it's fragmented, it's full of errors, then the engine is not going to run. So the first thing that we have to do is try to unify their data, try to bring everything together, try to make sure that there is only single truth of source in their company. And then we start to layer on top of that AI, which can say, OK, if a lead comes in,

Manuj Aggarwal (11:21.483)
using AI and automation, send a personalized message right away. Send a follow up in seven days. Send, you know, if you have a customer who sent your payment, like send a thank you gift, or, you know, if they send you a referral, send something meaningful to them. And all this can be done automatically. In operations, you can say, you know, let's say you are running a, you know, HVAC company and you have a lot of equipment out there. You can say, okay, you

Before it used to be the equipment fails, somebody calls the technician, the technician goes and fixes it. But now these days, I can start collecting data on the equipment and I can say, I noticed that there is a degradation in the service of this equipment and within two weeks it will fail. So rather than waiting for two weeks, why don't you send a technician now? By the way, you

John, the technician is already two kilometers or two miles away from that location. Why don't you just send a message to them and say, hey, on your way, just have a quick look at this equipment. So all these things can be streamlined. And you can imagine as you become automated, as you become AI empowered, lot of the costs, a lot of the overheads start to go down and the customers start to get exceptional service. And exceptional service means

Why do you think people buy so much online on Amazon is because you get exceptional service, because you get the best pricing, you get next day or same day delivery, all of these things. And the reason why Amazon is so successful is because everything is run by AI. So you can see that you as a business owner, any business owner, small, medium, large, doesn't matter. If they do it right, they can also become very

very much like an Amazon of their industry.

Joe Crist (13:22.389)
You it's, you brought up something that is very near and dear to my heart, right? Especially when it comes to technology adoption. I've seen countless times where companies will buy, you know, like the ones who are the early adopters, they will buy a new tool. But the challenge is their process is not well defined or does not work at that. I'm sorry, you've seen this as well, where the process is not really that valuable to the

Right. And what technology does, whether it's, you know, AI or IOT or blockchain or really anything you have, the, the, your, your value stream, your, your, business process or whatever you may be calling it is not actually delivering value to the customer. All that tool is going to do that AI can do whatever it may be. It's just going to take a bad process and make it faster. Right. Which you don't want. Right. It's now you're, you're, you're essentially.

Manuj Aggarwal (14:15.699)
Yeah, exactly.

Joe Crist (14:20.457)
failing faster at delivering value. But you did bring up something interesting. think, I don't think a lot of people really talk on, right? It's actually having the right data, right? Data governance is such a big deal when it comes to actually leveraging things like AI or machine learning, right? And then also, or just even when you're dealing with an entire enterprise architecture, right? Like the way your data architecture moves

works with different applications and different tools does matter quite a bit. So we actually do have that incomplete package, right? It doesn't help anybody. All it does is create greater confusion.

Manuj Aggarwal (14:50.239)
Yeah,

Manuj Aggarwal (14:57.118)
Absolutely.

Joe Crist (14:58.793)
Yeah. So say, you know, it's a brand new company, right? They obviously want to adopt AI. know a lot of them work like the enterprise level companies out there already have it like Google, Facebook, and they're doing pretty good when it comes to leveraging AI, right? They have a lot of experts, but there's plenty of people out there who just don't have that knowledge. So if you're if your company's starting from, you know, the ground up when a concept actually implementing AI, like what should they really start looking at first?

Manuj Aggarwal (15:27.979)
Well, if they're starting new today, they have a huge advantage because they can actually start to think about AI first company. They don't have any legacy systems to worry about or anything like that. But regardless of whether it's a new company, existing company, old company, whatever it is, my advice to people is first look at where does 80 % of your revenue come from.

where, what kind of customers you have. Because in most situations, 80 % of the revenue or the results come from 20 % of the effort. And so rather than looking at the entire operation, entire business, focus on those 20 % and within those 20%, focus on the low hanging fruit and say, okay, you where are we spending most of our time? Where is most of the errors happening?

Where is most of our clients getting bad service or they are unhappy? Where can we put in $1 and get $5 out because of the results it'll produce? Because when you start getting these kind of results, you can start to snowball the effect. You can start to get a lot of return on investment and start to invest back into larger and larger initiatives.

Joe Crist (16:55.531)
Absolutely. And that really does help them scale too, because it's about, you know, it's pretty efficiency, right? Where it's, most of your customers are only going to like a few of your products, right? And by really leveraging, you know, and AI to really carry it, right? You're able to not only deliver value faster and also with greater consistency, which is...

Manuj Aggarwal (17:00.799)
Yeah.

Manuj Aggarwal (17:07.115)
Mm -hmm.

Joe Crist (17:23.083)
creates a lot of trust between companies and customers. But also it allows you to really focus on other issues in the company. It's one of the fastest ways to really scale. And by doing so, really also minimize risk.

Manuj Aggarwal (17:26.144)
Got it. Got it.

Manuj Aggarwal (17:37.941)
Yeah, absolutely.

Joe Crist (17:39.573)
Right? Yeah. So yeah, AI is really, it's really amazing. Like today what AI is doing. But one of the challenges I have seen myself and though it's great for a lot of people, it's really picking the right tools. know, there's, mean, when it comes to marketing or accounting or finance or operations, everyone is leveraged. There's a lot of different vendors out there creating different tools to be leveraged by different companies.

Right. So when it actually does come to like really implement like implementing something large scale, you know, like, there, are there any like best practices out there or like recommended practices for, people to really start looking into or even frameworks.

Manuj Aggarwal (18:23.487)
Yeah. See, here is the thing, right? We are, again, quite early in the AI wave cycle. So my recommendation to people is, if you are building something meaningful within your business, try to focus on established names, established companies. So for example, obviously, OpenAI, Microsoft, Google, these companies are not going anywhere.

products are robust and if you build something on top of their products, you can be rest assured it will last long, you'll have support and whatnot. Now, specifically for other use cases where you have to venture into new types of tools, then look at the history of the company. Are they venture backed? Do they have the right capitalization? Who is the team behind them? Don't try

go after the shiny object and say, okay, you know, this new tool just came out. But when you look at it, it was built by some student in their basement. And in six months, they may not be interested in maintaining that product anymore. And if you build your business on top of it, you're not gonna get a new version of it. Maybe it'll break down. I mean, this has happened so many times, like people who have used WordPress, for example, for their website.

There are millions of, not millions, but thousands of plugins that people have installed in their WordPress sites. And many of those plugins are not maintained. They have security issues, all of that stuff. And now, many people face this challenge of trying to replace those plugins. So it's very similar like that. with the AI as well, just be aware of what is the problem you're trying to solve.

And when you come across a specific problem, evaluate two or three vendors who can help you, and then look for the credibility and trustworthiness of each vendor, and obviously the fit of the technology, and then make the decision that, this is the technology I'm going to go

Joe Crist (20:37.259)
Absolutely. And you said something pretty important too, the right fit. Right? I see a lot of companies out there and people too, just random consumers who will buy something because it's best in class. Not every company needs best in class. They need something that is really will work with their process that they already have designed. Right? But also right about longevity as well. Because the thing is too,

Manuj Aggarwal (20:58.056)
Exactly.

Joe Crist (21:05.471)
You can't be short sighted when it comes to actually building a good tech stack and a good architecture. really need to understand that. consumers, businesses need to understand

If this fails in the future, you're going to have to replace it. And if everything's already integrated into it, like that's going to be a very, very, very expensive fix.

Manuj Aggarwal (21:21.643)
Exactly.

Manuj Aggarwal (21:29.407)
Well, again, in those terms, when you start to implement something, you could create an abstraction layer between your existing core system and the technology that you're using so that if in case you need to replace it in the future, it's not as painful. It's almost like your electric outlet. The same plug can be used to plug in the toaster.

the oven, the grinder, whatever it is, but it's the same plug, right? So you could create some similar interfaces in your core technology where you can plug and play external components and not have to deal with a lot of replacement when you have to replace things.

Joe Crist (22:16.245)
Yeah, absolutely. And that's a great point, right? As you're things like a hub and spoke model where you can really just plug and play and then it's obviously as long as it's working, but there's solutions out there like middleware or even using things like RPA to really bridge that gap.

Manuj Aggarwal (22:27.304)
Exactly.

Joe Crist (22:30.325)
Yeah, that is, that's a pretty critical thing. And I've seen a lot of companies and I always advise against this where they will try to build a custom solution to fix it. Right. But the thing when it comes to custom, like custom solutions, like the company will have your dev team create. It becomes very difficult to scale and then integrate with like new tools, right? Especially when things go wrong or there's a new update or, you know, a patch may exist that may actually interfere with that. Right.

Manuj Aggarwal (22:51.924)
Yeah.

Manuj Aggarwal (22:58.248)
Yeah.

Joe Crist (22:59.391)
then no one knows why it's gone wrong. Absolutely. So obviously AI is getting a lot of capital right now being invested in it. And there is a lot of companies out there building the next great thing. What do you see the future looking like? Right. Because we are still very early on in the age of AI. Where do see it going?

Manuj Aggarwal (23:01.321)
Yeah, yeah, absolutely.

Manuj Aggarwal (23:22.027)
I'll give you a couple of quotations. Sam Altman, the CEO of OpenAI, he has said that a billion dollar company is going to be run by one person by 2030. Meaning everything else, only CEO will be needed and everything else will be run by AI. Another example, which may be a little bit more relatable is, I believe in about 15 years, driving by human beings will be made illegal.

So most of the cars will be just automated on the road. So if you want to look a little bit further, I believe we are going into a future where the virtual world and the real world is going to sort of fuse in a way that we won't be able to tell the difference. It's almost like, again, I don't want to scare anybody. It doesn't mean to be scary. But it's more like a matrix kind of a scenario where

machines and humans coexist, but not in a way that machines are taking over, more in a way where machines are assisting or empowering human beings to do their best

Joe Crist (24:33.835)
Absolutely. And I've already sort of seen a lot of innovation, especially out where I am in Arizona. We have a company called Waymo that has self -driving cars, right? And they are all over the place and you can always see them. very distinct looking, right? They're covered in cameras and sensors and everything else, but you'll see them just driving around town, right? But that's the really what that's creating now is the ability for people not have to worry about.

Manuj Aggarwal (24:41.855)
Yeah, exactly.

Manuj Aggarwal (25:00.128)
Yeah.

Joe Crist (25:00.501)
getting in their car and driving and spending a bunch of money on gas and insurance, all these things is really what it's doing. It frees people up and it allows humanity to really scale more effectively because we're using technology, AI driven technology to really free us up to focus on things we care about. But it is really interesting too, like how it's going to impact other industries. I I'm still waiting for the day when we have...

Manuj Aggarwal (25:18.837)
Yeah, yeah, absolutely.

Joe Crist (25:27.345)
self -driving semi trucks that are making deliveries across the

Manuj Aggarwal (25:31.256)
I think we are not too far from

Joe Crist (25:34.837)
Really? Yeah. I mean, we already have cars right now that can do it. It's probably only a little more work. But yeah, it's such an amazing thing to really see how fast things are really coming along. if you look at last four years on Earth, how many world events are really driving how technology is being developed and at what rate it's being developed, and also the integration of different technologies together.

Manuj Aggarwal (25:59.592)
Yeah, absolutely.

Joe Crist (26:02.601)
Yeah. So I do have one more question for you. Obviously, were a master in the AI space and there's so much that you've already told me and I'm sure the audience as well that it's probably pretty new to them. But if you could give the audience any piece of advice, no matter what it would be, what would you tell

Manuj Aggarwal (26:27.691)
Well, so here's the thing, right? Like as AI takes over, the world is going to shift in so many ways we haven't predicted. But what I can tell you is that our world today is based on human intellect. So whoever has the ability to solve problems, they get the big bucks. But intelligence is going to be a commodity now. It's going to become a commodity. So for example, Einstein had an IQ of about 170.

And AI today can easily surpass that. And we are just in its infancy. So intelligence is not going to be as valuable moving forward. What will be valuable is your ability to empathize, your ability to listen, your ability to really understand what other human beings want, and then use the technology to fulfill that desire. So start working on your communication skills, your creativity, your...

your empathy, these kind of things that will be much, much more valuable moving

Joe Crist (27:33.195)
I love that. I think about that a lot myself where it's, I remember just 10 years ago, feeling how disconnected the world became. And I think that's one thing we really need to focus on now is getting reconnected and really talking to one another and feeling for one another. I'm sure nobody wants to be made irrelevant because AI is...

It is going to start doing people's jobs for them. And there are a lot of industries already changed and there's also, yes, absolutely like connected people, like, you know, have more love in your heart, like so, so much that it's overflowing to the people around you. Yes. I absolutely love that. is that we actually are at time though. And I really do appreciate you coming on the show. I appreciate you not only making me smarter in the world of AI, but our audience as well. So once again, thank you so much.

to our listeners out there. Thank you so much for joining us on today's episode of Thriving the Digital Age. I will see you all next week. Bye

Manuj Aggarwal (28:36.341)
Thank you so much.