The Agentic Insider

TAI - Dhaval Patel
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Speaker: [00:00:00] Welcome back to the Agentic Insider. I'm your host, Phillip Swan. In this show, we explore cutting edge ideas and trends in AI and data, as well as hear from other industry thought leaders in the AI space. This podcast was brought to you by arid AI committed. To safe and responsible AI innovation. Let's dig in.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Hi, and welcome to this week's edition of the Agentic Insider with Alistair N is a professional with over 20 years, experience in data, AI technology, and analytics. And he is a program committee member of the European Conference in Artificial Intelligence. He's also an adjunct professor in the Masters of Technology Program at NYU School of Engineering, and [00:01:00] he is the co-founder and Chief AI Officer at AI4Purpose Inc.

And previously head of. Analytics and data science at SaaS. Dhaval Patel. Welcome to the show.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Thank you. Pleasure to be here.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Dhaval. We've been excited talking to you, um, both Alistair and I, but can you tell us what future you're solving for?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Well, yeah, no, that's a great question. And and thank you so much Phillip, Alister, uh, for having me today. Um, so what future. Well is, if I think of the future that I'm solving for is where really data and ai, um, and this, uh, technology evolution, they can stand together, right? They're not just, uh, powerful technologies and tools, but they. They can be and they will be the trusted partners for humans in decision making. Now, I know we see AI as, as a threat. There is a, a lot of resistance and reluctance in AI [00:02:00] adoption to some degrees. However, um, we are on the verge of having AI becoming an integral part of our, our day-to-day lives, right?

And, and believe it or not, AI is here to stay and it'll flourish going forward. So. What in, in my particular areas, I have been mostly involved in healthcare and life sciences. Um, and a, a strong horizontal of my skillset has been data science and AI for over a decade now. So in life sciences, what that means is. Accelerating the path to, for, for the drug discovery, getting the drug in the market, uh, by leveraging this cutting edge AI technology and tools available, right? Breaking the, the silos right in, in, in the life sciences industries and how really we can go beyond the traditional drug dis discovery approach that sometime takes.

years for, for, uh, a particular therapy to come in the market. Now I also have a personal, uh, uh, tragic story about my dad who had an IPF, which was an irreversible [00:03:00] condition, but at times, yes, the drug, there are so many trials in, in, in, in, in the pipeline, and the drug could be available in the market earlier if there was the right technology available, right?

Patient pool available, uh, who could respond to the therapy. And of course, the right evidence that can be generated, right? So.

That's what I'm thriving for, uh, where AI can become part of this new scientific breakthroughs, help people, humanity to flourish. Now, on the flip side, as a father of two young kids, and both of them, they're AI experts, right?

They're on chat, GPD pretty much every, every single day, right? One tab is open on my daughter's Chromebook, and she tells me that she knows everything now. Thanks to Chad, GPD and I don't know anything, I don't work in AI according to her, but what I, what I am looking for that generation especially, um, I want them to inherit a future where technology amplifies, um, their, their capital, right, their, their potential.

Right? It's just not dify. I don't know [00:04:00] if that's the word, but want a techno

riverside_alistair_lowe-norris_raw-video-cfr_the_agentic insider_0032: Yeah.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Exactly. Yeah. So I don't want the technology to cripple their, their thinking, the potential that they have, right? I want the technology to amplify their potential and they will have a better life, better future for them as well, right?

For them. And not just for them, but for, for every human beings and, and for every family. So that's what I'm, I'm looking for. Um, and that's the future I'm solving for.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: That's, that's awesome. And I've just stayed as a father of two myself. Uh, mine are now probably more grown in the years I still. Or nothing. So, um, get used to it.

It's,

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Well, finally we are at a point where they assumed that I work and I do something. Up until last year, at least for my younger one, he was like, you stand in front of the screen whole day, which I can do it as well. So he didn't think I work for, for something. Right? Anyways, that's the curse of working from home.

riverside_alistair_lowe-norris_raw-video-cfr_the_agentic insider_0032: Oh, it is. Absolutely. And I mean, I think, I think for, I think [00:05:00] for, um, uh, for, for us, you're speaking the same language really. Because, you know, we have three pillars of responsible ai. We, we talk about, you know, AI being ethical, AI being safe, and AI being good, good for people and good for the planet. And I think that that's, that that's really aiming to benefit society.

Okay. And, and individuals as a whole, you know, improving health. Care, improving education about creating those positive impacts. And I think that's, that's really lining up with the way that you are talking about this. We see that, that we have a principle around, you know, human AI collaboration. We want, want systems to be able to, to augment and enhance, you know, human decision making.

Um, um, you know, and creativity, productivity, things like that. But at the same time, we also feel there's a huge social and cultural impact, and we want AI to be attentive to that. And so, you know, when I look at, you know, what you, what you've done, you founded, uh, you know, your, your AI for purpose. And really, I think this is, you know, this organization here that you're doing it, this, this, it feels like this is really around AI for social [00:06:00] good.

Can you tell us a little about why you decided to found it? And then what you are really trying to, to achieve with the, with the organization.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Yeah, sure. Yeah. So AI for purpose, um, it's a, it's non-profitable 5 0 1 3 C organization. Um, I have been fortunate to work with, um, uh, really, I would say super humans in the industry, right? And in pharmaceuticals, life sciences, healthcare, and, and of course in finance as well, where I started my career.

Um, and so these leaders, right, they also. Had same thing in or something in common, and it was kind of on the same thread. How do we make the social impact? And now with all this explosion of AI and then bringing all this leadership together, right, how do we really harness the power of AI to, to make the social impact, um, to, to. Impact people's lives. And again, it it, it was really close to the personal story, uh, that I, and, and many of our, our advisors and co-founders share, uh, that [00:07:00] how do we really enable the next, next leadership, next generation of the leaders, right? Uh, through innovation, through mentorships, et cetera. If I go back to and look at my career path, I happen to land on, on the journey of data science and AI accidentally.

Like, I didn't really choose Jews. Right. Um, and back in the days when I started data science, it wasn't mainly, it wasn't even known as data science. And when DJ Patil in around like 2011, 12 coined this term, like sexiest job in the 21st century and whatnot, I married to the title in, in two of my previous jobs.

I even fought for the title, but the journey that led me to become a, a, a profound data scientist and AI leader. Um. Really, if I think back, if I had a good mentorship, good, good path to good network, um, I could have, my career could have been much better. I mean, I don't have any regrets, but I could have made better decisions, not accidental decisions, right?

So that's where many of us, uh, we had, we were sharing the same passion. And the couple [00:08:00] of co-founders and I, we were talking basically, how do we make this happen? How do we create an organization that also stands on these three pillars? We, we have three pillars, innovate, connect, and mentor. Right? Innovate is, is more like incubation.

So we, we host bunch of hackathons across the, uh, country in, in some of the prestigious universities and nyu, Columbia, et cetera. We work with, uh. This new breed of ai, uh, experts, right? The, the students, et cetera, try to generate innovative ideas and create more of an incubator. Um, we also kind of create this, uh, network, right?

We, we, we are, we're connecting people and bringing this ideas and, and kind of harnessing the power of this collective intelligence. And then mentorship again, it's more like how do we really. Take this incubator ideas, right? And, and take it to maturity stage. If I look at my data science career, like 89, 80 to 90% of my work has been just on my laptop. It never saw the daylight, right? Two reasons. One, [00:09:00] there wasn't really, um, uh, a proper roadmap, right? How, how do we really deploy those models, et cetera. It wasn't well. Thought through back then maybe technology wasn't, or the platforms weren't that mature as well, and second funding, no funding, no daylight.

That's, that has been kind of the key theme. Right? And so really to, to create or, or rather accelerate the innovations, right? We, we co-founded, um, and I co-founded AI Purpose, purpose with, with, um, some amazing leaders in the industry.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: I'm listening with fascination here because you have had an incredible career, um, going from Nvidia as a device driver writer, which is, goes back to where Alistair and I started off life as well. So we have that in common as well. Um. You know, it you to being a data entrepreneur at Bloomberg and, and now building what you're doing.

So is there a really a pivotal moment that shifted your career, right? You know, that really [00:10:00] going from a traditional software mode into data and ai, what, and if so, what was that pivotal moment in your career?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: So there, there were two pivotal moments, uh, Phillip. Um, and so one. When, when I hopped on this data science AI bandwagon many, many years ago, like I said, it was accidental, but I. I. started my career in finance and back in the days, right, this is like 2007, eight, finance was the only industry generating real big data, and I was working on real, real big data with the technology pre-cloud era technologies, right?

Mainframes and whatnot. And I got really fascinated about the data. The data is new. Oil wasn't become, it wasn't even popular back then, right? So this is again. Pre the, the data oil era. And, and so what, what I saw was like the power that that technology technological evolution can bring, right? If you use data and information [00:11:00] wisely and in finance industry, I think finance is probably, um, at the forefront of adaption, right?

They are kind of hyper frequency trading algorithms and all kinds of stuff are existing for a while now. And so I, when I moved from, and I was in Australia back then, um, but when I moved to states, um, I saw that even in United States, that was the first time in 20 10, 20 11, I saw the job market and the demand for those skillset were even quite higher.

Right? Um, and I really started kind of exploring like, what is next pivotal point in my career? Um, I came across a couple of folks, um, who were, who are still my mentors. Um, and really the guidance I, i, I got was, hey, data is becoming the, the new thing, right? The big data slowly becoming popular. And so I was looking into options and I'm twice PhD dropout.

Um, and, and so I was really looking like what would be my, uh, the, the, and I wanted to pursue PhD in, in the, in the [00:12:00] States. And so what would be my PhD? Um, uh. The, the, the what, what area I, I would specialize in, right? So computer vision or machine learning, and then a bunch of other stuff I was exploring and then. I came across around this DJ Patil era where LinkedIn and all, all of those data science things were becoming popular data science. Right? And I was like, this is the next new thing, next big thing for me. Right? I started taking lots and lots of different courses and learnings and whatnot, and I came across, um, Andrew Eng, uh, he was at Stanford, so I was taking some certifications, and this is again before he.

He co-founded Coursera. Right? So again, my interest continue to like, continue to, uh, progress and then kind of becoming more and more, uh, passion rather just becoming an interest, right? So that's how I started my journey on this data science AI path. And then I, I got into healthcare, um, after finance and I really liked it, right?

Like my skillset was really impacting people's lives. It wasn't [00:13:00] just right about the finance, but it was about like how it can help people's lives and fast forward in right before COVID in 2020, I had a personal tragedy that I mentioned, right? My dad was diagnosed with IPF, uh, the id, pulmonary fibrosis, IPF, and then. There was no cure. I was trying to figure out like how can, how we can help and whatnot. And he was back in India, uh, he couldn't even fly his, his,

um, yeah, condition got really worsened and, and so we couldn't really enroll him to any clinical trials and whatnot. And then COVID was. At the peak right around that time. And so yeah, a co a year down the road he passed. Uh, but that actually led me to, uh, this, this co-founding AI for purpose as well. Right. Throw me towards a purpose where if I don't have the medical degree and I can be the doctor who can have. Who can probably treat for those conditions, I at least can pay my, uh, or, or I can contribute, uh, to the society and, and, and kind of continue to drive [00:14:00] that innovation, right?

So AI for purpose again. I don't wanna share a personal story of my co-founder or the CEO, but she has also the, the same passion, same story, her personal health story as well, which is all over LinkedIn, but so we were kind of driven with the same passion. And then now with AI for purpose, that is giving us a purpose, right, to stay up in the morning. Keep, keep going until we, we really make something happen. We have right now four or five ideas, like early stage, mid stage ideas that we're working with and whatnot, right? That could impact people's lives in a big way. So that's, that's something I, I find like those are pivotal points of my career and hopefully that will kind of impact people's lives in a positive way.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: That's fantastic. I just want to dig in one in one area, because we're talking about real AI applications and real use of big data and talking about financial services. Having the lead on that, and I tend to agree with you in terms of maturity, but. I'd love to [00:15:00] just dig into one thing, if you can share, uh, you know, what surprised you most about the financial data analytics industry when you were there?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: I think the commonality is, is, kind of the, the, the explosion of the data and richness of the data. Now, even as technology matures and we. As, as the users, right? Generate more and more data, right? Or every single moment is being captured somewhere, right? Either financial or personal or social or, or healthcare related, whatever it is, right? Collectively that defines as a human right or a personal life, right? If there is a way to capture Phillips 360 degree view from whatever angle, right? It can help with the financial world decision making or it can help with the healthcare world decision making. Right. So I didn't see like a big shift in terms of the, the end goal, although, yeah, in, in financial it was a little easier, although it's heavily regulated industry, but it, it was a little easier 'cause people, people trust technology with [00:16:00] their finances, but people do not trust technology with their lives.

Right? Like life is a very sensitive topic. I mean, even if I had to make that decision. Right. Um. Putting the human health in, in, in, in kind of the, the grace of, uh, AI or technology, right? I would be reluctant to do that. Um, and, and so there is a skepticism or a little reluctance of adaption in my opinion. Finance is, is seeing this more of a. A value generator. Right. And finance is also always on the verge of like, or on the toe of, uh, being the, the early adopter, right? The early adopter advantage versus in healthcare it is more of the laggard, but they want to make sure that there is enough, uh, evidence, enough proof. Has anybody else done it? Right. So in, I have been in the life sciences for so long, um, worked with pretty much, uh, major, major of, of like fortune hundred of uh, or Fortune 10 even, [00:17:00] uh, classified pharma companies. But they, they always ask the same question, like, if I bring an innovative idea even within my group or when I was consulting to pharma, the first question they'll ask, which other company has done it before? Have you done it before? Can you send me a case study? Right? So they want to see the proof versus in finance, they're risk takers, right? So financial industry is more of a risk taker. Um, and so that's the difference Phillip, I, I see, um, in, in, in the both side of the world. Slowly but surely. Uh, the, the healthcare in general, right?

Not just pharma, but healthcare is catching up, right? Especially in diagnostic and, and, and other type of care. Yes, it is catching up quite a bit. Assisting physicians, um, note taking, et cetera. You can see all kinds of AI automations and I'm sure at some point you'll get into the agentic side of things as

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: There's a, there's a whole stink going on right now with Epic implementing,

uh, their own scribe opportunity and just [00:18:00] eliminating like a billion dollars worth of investments in, uh, HIPAA compliance scribes, which is kind of interesting.

riverside_alistair_lowe-norris_raw-video-cfr_the_agentic insider_0032: Absolutely. So, um, so Dhaval, from your perspective, you know, thinking of, you know, where your way from, from the chair that you are sitting in, how are you seeing, uh, the evolution of agen AI and the, uh, and the challenges where you see it can really be adding value? That, that that's that sort of opportunities to be, uh, to be addressed.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Yeah, I mean, evolution of agentic ai, um, yes, it is. I don't know. I mean, it's, it's exploding, right? So it's. And, and then, yeah, I, let me also clarify, and I'm, I'm sure you guys know it, but like there is AI agents and there is agentic ai, right? So there is, there is a, a, a solid difference, right? AI agent for plain, and I, I'm explaining this to, um, some of my non-AI friends as well.

Like when they say, Hey, what is this agentic? I, and then they interchangeably use AI agent, right? So I tell them basically that. AI agent is someone you [00:19:00] can train as an employee with a set of rules who can follow the direction, right? Like crab, a crab, two buns, put

a grilled chicken inside, put two, two pieces of, uh, tomatoes and a lettuce and whatnot, right?

And it'll, you'll, you'll get an, uh, a really good sandwich at the end. Right? So that's ai agent Agentic ai on the other hand, is, is more, it, it, it can. Kinda adapt that situation. Right. It, it can, it can probably track your mood and if you're not in mood to have a hamburger right, it can give you probably the, the food that you like.

Right. So that's kind of, I don't know if it's a, it, it, it's a little lame analogy that I use, but yeah, that's the kind of the point that I, I, I want to make to my non AI friends. But yeah. Jokes aside, ai agentic, ai, AI agents, there is a huge explosion and I know a lot of us, um. And, and, and I, I'm hearing from a lot of my friends as well, they are seeing AI as a threat, threat to their jobs.

And as, as you can see, right, all these headlines, right? Microsoft [00:20:00] Laying of Engineers and other like top. Technology firms and, and whatnot. And then it is penetrating or trickling down to some manufacturings and like blue collar jobs and low, low end jobs as well. Right? So, um, where this will go, I mean, yes, it's, it's, it's going to be a little bit of a turbulent, uh, path going forward.

But like I said, I, I'm more optimistic. With all this agentic AI becoming mature, like more mature and AI agents are coming along to help, right? So it'll rather Amplify the human potential, right? So you rather than being, um, just a, just an employee or, or just using chat GPD for your, for your daily task routines, even if you're a programmer, rather than doing that, you'll be probably spending your energy and your human brain, human power to something more meaningful, more intelligent, right?

So, agent DKI. Again. Yeah, I'll start. Um, it is [00:21:00] going to help the, the way we think, the way we do. Right. And right now, I, I think we are just, uh, scratching the, the surface or we are just seeing the deep of the iceberg. There is a lot more to come, um, in, in, in very near future.

riverside_alistair_lowe-norris_raw-video-cfr_the_agentic insider_0032: Yeah, absolutely. I mean, I think, you know, when you talk about the difference between agents and agent ai, I mean, I think if you, if you train an agent, you know, to be able to assist you, it wouldn, no matter, whatever your role is, and you have a series of agents to. Able to help you, then you are, you are moving yourself, um, you know, from, from less of the operator and the doer and to more the supervisor over a series, as you said, of, of AG agentic employees at that point.

But I think, you know, to, to really have, you know, a broad, um, a, a broad agentic AI approach, we're now talking about something where you can swarm large numbers Okay. Of. Of AI systems together in ways of solving these pharmaceutical healthcare, life sciences problems. Okay. And, and really hitting your, you know, your first pillar around innovation for your, for your AI purpose.

Really smack on [00:22:00] the.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Yeah, and I, I have friends in non-healthcare, um, field as well, like some of the small business owners right in supply chain and even shop owners, et cetera. They're also becoming more and more curious, like how they can embrace ai. How they can play with some AI applications. They've heard about AI agents or agent take AI for them.

Everything is same, right? Everything is ai and so how they can really start learning. So every social gathering is about that, right? Somebody has to turn on the switch about AI and then things go on, right? So how do we do this? How do we, so it is naturally raising the, the, the curiosity bar higher and higher, right?

Um, and like you said, the innovations are. Going to come, I mean, in all industries, healthcare being of course, uh, at the critical juncture right now, and I see. We, although, yeah, it is my own, um, assessment that healthcare being the laggard and then the technology adoption and AI adoption, but there, I see that they're also kind of coming, coming to the forefront to [00:23:00] some degrees.

I mean, they're adapting or putting, putting money to, um, in, in the, in the AI based research, AI based tools and then partnerships as well. Right. Just I was reading open AI kind of partnering and, and kind of. Pumping money into chai for healthcare innovations and whatnot. And so yeah, things are, things are kind of, yeah, going or firing on all cylinders, even in healthcare.

riverside_alistair_lowe-norris_raw-video-cfr_the_agentic insider_0032: Yeah, absolutely. And so, I mean, I, I, you know, taking a, a, you know, one thing I wanted to drill into, um, 'cause I, I love seeing that it was, um, it was something you were doing. So you are a program committee member for the European Conference on artificial intelligence. Tell us a little about why you decided to get involved.

With the, the, you know, European Association for ai. What was your, what was your reasoning for jumping on with that and how, um, how were, how were you looking to be able to guide it going forward?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Sure. Yeah, no, that's actually that involvement. Um, again, it, it, it kind of, uh, so, uh. My day job freed up some of my time. And then when I was transitioning from Sasa, my previous job and [00:24:00] kind of getting involved in more, uh, some social impactful stuff, right? And trying to spend my time into things that matter.

Um, and wanted to also see like at the global. Uh, global front, right? What are, what are the innovations happening, right? So that basically, uh, that, that gave me kind of a window in the European side as well. And it is, again, it is more of a, a conference planning help, uh, as a program committee member. Um, so there is a, a big conference coming up, right?

European, uh, the conference of, uh, artificial intelligence, EC ai. So I volunteered my time there, uh, both through NYU and then of course where I, for purpose, basically helping out, uh, picking the topics that, that, that are really either trending or futuristic, right? And, and, and also kind of, uh, helping with the selection of, uh, the abstracts and submissions.

And right now we are also assessing, uh, some of, uh, the, the final papers final, um. Kind of the presentations and whatnot that will [00:25:00] go in, in, in, in this conference. So really what I enjoyed is kind of seeing, right? Like of course it's a global event, so it's not just limited to Europe. Uh, but there is, you will see like it's, it's European conference, right?

So you'll see a heavy European, um, side like presence as well. So yes, US is leading the charter, US is leading the ai, uh, innovation, but European, uh, companies, European, um. I would say AI entrepreneurs. Right. Uh, they're also kind of at the forefront and really, I, I, I. Enjoyed pasta, I would say four or five months being, being part of that committee, uh, to see like the ideas, right, new ideas.

And then of course attracting, uh, some of the like global talent, uh, to some of these conferences was really kind of key as well. The. The one learning that I had was right. I was, up until now, I was in my own sort of small US-based ai. Well, right. I worked in some of the global roles before, but [00:26:00] especially in terms of ai, I wasn't really involved in much like at the global scale.

So here like hearing the perspective from the other side, other side of the ocean, um. And then kind of seeing what they see and, and where they see the application again, the, um, especially in healthcare, I mean, as you know, right? US is unique in terms of our health own healthcare system versus rest of the world. And so kind of seeing some of this, um. I would say equivalent or, or somewhat less advanced healthcare, uh, systems in, in the world. Like how they are seeing the adoption of ai. Right? Um, also this conference is not limited for healthcare only. So you, you will see like finance, supply chain, all kind of burning, uh, issues, right?

And how they're proposing the solutions, the papers, et cetera. It is kind of their gateway to, to kind of start the entrepreneurial journey or kind of take their products and and ideas to next level. So that is amazing to see.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: So you've got, this is like, you've got really a global perspective [00:27:00] on what's going on now, you know, with, with especially with doing the work in Europe, you're obviously interacting with businesses and enterprises and part of your work and all of this. In your opinion, what percentage are actually agent ready for agentic systems in your opinion?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Well, um, Phillip, that's actually a very difficult question, but if I had to do an educated guess, and again, yeah. Yes, I, I do talk to a variety of people, uh, variety of business, uh, background people or even business leaders, right? Um, and through AI Pur purpose, we are guiding, um, and, and advising few, um, organizations as well, early stage, mid stage organizations as well. I mean, they, they all talk about it. It is, it is, again, before I give you my percentage, right? That magical number. Um, or, or a range of that number. Let me take you back maybe 10 years ago when people were talking about data science. And like I said, I was early, early [00:28:00] adapter or kind of writing that. Data s train very early on everybody used to talk about data science, right?

And nobody used, nobody was doing it right. Um, or nobody was doing it right way. So we are in the kind of same mode right now where everybody talks about AI and agent ai when it comes to the implementation and kind of putting the governance, I mean, AI is one thing, but then, uh, productionizing ai, it comes with a. Bunch of stuff, right? You need to think through, right? These companies need to have a solid AI roadmap. They need to invest into technology or AI evolution wisely. They need to Also geopolitical situation, right? Like the geopolitical news is all around ai, right? Can you export the AI cheap or not? Can you even sell or whatever, right?

And then AI governance, right? So all those things, right? And companies are not ready yet. Um, many companies are still struggling. POC or, or creating an MVP is one part, but then deploying it and productionizing it, it's, it's a whole new ballgame. [00:29:00] And so companies, I don't think they're ready. So to give you that magical ballpark number, Phillip, I would say probably 10 to 15% or 20%.

I'm not really kind of downplaying that number. I'm sure for a lot of people that number would be quite high, but for me, just being the. Ready to, to kind of productionizing the AI agents agent AI or full AI workflow. They're not there yet, so they're still in exploratory mode.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: AI readiness is a big thing. It's not just the AI use case, it's the AI readiness that is absolutely, you know,

critical is, you know, data first. Where is the data? Is it, you know, how clean is the data? I mean, there's always, there's all the age old problems, right?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Right. And, and, and, uh, even if there is data, I mean, the, the problem though is with, with like the governance, right? Um, Um, and Mike. Like data science, career and, and when I started working, especially in pharma industries, right, we were working alongside with statisticians, [00:30:00] right?

Traditional statisticians. And they did not see this initial like data science explosion as a, as a kind of complimentary skill or, or they were always reluctant, right? And so there is that kind of, um. Community will always exist, right? Same thing is happening with AI in some industries, yes, everybody are kind of trying to see what we can do with ai, but when it comes to the, the, the putting AI for, for the usage or in production, there is a lot of reluctance, right?

Everybody knows that ai, gen, ai l lms, they hallucinate, they, they. Need to be trained on the right data. They need to have proper AI governance. I mean, more and more, um, awareness is coming, right? Like responsible ai, ethical ai. We'll see Chief AI officer roles are on the rise. Um, AI strategy, uh, are, are, are kind of highly shouted.

Uh, consulting helps in in management consulting and strategy consulting organizations [00:31:00] and how to really. Properly use AI is, is becoming still like one of the top things, right? So every company that I talk with right now, they have some AI exploratory fund. They want to test where they can apply this AI and I call it AI monkey 'cause it's still hanging in the middle somewhere. They, they want, they want to put this monkey on back of something meaningful, right? So it's. More at exploratory phase. And, and, and some companies, of course, there will be the winners, right? Um, those unicorns, they're already applying AI and they have been applying for quite some time, right? So some, some of these companies, we, again, we don't, we, we care about the, the major mass.

I mean, some of the, the, those tech firms have been using AI for quite some time now.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Right. As, as is as the automotive industry has manufacturing,

you know, financial services, et cetera. Exactly. So you're seeing some common mistakes that, that people are making. Right.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Yes. Ab

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: there,

what would some of those be?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: some [00:32:00] of them, I mean, the common mistakes, like I say, they are, without thinking through how to put the ai, um, in production or, or. Adapt the, the AI in more responsible way. Right. A lot of people are kind of, uh, seeing AI as a, as a board that is sailing so fast that they, they don't wanna miss it. So they are kind of just putting small bets here and there, trying different tools, different pla, different platforms, different um, even APIs, right? There is, there is like. Whole new, new gamut of like all these gen AI platforms, right? And the, the, all those APIs and platforms even that can help you become, build AI agents and then wrap it around with agent DKI, et cetera. So for explorations, I mean, I have done ton of explorations as well, um, in, in different, um, use cases. But putting that. In, in a more responsible ways and, and, and, and having a, a, a, like a solid AI governance wrapper around it, it has been a challenge. And [00:33:00] really when it comes to more compliant industries like finance or healthcare, right, you need to also make sure that. That, that governance layer is rock solid, right? So you are one, you are using the information, um, in, in, in appropriate ways, um, and also having checks and balances, right? So you just don't live human out of the loop. So how you can really kind of embrace this. AI plus AI type of, uh, system. AI is human intelligence.

AI is artificial intelligence. And then having this combined system in place which can complement each other, right? So AI can definitely, uh, parse through like millions and millions of records in, in a matter of seconds, right? Or even milliseconds, right? Um, and then human on top of it can supervise. Approve, disapprove, right? So they make the human needs to make sure. So again, creating this governance model I is also becoming more and more challenge, uh, Phillip. So what, what mistakes I have seen [00:34:00] blindly adapting to some of the things, right? And thinking through, without thinking through, right. How it can help what kind of, um, workflows, et cetera, uh, to, to automate or, uh. To even improve upon. And plus, uh, the companies are adapting some of these AI technologies without bringing employees in the loop, right? So employees are always threatened, right in the back of their, their mind, right? They will always see this AI as a threat. And so I think, uh, there is also a need, a solid need from early on, right?

To change the perception that yes, there will be some revolution. Transformation. I call it transformation rather than revolution. Some transformation. And employees need to also kind of embrace this transformation. They need to also be at the, at the forefront of, uh, learning about this, uh, AI or tools or agent ai, um, et cetera, and how they can really improve their jobs basically. And so, really. A few. I mean, I, I call it a framework and governance [00:35:00] in, in, in a kind of a nutshell, that needs to be really well thought through, adapted without kind of keeping the human out of the loop and even employees out of the loop, right? Because you wanna create a, a, a harmonized system where AI can live with our, our so-called dear human intelligence.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Right. So look, you know, we've seen the evolution and you. You've, you've definitely seen it in your career. You know, you're talking about transformation, going from traditional programming to data science now to agent ai and we're seeing all of these tools, you know, vibe, coding, this, vibe, coding that, and you know, the reality of it is, you know, in our opinion is it's great to go to rapid prototype, but you need to actually ha go back to that use case, right?

So. want to go back to where do you see autonomous AI agents coming to life First, wh which industry do [00:36:00] you think that's going to happen?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Um, I mean, in my opinion, I think the, those. Autonomous agents, it can help in pretty much all the industries, right? But if I were to choose the very first industry or kind of the kind of jobs where really the, the type of jobs that are really like rules based, right? Where they're defined to do certain tasks, right?

They're defined to do certain, um, gather information, making certain decisions based on certain information, et cetera, right? And then. As, as we talked about earlier, right, like creating these armies of agents and putting a wrapper around and creating more of like a pro project manager type of agentic AI workflow that is, um, going like those, those type of, um, setup and task will be the first to kind of automate, uh, with the auto, like with, with its agentic framework. Um, where I have seen is, um. Uh, like scheduling, [00:37:00] um, the, the notification system, Like the, the AI agents, and especially even in healthcare, I, I see more and more AI agents that that really kind of goes through thousands and thousands of, uh, records, research papers, right? Summarizing them, um, helping kind of gather information and, and, and really identify or tr help identify those needle or maybe needles in haystacks type of situations.

Um, and. Really kind of automating some of the low end work, um, lower level work where it really doesn't require too much of human intelligence rather than the labor itself, right? So administrative tasks, um, those are really easy to automate, uh, with, with AI agents and kind of really, make it more, um, perfect in a way that you are really like error prone.

It just follows certain rules, right? Based on the rules, it can make the decisions. And so those type of, I mean, it, it, it's, it exists in every industry as Phillip, so not just like one industry to begin with.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Understood. And then [00:38:00] is there, just the last final question for me before we hit the rapid fire questions that we always ask our guests, is there anything about Egen that excites you the most or the corollary of that? What concerns you the most that we haven't discussed?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Um, yeah, no, I think, uh, it's an excitement with a little fear as well. Like I said, um, the companies are still trying to adapt, um, and it is still fairly new. Um, although it doesn't feel like new, um, a, like the whole AI thing is not new anymore. Um, agen AI to my, um, opinion, I mean, it, it can, if it is. Adopted responsibly.

Right? It can really push the performance, the efficiencies all around, right? Um, it, it, it, it can, I mean, I, I was really, um, looking into some of the articles and, and reading around like how we can really apply even in healthcare research, right? So, um, for example, like going through this, this like blast. A variety of different data points, right?

You even just for [00:39:00] one patient, right? From lab results to EMR data, to, uh, medical claims and kind of trying to understand the whole patient record and then. Doing that for millions of patients. Right. And, and, and of course if, if there is a system available to do this in real time, how it can really help with the diagnosis and, and treatment decisions, right.

In real time. Now, that is, is something that, that we are kind of marching towards in, in healthcare systems or in like, uh, uh, patient care. Same thing for pharma companies, how they can really kind of. Do this faster drug discovery. Right? So having that discovery drug discovery assistant type of, uh, agent DKI framework where, um. It can scan like millions and millions of papers, scientific papers, and then databases, and then different data points, and, and really try and identify from anything from unmet need all the way to like the therapies that will respond to the type of people, et cetera, and really kind of helping humans. Or, or the human teams basically to, [00:40:00] uh, to focus on things that matter, right?

So avoiding or eliminating noise from, from this big plethora of information. And so there are, there are, yes, absolutely, um, solid, uh, use cases that are on the horizon. And like I said. Things are evolving much faster than, uh, we can imagine. And so I'm really excited to see like where this agent, whole agent AI will, will help going forward in research and bringing new therapies to market, improvising this personalized healthcare. Of course, on the other side, I improving supply chain, making sure that, that we, we, we kind of. Really adapt AI responsibly all across us, basically, right from automotive industries to supply chain to healthcare. And like I said, I have two young kids, so also to the education systems as well. Not just leave them on to check GPT, but have a properly covered educational platform as well. Right? And, and agent. AI framework could also help there [00:41:00] as well, right? They learn and adapt their capabilities and kind of challenge them and then improvise them. I know China is kind of at the forefront of adapting AI in their educational system early on. Right? I was reading about their, their elementary school curriculum is now embracing ai, and so of course this is again, like I said, scratching the surface.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Great. Awesome. Listen, rapid fire questions. What'd you like to do for fun?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Um, a bunch of stuff when I'm not in front of my screens, which I am kind of like mostly at least eight, 10 hours. Uh, I, I'm a marathoner, so I run, I spend time with the kids. I, I believe in physical health as well because AI is sc crippling the human health, if

not not taking care. Um, yeah, desk jobs and then kind of sitting in front of computers all the time.

So I. Try to keep myself busy with running, swimming, going with the kids sports, et cetera, but also try to keep my eyes open, right? Like where, where we can, again, apply some of these learnings where [00:42:00] we can even learn from, from the other side, right, from nature, from kids, whatever, right? And bring that learning into, into the daily work.

So that's where I keep myself, um, busy and that's what I, I, I love to do outside of the work.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Great. Well, and lastly, what, how do people get a hold of you, Dhaval?

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: They can reach me through LinkedIn, a bunch of them do my phone numbers and then emails as well. Right. So, yeah, I mean, and again, in person, I am trying to be at, at most of this, uh, um, conferences. I mean, lately I, uh, also. Started part being part of, uh, lots of hackathons and, and as my time freed up,

uh, we are also, we are also organizing AI for purpose, uh, organized events. We just had our AI workshop a few weeks ago in the New York City and, and yeah, I was able to connect with lots of new folks there.

Right? So it was open event for anyone to attend.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Patel, [00:43:00] thank you so much for being on the show today, and it's been wonderful having you on.

riverside_dhaval_patel_raw-video-cfr_the_agentic insider_0031: Yeah. No. Thank you so much, Phillip Lister. Yeah, it was pleasure to talk to you guys.

riverside_phillip_swan_raw-video-cfr_the_agentic insider_0030: Uh, to our audience. Thank you very much for listening and we'll look forward to seeing you next week. Take care.

Speaker 2: That's a wrap on this week's episode of the Agentic Insider. Thank you for listening. For show notes and more, please visit AgTech Insider Show. To learn more about Arids visit arids.ai. We'll see you next time.