How I AI
How I AI showcases the people shaping the future with artificial intelligence. Host Brooke Gramer spotlights founders, innovators, and creatives who share not just the tools they use, but the transformations they’ve experienced. Human-centered storytelling meets visionary insights on business, culture, and the future of innovation.
How I AI
How a Product Leader Builds Enterprise AI Agents
I sit down with Anuj Jain, a seasoned product leader who’s been building AI products long before the current hype cycle and is now shaping how enterprise AI agents work in the real world.
Anuj is the Head of Product at Nurix.ai, where he leads the development of advanced conversational and voice AI agents used by enterprises across customer support, sales, and internal operations. His background spans AI platforms, growth systems, and large scale enterprise tools, with early work leading AI product teams at Sprinklr during the first major deep learning wave.
In this conversation, we go beyond demos and buzzwords. Anuj shares how AI is being adopted inside enterprises today, why context engineering matters more than the model itself, and why AI is not a silver bullet but a system that must be trained, trusted, and evolved over time.
He also offers a fascinating look at how India’s tech culture is adapting to AI at scale, and how he personally uses a voice agent during his daily commute to think better, prepare for hard conversations, and challenge his own ideas.
🔥 Topics We Cover:
- What it really takes to ship enterprise AI agents into production
- Why context engineering is critical for reliable AI systems
- How AI is reshaping the workforce in India and globally
- Why AI should be treated like a new hire, not a magic fix
- How voice agents can be used for thinking, decision making, and leadership
- The future of enterprise AI, agentic workflows, and internal operations
Tools & Concepts Mentioned in This Episode:
AI & Product Platforms-
ChatGPT
Claude Code
Vercel
Enterprise AI & Agents-
Nurix.ai
Sprinklr
Productivity & Workflow Tools-
Granola
Cluely
Expensify
Connect with Anuj:
LinkedIn: https://www.linkedin.com/in/anujjain23/
Company: https://nurix.ai
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"How I AI" is a concept and podcast series created and produced by Brooke Gramer of EmpowerFlow Strategies LLC. All rights reserved.
So one of the key thing is that, AI in isolation versus AI, when it is integrated and part of a system, it has to be very, very well context aware. So let's say if we are building like customer support agent for an enterprise, it has to be very well aware about what is the current context of the business? Is there a sale going on? Is there any like, anomaly in the logistics or maybe what is my knowledge base? What are there things which have been changing? What is a promise delivery date? A lot of different data points, right? And all of these things, especially in enterprises, is not very well structured. A lot of knowledge in enterprises is trivial, like it still sits with in people's mind and not on some documentation. So it is very difficult to first ensure that enterprises are able to have the right kind of workflow documented, and then actually that context is given to the AI.
Brooke:Welcome to How I AI the podcast featuring real people, real stories, and real AI in action. I'm Brooke Gramer, your host and guide on this journey into the real world impact of artificial intelligence. For over 15 years, I've worked in creative marketing events and business strategy, wearing all the hats. I know the struggle of trying to scale and manage all things without burning out, but here's the game changer, AI. This isn't just a podcast. How I AI is a community, a space where curious minds like you come together, share ideas, because AI isn't just a trend, it's a shift, and the sooner we embrace it, the more freedom, creativity, and opportunities will unlock. Today's episode features Anuj Jain. He's the head of product at Nurix AI, where he's building some of the most advanced conversational AI agents in the enterprise world. What I loved about this conversation is how grounded and real he is about the state of AI. He gives an inside look at India's massive tech culture shift as AI rolls out across the country and he breaks down why context engineering matters just as much as the model itself. He also makes a powerful point that AI is not a silver bullet. It's a journey and the leaders who learn how to fine tune context will all win. If you're curious how AI agents are actually being built, adopted, and tested inside high growth tech companies, or just want a peek into the future of enterprise ai. You're gonna love this episode. Alright, let's dive in. Anuj, welcome to How I AI. It's so wonderful to have you. Hey Brooke. Thanks for hosting me. It's a pleasure. Thank you so much for taking the time outta your busy day. All of my guests that come through and join me from all over the world. And you yourself are joining from India today, correct.
Anuj Jain:Yeah, that's correct. I'm based out of Bangalore, India.
Brooke:Well, I'd love to take this opportunity to open this space. Can you share about yourself and how you ended up where you are now?
Anuj Jain:Sure. Um, so I started computer science from IT and then I worked as a software engineer for a couple of years. But then I realized maybe I'm not that suitable for the systems programming. I went to the B School and post that joined the product space. And that is where I was fortunate to start my career with Sprinklr, where I got the opportunity to lead the AI product team. And this is back in 2017 when deep learning was in fashion and started on this problem of how AI can actually bring any value to the enterprises. And in the next three years we just, build sprinkler intuition, which was the AI layer for sprinkler serving across different clouds like marketing, customer support, advertising, and build a lot of capabilities there. And that really excited me in AI at that time. Post that like I uh, wanted try things and on the consumer side of products as well. So I joined Cal Fit where I was leading the growth and platform charter and built multiple internal tools and also some growth hacks for the, for the fitness business to really scale in India. And then uh, did a short stint with a friend in a startup on the product side of things. And then right now I'm heading the product at Nurix. So Nurix is a conversationally AI agent company. I was pretty excited as soon as I got this opportunity because I was coming back in the AI wave and this is a much bigger wave to ride on, right? So, here we are trying to build primarily voice agents for enterprises across use cases like customer support, sales recruitment. Um, So yeah, that's our first offering on enabling enterprises in autopilot. And we have few more to come yet.
Brooke:Wow, you are definitely multi faceted, and I can see how you landed the opportunity you have now because you've worked in so many different departments, right, that you brought this cohesive knowledge together to bring you to where you are now. And what, what is Sprinklr
Anuj Jain:Sure, sure. So Sprinkler is again a B2B company. Um, Sprinkler started with the social media management part of, for enterprises like. For example, if Nike had a hundred different social media presence across 20 different channels. So an aggregator platform to manage everything from one platform. So that was the beginning of Sprinklr, but then it spanned into a lot of other areas. It used to market research through social media data advertising cloud. Then we had customer support cloud. There was a whole engagement cloud. And these were like the major clouds at Sprinklr. Uh. What I was primarily doing, there was more like a horizontal team serving AI capabilities to each of these different clouds. So we were building the AI layers, which used to help understand a lot of data, which is unstructured data, your text images coming from social media and provide insights to the brands. So that was one of the key. Parts of the research cloud. And then there were a lot of capabilities built for customer support. So we had like our co-pilots uh, helping agents being more efficient and being much more accurate on kind of responses they provide. And also on the advertising front, on bunch of algorithms around budget optimization and how do you actually serve your ads in a much better way so that you can get the best ROAS. So yeah, those were the things which we were doing at Sprinklr Fun times. Yeah.
Brooke:I was gonna say that sounds like a very clever name for a business and it caught my attention. And now that you described what exactly it was providing, it's a very clever name for exactly the type of work it produces. So thank you for digging into that more. So bring me back to the beginning. You said it was around 2016 when you started working in this space, and when did you know that AI was really gonna take off and it, it was something that you were really excited about and wanted to pursue working.
Anuj Jain:Yeah, so, I actually, when I was at my B school, I was interning at a venture capital firm, and there I got to explore this space of SaaS companies. And there I started seeing a lot of traction coming into the automation stuff. And then when I joined Sprinklr in 2017, and then I saw AI I just, I was mind boggled with the kind of technology AI was. And I could just relate to a lot of problems, which could be very much automated. Like. There were just too much trivial real work happening before that. And when we did a lot of these automated, a lot of these things at Sprinklr using ai, I could really see like how people could be best utilized rather than doing a lot of trivial work. So for example, right, like. Teams at one of the largest entertainment players. They were actually just going through like a hundred thousand messages on social media and trying to see which one should they even reply. Like, I mean, that was something, which was one of the use cases which we automated at Sprinklr, where it just gives you, which are the messages, which should be engageable out of this a 100k directly gives you, okay, those are the 600 messages to engage on. It's just a lot of time saving for the, for the brand and also much larger opportunity to engage more with the customers. So I think that was this time when I was really mind boggled with AI. Uh, And then we were like, I could also see there were a lot of things wanted to do on ai, which was not possible back then. So things like we were trying to automate how can you query a lot of structured data through just natural language. So for example. Okay. How was the sentiment score for Nike in September, right? So something like that. We were not really able to crack back then, but when AI came and like when GPT launched that was my second phase of being really, really fascinated by this technology. ChatGPT was game changer. And that is when I could see whatever things we were thinking back then into a live product now. And I think it has evolved much, much more significantly now. I think with Chat GPT 5.1 or five like it is very highly intelligent. And it is something where I think there is just a lot of user behavior has changed. A lot of people are not even searching on Google. Like for example, for me, Chat GPT has become my go-to app. Like for anything, it's not just like for work or for personal, but every single thing I'm, I'm using Chat GPT here and there everywhere. So yeah, I mean that was my story of fascination with ai.
Brooke:Thank you so much for sharing your personal experience, and I love interviewing people from all over the world. My next question for you is maybe you can kind of share a bit of the cultural landscape in India. Can you share and just describe how the tech workforce is there because it seems to be a very popular, maybe it's a competitive landscape. And also a second follow up question to that, how is everyone reacting with the rapid technological change with artificial intelligence? Maybe you're in a bit of an AI bubble yourself. Like I feel like I am sometimes here in Miami, but I'd love to dive into your personal experience of the tech workforce and, and how AI is shifting everything firsthand in India right now.
Anuj Jain:Yeah, great. Great question. So I think if you look at India's tech workforce, it's primarily a lot of IT services companies, which are based out of India and serving the world. And then there are a lot of, uh companies, which are global companies, but have their engineering headquarters, a large base of engineering happening out of India. So there is always that engineering talent, which has been based out of India but serving for the world. I think now. This whole tech workforce is essentially a lot of these are working on AI across different things. And especially like when I talk about how we are looking at it at Nurix we are serving both US and India markets. And India is much more nuanced because if you look at India like it, we have almost a hundred plus languages. There are so many dialects. There are so many accents. Because we deal with the voice agents, it is much, much more versatile compared to, let's say US where primary language is English. There's still some Spanish, but I mean the variety is much, much more in India. And then there's a lot of different kind of folks. The, we have a huge population, so you, that again gives you a lot of variety and versatility to focus on. So just the number of languages, number of dialects, all of those is one kind of dimension which increases the complexity in Indian market. The second is also like, uh, in general, AI adoption from an enterprise perspective is really helpful because in India there's always a competing force for the labor for, for people to actually like whether, what you want to have a call center, whether you want to provide support across 24 7 kind of services. So that is where I think India is still getting, adopting these technologies to provide the right kind of value for their businesses also, and even Indian companies, which are serving to a lot of, let's say, the global companies there, even in this, because of AI coming up. There is a lot of efficiency, which is built in and which these companies are working towards. So they can still charge the same, but their cost structures are going down. So the bottom line is really improving because of that. So that is the kind of change you would see in, in Indian market. And from a consumer point of view, those nuances make it more difficult for AI to to catch on. So yeah, that's, that's what I would say about India.
Brooke:You mentioned the competing force for labor. How is AI impacting the workforce now? Maybe you could even speak internally with your company. A lot of people are shifting having agent managers, having agents do a lot of the repetitive tasks. How can you speak on to the mass implementation and, and the workforce within India now?
Anuj Jain:Sure. So, let me start with some of the enterprises where we are working, right? So if each of these enterprises have huge growth goals, like they want to grow their revenue, grow their suppliers, vendors potential candidates, but they want to grow at a very low cost growth, and that is where even, whatever, let's say the human teams, they have for customer support, for sales, for qualifications, for recruitment, they still want to see how can these teams be much more productive, and that is where the angle of AI is coming and becoming very important that without increasing the cost on hiring more people to support this kind of an operation. How can we leverage AI to make these people also more productive and also do more like more impactful work compared to more trivial work? So that is one big change, and this is happening across domains like customer support. Uh, A lot of telesales kind of scenarios, which are like actually calling people and then qualifying the leads uh, to see who was, who is interested in the product or service. And then also some kind of recruitment use cases where, especially where you are hiring on a mass level uh, you want have to do a lot of coordination to ensure that you're getting the right kind of documents. The people are onboarded, they have the right kind of reminders. So all of these are the different use cases where AI is seeing a for great traction right now in India. And then even talking internally, I think internally, like we use uh, Newlix as a test bed for Nurix. So because we are actually into AI agents for enterprises we test everything, what we do in our company first and across these different departments, everybody has a mandate to create some kind of an AI agent to automate their work and be much, much more productive. And some of the cool things we have built, like one, one of the cool thing, which was built by somebody in the strategy team here was like a competitive intelligence tool. So it's uh, it was completely built over like Claude code hosted on Vercel. And he is, he is not even a software engineer. So building the full tool, which is like taking real time data from LinkedIn uh, the internet, and then ensuring we have a single view of the competitive intelligence that which of our competitors recently launch something where the customers, they have. So it's a very, very interesting kind of a phase. Just that is one example. Our sales team is using a lot of AI tools to be really prepped up with their meetings. This is another cool capability which we have built internally is the live meeting assistant. So you might have heard about Granola Cluely. So it's a, this tool is more of a combination of Granola and Cluely, like, what it does is, let's say if I'm in a meeting with you and you ask me some tough question, like, you asked me something about technology and maybe I'm not aware about it, but maybe there's, it is hidden somewhere in the documentation. So this thing this assistant is on the live meeting assistant and I have a help button. And when I do that, it actually, because it has the context, what question has been asked. It goes back to the Google Drive, it searches for it and gives me relevant answer with the link. So actually I can answer rather than just saying, okay, let me get back to you. Right. So all of those things are are some of those things which we have been using here at Nurix. And I think some of these things will be very widely adopted in very near future, across not just India, but across the globe.
Brooke:Thank you for sharing more about your current technology stack. I love asking that question. And it was interesting to hear how you're staying productive. Just yesterday I was in a workshop and I used Claude Artifacts for the first time, but I was given a very intense pre-written prompt for me to just kind of put in and see it work in real time and I, I have a free Claude account. I don't pay for Claude at the moment. And I was super impressed with what it was able to generate and create. And following our call, if you could share any of those tools that you just mentioned, I'd love to link them out in the show notes. I love to always expand listeners into different ways of exploring ai. Maybe someone was very lit up with that real live time answering system that you mentioned, and they wanna try it out. Beyond the technical side, how has working with AI changed you as a leader, as a creator, as a thinker, a lot of us are having to decondition the way we work and the way we think and the way that we produce.
Anuj Jain:Great question. I think um, since like being in this space. I think there's a constant change like every single day there is, there's something new happening that is very difficult to keep a track of everything, what is happening around you. Uh, And it is critical for us also to be aware of that. So that is one thing which where you again, use AI to know about ai. As a thinker also and as a leader, I think, these AI tools have been very helpful to me like, even when you want to have some certain hard conversations with some of your team members, like you can just do a very good rehearsal with the likes of chat GPT and Claude, you can be much more prepared. You can really have the right choice of words and all of those things. So earlier before having these AI assistant, it was a lot of mental exercise. you might, you know, talk to a lot of other people who have been in that kind of situation and you'll get a lot of different advices, but you still don't know. But here you can actually just have a very, very intelligent person who you, you don't have to care about anything else, like privacy or anything. And then you can just do a lot of bouncing off. Uh, So from that lens, it really helps you to become a better thinker. What I do, right? Like, hack for me, especially, you know, what I've done, I have like using the our platform itself i've built like a, a voice agent and I have a phone number to it. So whenever I drive from home to office. It's like a 20 to 30 minute drive which usually I was spending on, let's say some songs or something random. But now what I do is I just dial this phone number. And I just talk to it about whatever are the key things, which are in my mind. And I just do some brainstorming, okay, what do you think about this? Is this a good idea? Give me some ideas around improving this kind of a thing. So it just becomes a lot more productive. So that drive, which was very unproductive for me, has become much more productive. So that is one example. Uh, And as a leader also, I think just on a lot of different things, which are your blind spots, and again like using these assistants, if you type, I think that it still takes a good amount of time, but I, I use a lot of voice feature on all of these assistants and that really helps me to structure the thoughts better uh, Identify the blind spots. You really have to prompt that to the, to these assistants because ultimately, typically they're like maybe more agreeing with you, but then I prompt them to not agree with me and really challenge me. So, yeah, I think those are the things where AI has really helped me evolve my thinking, find my spots, and also like manage people better, do some hard conversations, really see the, all the different sides of a scenario before even going into it.
Brooke:Wow. What a fantastic case study. That's so genius to dial into your own voice agent as you're commuting to and from work. That's a like the most efficient thing to, to use that time. And I just love your thought process and your, your reasoning because you're right, there really is no right or wrong way. And it's, it's very unique and individualized. I think that's why I love interviewing people every week to hear how they have fine tuned their approach to ai. I also love voice and, and speaking and just the other day I was on. The stair master and at the gym and I was able to put together a whole you know, speaking point and thought process. And just this morning I woke up very early and had all of these amazing thoughts swirling in my head for a talk I'm organizing in a couple weeks. And so I decided just to record myself speaking for 20 minutes lying in bed. And that essentially is gonna be my talk in a couple weeks. So, big, big fan of recording and, and voice agents as well. My next question for you is to, on the flip side,'cause we just talked about many, many benefits and, and you talked about at the enterprise level and the personal level. Have there been any challenges to your AI adoption or processes? As, as a product manager and you know, someone that's really building smart AI tools and, and solving real problems. Tell us more about your experience, about any challenges with adoption and, and producing product.
Anuj Jain:Yeah, great question. I mean, uh, although we discussed everything good about ai, I think there are still lot of challenges for AI to go into production. There are a lot of quick things, demo kind of things, which can be very easily built. But when you have to do like a production grade kind of AI AI agent for enterprises, it takes a lot of effort. So one of the key thing is that, you know, AI in isolation versus ai, when it is integrated and part of a system, it has to be very, very well context aware. So let's say if we are building like a like customer support agent for a, for an enterprise, it has to be very well aware about what is the current context of the business? Is there a sale going on? Is there any like, anomaly in the logistics or maybe what is my knowledge base? What are there things which have been changing? What is a promise delivery date? A lot of different data points, right? And all of these things, especially in enterprises, is not very well structured. Like all, a lot of uh, knowledge in enterprises is trivial, like it still sits with in people's mind and not on some documentation. So it is very difficult to first ensure that, you know, enterprises are able to uh, have the right kind of workflow documented, and then actually that context is given to the ai. So that is one piece like in in one line, if I have to say it has to be really context intelligent so that context engineering will take a lot of time. You can't give wrong context, conflicting context. All of those things are important. Uh, I think the second thing is just from an expectation point of view, I see a lot of leaders trying to, you know, uh, leverage AI into their enterprises and different use cases. But AI is not like a silver bullet that, okay, I'll just implement AI and I'll just see a lot of revenue coming in or a lot of costs going down. It is still like a journey in which you have to invest continuously because think of this AI agent when going into production as a fresher, and then it has to learn uh, of the things, of the scenarios which are coming up in the real world situations, and then respond accordingly and learn accordingly. So it is a journey where you, let's say, deploy some kind of an AI agent. It'll be at certain level of accuracy or some certain level of outcome, but if you just judge it on day one. It's not the right factor. It is, has a journey of its own. It needs to continuously learn of different kind of scenarios, what to do and working with the business teams also, what is the right kind of like how to handle these scenarios. What is your workflow, what is your company's workflow? Because not like two companies, even in the two competitors, they will not do it in the same way. Everybody has their own brand guidelines. All of those things come into nuances. So don't expect it as a silver bullet, expect it as a fresher, you are grooming, but that fresher can actually be very, very highly leveraged and highly skilled in a few months of time, which can give you a lot of output. Uh, So that is the second thing I would say on the challenge where ensuring that everyone is, has the right kind of expectations. The third thing I would say is, what I've seen especially is the trust in AI. Like a lot of times I see okay, why did this happen? Why did AI give an answer like this and not like this? So there's a lot of traceability, auditability, kind of tools which are required for people to really understand what is happening behind the scenes rather than just like a black box, which they do not have any control over. People like to have control, so everybody strive for control. Okay I want to ensure that this AI works accordingly like this so I need to know why it was thinking like this. What are the changes which I can do? So that is the third thing. Which comes in, especially for the enterprise deployments. Uh, So that is on the enterprise side. I think apart from that, on the, on the personal front, also the, like, if you're using it for your own productivity context is pretty important. Uh, In addition to that, I think one of the key things which I've seen is uh, also like we believe that prompts are very simple, but then there is a lot of power you can unlock if you have like a prompt library for you. So I have like a prompt library, which is like a system prompt, and then I just insert the task in between and everything else is the same. And so that I don't have to give it context again and again, I don't have to mention about what I do, what kind of situation I might be in, what are the challenges so it already has a lot of context. So I, yeah, I would say those are some of the things which I've learned over the time. And uh, some of the advice I give to people when they're, they're starting on ai.
Brooke:That is very beautiful said. I like that you not only spoke about your challenges, but you turned them into lessons and learning moments and what the, the positive outcome of, of how you move forward differently. So thank you so much for sharing those three key points. I was resonating a lot when you were sharing about workflow context engineering. This is kind of like a hot topic right now when it comes to creating your prompt library and my most recent corporate job was working for a hotel. As the director of marketing and that's when I learned so deeply the importance of standard operating procedures and how there's so many managerial departments that have completely different jobs that are such a critical point to the, the hotel operations. I think that really set me up for success to get into the mind of creating SOPs for what it is that I do. And that's such a critical first point when you are creating agentic systems like you do. If you're tuning into this podcast, you're most likely an AI advocate, and you may have also wondered how to support your body against the invisible stress of EMFs. Think wifi, cell towers, or hours in front of your laptop. Lela Quantum products are lab tested in triple blind studies and are proven to help harmonize and neutralize EMF signals. Their products are the few things I felt a real energetic shift from. I personally wear their quantum energy necklace daily. And if you're someone who cares about optimizing your energy and nervous system like I do, explore their offers with my exclusive discount link below. My next question is more of a fun one you know, maybe you wanna share something that you're working on already, if you can, or it can be another personal share because it sounds like you're already very creative with AI personally, and I ask everybody if you could wave a magic wand also known as vibe coding, or just creating something with ai, a capability or a tool that doesn't exist yet, that would be a really amazing solution for, for supporting yourself. What would you wanna create?
Anuj Jain:That's a very interesting one. I mean, I, if I'm just thinking that right now, I, I'm still able to automate a lot of effort, which is, which is more individual work in nature. But what I still feel is I, how can I optimize on the time I spend in meetings? And I think that might be a universal problem with a lot of people, just like, maybe this is pretty farfetched, but if I can actually create like a clone of me, which has a very good context to how, how much I have and able to take. Simpler decisions in those meetings can attend meetings on my behalf. Give me notes. I think that would be great. Like where the other person feels at least I am available, but actually I am, I can work on some of the more pressing items. So yeah, like a, a clone of me, which could talk like me, which could look like me, which could do like a video call, like could do podcast maybe tomorrow with you. So something like that, maybe.
Brooke:I love this idea as you were talking because even just this morning I was emailing back and forth for an event I'm producing and obviously there's the people behind the ai, right? It's, it's our brain, it's our knowledge. We're the ones prompting it. But it's like very clear at this point that it's my AI talking to their ai and you know, taking it one step further of meeting bots and having your meeting bot represented in front of your colleagues meeting bot and making sure that their, their data and their context is all up to date. And essentially they just have to meet and exchange information. And then you have your, next steps and, and initiatives following that meeting. So. It's really fascinating to just to kind of like think again and going back to that like restructuring our mind and our workflow. And will probably be a day where we no longer have to actually attend meetings and our ais can represent us and talk to each other.
Anuj Jain:Yeah, I wish.
Brooke:Yes. We'll see. We'll see. It's only a matter of time. Speaking about the future and what's next, do you see enterprise AI and agent systems heading in the next year, especially from your vantage point at a Nurix ai? What's really exciting you most?
Anuj Jain:Uh, I think enterprise AI is, getting a lot of traction today because of the, some of the reasons I, we discussed earlier, right? Enterprises by default are designed to generate profit for their shareholders. So they have to really think on how to grow the top line and grow the bottom line as well, so. I think from that lens, AI has a lot of potential. There are a lot of different use cases which we, where we have seen a lot of traction. Like for example, software engineering itself, right? So there's the, almost every engineering team right now is using the likes of Cursor Claude to just be three x, five x faster. Uh, I think that is a great productivity boost. And the second thing, second use case, I think where we have like seen a lot of traction is also on these, all the call center kind of, call center operations. So doing, calls for like inbound customer support or maybe even out like reservations, recruitment. So I think that is an area which is really picking up. Even in the last few months we have seen a huge traction from lot of companies trying to, you know, try these new channels also because even if they were not trying, let's say voice-based or telesales kind of channels, now they really want to try because AI is available and they don't have to really spend in hiring folks, setting up, training them, all of those things. It's a quick POC even for a lot of companies to just try and see if this, this channel works for them. The third thing I think is a lot of internal operations are some things where a lot of companies are building for internally, and also a lot of companies are trying to sell to these enterprises. I think a lot of these common operational workflows, so for example, like a claim processing, if you have to do at an insurance company, it goes through multiple different steps. Multiple different people are involved. You have to do a lot of document processing and a lot of validation. Whether this is correct, matching all of those things, it's not a fraud. All of these things I think, ha, have a very huge potential to be automated with ai. A lot of workflows on the finance operations. Where, let's say somebody's just taking a receipt, like Expensify kind of tools where you upload and then somebody approves and then you get the your get your money back. So I think a lot of those things which are still trivial in hr, people are doing it because those are the necessary evils of the enterprise. I think those will be the early use cases, which will be pretty much adopted. And I think apart from that, one. One of the key trend, which I'm seeing in enterprise AI is that there is also a lot of willingness, which is coming up. At six months back there was a lot more uh, the risk appetite in enterprises was much lower, I think, which is increasing with time. So that will enable a lot of ideas to serve a lot of these startups like us coming up into the picture, trying to help these enterprises and see where like, what things actually are working. So I think these are the major enterprise AI trends I would feel, and I'm really excited about you know, solving for a lot of these work where I think people can do much more impactful work. So that is one thing which I'm really excited about.
Brooke:Thank you for sharing. It was interesting to hear just like the different verticals that you touched on from finance and, and, and digging into where they're headed. So my final wrap up question is always any one key takeaway that you want listeners to walk away from with this conversation.
Anuj Jain:I think I would say like I still feel there are a lot of people who might be hesitant about AI and thinking that maybe AI will take, take my job or anything like that. And also another myth I would say is AI is only for engineers or technical folks. I think that is one key thing I would really encourage people who is listening to this like it is, it is for everyone, and you just need to get your hands dirty. Like now everything has become so easy with ai it's purely the intent which matters. Don't be limited to what you, what are the skills you have today, but really try out a lot of these things. Try out your ideas, whatever you think you can easily build like a quick prototype through a lot of these AI tools right now. If you have some ideas, if you want to productive, like just improve your productivity, just think about every week or every day, like just one task which you think can be automated and just try out that. I think that will just, that 1% kind of uh, uh, one improvement per day or per week will really give you a lot of productivity boost and also will help you understand AI better. So as as career grows in future, like in two, five years, we'll see a lot more AI in the, in our jobs we'll have to maybe deal with AI agents and if you are early to this, you will be much ahead then a lot of other people who are not trying this. So I would say like, don't be afraid of ai. Don't be hesitant of it. Like just get your hands dirty and just get your intent right.
Brooke:I love that final key point, and it's so aligned with my mission, is really inspiring others to try out their ideas, build the quick prototype. It's very easy now, and that's really the intention behind the live events that I've been doing recently in Miami is Getting people to think about what it is that they wanna build and then partnering with colleagues that are gonna sit down and do hands-on workshops with them. It's really cool to see the energy and the momentum and, and real life. So thank you so much for again sharing that final key takeaway. It really hit home for me. And last but not least, how can listeners reach out to you? How can they find out more about your work? How can they connect?
Anuj Jain:Sure. So, I'll just share the links, which you can attach in the podcast and you can just search for me on LinkedIn. And I work for Nurix so Nurix.ai is the company URL. So yeah, you can feel free to reach out. DM me, send a connection request and I hope Brooke will share the links in at the below the podcast as well.
Brooke:Thank you so much Anuj. I don't know if you've ever been a teacher, but I feel like I learned so much today and I really appreciate your time and your energy. So thank you so much.
Anuj Jain:Thank you, Brooke. Thank you for hosting me. It was a pleasure to be on the show and I hope whatever learnings at least I had, could really help somebody. So looking forward to it here.
Brooke:Wow, I hope today's episode opened your mind to what's possible with AI. Do you have a cool use case on how you're using AI and want to share it? DM me. I'd love to hear more and feature you on my next podcast. Until next time, here's to working smarter, not harder. See you on the next episode of How I AI. Have you just started exploring AI and feel a bit overwhelmed? Don't worry, I've got you. Jump on a quick start audit call with me so you can walk away with a clear and personalized plan to move forward with more confidence and ease. Join my community of AI adopters like yourself. Plus, grab my free resources, including the AI Get Started Guide. Or try my How I AI companion GPT. It pulls insights from my guest interviews along with global reports, so you can stay ahead of the curve. Follow the link in the description below to get started.
