Neeti Mehta Shukla: Work without the busywork

Imagine telling a chatbot to “onboard this vendor,” and it finishes the job across multiple systems in under a minute. 

On this episode, we sit down with Automation Anywhere co-founder Neeti Mehta Shukla to unpack how this shift frees people from repetitive tasks and lets them focus on more meaningful work that uses their human judgment, care, and creativity.

We trace the journey from early RPA (robotic process automation) to today’s reliable, scalable automation that runs mission-critical operations. Neeti shares some compelling examples: 

• A nonprofit delivering 400% more aid after automating intake.
• An energy company saving $120 million via an LLM-guided tax review.
• Universities improving student services with faster, error-resistant AI-driven processes.

Throughout our conversation with Neeti, we get practical about the future of work. Some tasks vanish, many roles evolve, and new careers take shape. We also dig into responsible AI (privacy, governance, transparency) and why certifications like ISO 42001 signal that speed and safety can coexist.

Ultimately, the overall message is hopeful and grounded — expand access to training, bring more voices into AI, and build tools that serve everyone instead of just early adopters. 

Learn more about Neeti Mehta Shukla and Automation Anywhere:

• https://www.linkedin.com/in/neeti-mehta-shukla-511476/
• https://www.AutomationAnywhere.com/

aiEDU: The AI Education Project

• aiEDU.org
• linkedin.com/company/aiedu/

Chapters

• 0:00 Founding Automation Anywhere
• 2:55 RPA explained with real use cases
• 5:35 Agentic automation and vendor onboarding
• 9:15 Jobs, transitions, and future skills
• 14:56 Why coding still matters
• 19:10 Tech literacy beyond Silicon Valley
• 22:40 AI for nonprofits and social impact
• 29:15 Signals of successful adoption
• 33:45 Education use cases and student experience
• 38:20 Start small, prove ROI, and document your learning
• 43:30 Free training, certifications, and re-skilling
• 49:20 Practical advice for parents and educators
• 52:10 Responsible AI, governance, and ISO/IEC 42001

Transcript

Alex Kotran: 0:04

I want to make sure I'm pronouncing your name correct. Neety?

Neeti Mehta Shukla: 0:07

Neety? Nice.

Alex Kotran: 0:08

Niti. Okay. Can you give us your your spiel? What who are you? And maybe just tell us about sort of like your the the short version of your origin story for Automation Anywhere.

Neeti Mehta Shukla: 0:17

All right. So Automation Anywhere, uh, as we said, you know, we started in 2003. And um here who's our CEO, um, you know, we were we were thinking about it, and he was a big proponent of look, there's so much work being done with software, and we both were in the tech field, of course. And um, but there's so many inefficiencies, and it was very glaringly obvious to us that there's a lot of busy work being done. So if you take that moment in time, um, you know, uh software had been around, computers had been around for whatever, 30 plus years, and we had created all these siloed applications, and um that that really had enabled us to do a lot more than we did before. Um, but it needed kind of a reset to rethink and re-architecture how to get that productivity and efficiency to that next level. Um, and the mission of the company, right, from the get-go was how can we enable humans to do more and fuel the future of work? You you use those exact same words. Um, and that mission hasn't changed in 23 years. Um, so our our roots are from that point of uh, you know, we created that early category of robotic process automation at that point, um, which also had intelligence built in. And then about 10 years ago, uh, we started the uh you know mainstream AI applications within the within the platform and uh come 2025 at this point in time, it's a very mature, stable product that uh you know services obviously very many mission critical operations across many industries and verticals. So um the reason I bring that up is uh it it can be relied upon at it you know at uh at any level, really at this stage. So it's just a fantastic time uh for automation anywhere from where it's come to where it is. Um and we're very super proud of uh you know what the technology has uh done and it continues to uh do.

Alex Kotran: 2:13

Robotic process automation RPA. Um I think it's actually important for people who are you know I think beginning the learning journey about around AI and their starting point as large language models to understand that, you know, depending on your definition of artificial intelligence, like we've had a lot of the capabilities that I think folks assume, you know, just became available thanks to LLMs. But yeah, what maybe is there do you have like maybe like an example that you could share to help someone understand what RPA looks like? You don't have to give the actual name, but maybe just like an example of a type of company you might work with and and how they're like what are they automating essentially?

Neeti Mehta Shukla: 2:51

Absolutely. So um maybe this is a good example because it tells you um what is possible today, right? So uh RPA just gets the work done. And that was for us generation one uh of our platform, and we are at about generation three. Um let me kind of uh lay out an example that kind of shows you the breadth and width of what is possible. So let's say you are a company, one of the millions in many any industry or vertical, and you have to onboard a vendor. Something as simple as that, right? Uh and as complex because normally there's just a lot of different steps that you have to do to onboard a vendor. Any company has this process. Um, now, ideally speaking, what we what we would do today and what the agentic platform that we have today will do is you just come up to the agent and you say, I need to onboard a vendor. I could be sitting in marketing or HR or in procurement, it doesn't matter. And the agent would kind of figure out one, what are the processes within your organization? So it's already been trained using LLMs, using other things, um, as to what this company requires for a vendor to be onboarded, understands and is already trained on compliance and governance around based on where you are or the government or regulations and so forth, what is needed. And then uh the pitfalls or uh, you know, things that we have basically trained the agent to look for. Um and just by the person coming up, the human coming up and saying, look, I need to onboard a vendor, in less than a minute, that vendor, barring any complications that they have not submitted something, should be onboarded. Currently, that takes anywhere between two to four weeks. Now, if you look at that whole process uh being done in less than a minute, there are LLMs involved, there's natural language processing involved, there's RPA involved, because what our platform is able to do is not just spew out these other steps that you need to do to onboard this vendor, but it actually does that work. So it actually will go into multiple systems and do what it needs to do in order to onboard that vendor. And that's actually getting the work done. So, you know, uh, if you look at what agentic process automation can do today, there are components of it from all these different aspects that come together and really are is at that crucial point of changing how we do work, uh, not just talking about it or getting information about it or learning more about it, but all of it and then actually getting it done.

Alex Kotran: 5:15

I think folks are coming around to this question of like, okay, we actually need to understand like what does the future of work look like? And they're hearing a lot of I think rhetoric around like, you know, techno AI and technology is going to be replacing a lot of jobs. A lot of the like when I think about onboarding a vendor, that's I couldn't imagine maybe a more boring aspect of somebody's job. Like, I don't think there is anybody that is going to shed a single tear for, you know, not having to go through the you said two to four weeks of of time involved. It's like a lot of documentation. And what would you say to a parent who's asked this question of like, you know, how like how do I guide my my student? How do I guide my my kid? Should they still go to college? Like, is, you know, are there careers that are gonna disappear because of these technologies?

Neeti Mehta Shukla: 6:00

That's a really great question. Um, and there are many aspects to it. I'll mention a couple of them. One is history has taught us that no industrial revolution um is without the pain of transition. So um, if you look at whether it's the first or second or third industrial revolutions, and right now we're in the technological AI revolution, um, transition is hard. And so I understand the pain of, okay, what is happening? How do I navigate this and what's going on? Um, but understand that it is short term because we are right in the crux of it, in the middle of it. And that transition has always been hard. But what history has also taught us is any one of these revolutions has really unleashed a series of innovation and productivity for the globe at large, right? So any uh region of the world, any vertical, any industry has really been better off or has come with more ideas and more products and services and so forth. So those jobs will be created. Um, yes, but we are in that transition of moving from one type of job to another type of job, and some jobs are more impacted than others. Um, but I think it's temporary. I think it's within the next two or three years we will see that transition happen because some jobs are already absorbed by the AI, of course, but some jobs are getting morphed by the AI. Um, so like I said about vendor onboarding, if you're in a procurement team, for example, and you're not doing vendor onboarding, um, hopefully you're doing something else and making your internal customers' life easier, right? Um, look at healthcare. I mean, we have doctors and uh nurses who spend so much of their time, in fact, the majority of their time, on administrative tasks. Um, and I don't know a single patient who wouldn't want the doctor to spend an extra 10 minutes even hand holding or having that emotional connect if you're going through some health issue. Um and that's important. I think if the end goal of what technology can bring you and bring society at large is important enough, then um then it's worth that transition cost, if I may. Um, so that's one aspect of it. The second aspect of uh what you asked about is um, you know, um, I don't think knowledge is ever wasted. Um, and that might be coming from a from a view of a parent, maybe. Um, but you know, if you when you go to university and you study um and you put together the skill sets that you might have, and yes, we are again in that transitionary time, so you have to have continuous learning, you have to continuously upskill because the industry is moving faster than the speed of light at this point. Um, so yes, there is that transitionary learning that's also needed. But when you put all of that together, it makes the human again come at any problem um with a level of innovation, skill set, and tools that they never had before. So if you took take a take a chance or I mean, take a list of uh the biggest problems facing the world today, and there are so many, but take everything from um, you know, uh capacity planning or climate change or the productivity crisis, um, how are we going to increase GDP in most countries when the population is decreasing? And one of the ways is when you increase the productivity of each individual person, and these technological tools will allow us to do so. So, by and large, I think um transition is hard. We're in the midst of transition, so it feels a little bit more uh uh in your face. Um, but I think with the level of upskilling and the workforce development that we're seeing come through, um, I think we'll deal with it better than we have in the past. Uh, you know, my favorite thing to say is uh, you know, we weren't put on Earth to transfer data from Excel to a database that's really not the human's core strength. And yet, so much of our jobs uh in some capacity or another has this element because of uh how software has been built over the last 30, 50 years. And we have a chance to change that efficiency and productivity. And um it's exciting, it's new. I mean, we don't even know the names of the jobs that will exist in 10 years from now, just because the innovation of products and services that will come out of this revolution will be so extraordinary. Um, and all those will need jobs. So uh hang in there, keep up skilling, keep learning, uh, just like any every one of us has to. Um, but I think the promise of uh AI is significant.

Alex Kotran: 10:32

Yeah, uncertainty can be really scary. I it's worth saying that uncertainty also brings opportunity. And frankly, the more I dig into it, the more I feel like you know, students today are probably in a much better position than even like a lot of folks who are in the middle of their careers. Um, because you know, these kids are AI native. They just and the example I give is like imagine trying to teach your your parent how to like create an Instagram story. Um and then it usually clicks for kids because they're like, oh yeah, they could never figure that out. And yet here you are, sort of like throwing together all these like very it's I also struggle with Instagram stories. Uh so so but when you founded Automation Anywhere, co-founded Automation Anywhere, um this is 2003, this is like so that so computers had roughly proliferated, the internet was in sort of like the still middle stage of maturing, fiber had been, I guess at this point, overbuilt. Um, but there was, you know, there was like broadband was becoming more and more accessible. We didn't have, I think, any social media companies. I'm trying to think when MySpace was maybe MySpace in 2003. Not seven. So as you think back to what sort of equipped you to navigate, you know, what at the time was also a lot of change and disruption, but ended up being in retrospect, you know, tremendous opportunity. Yeah, like what equipped you to navigate that? And what, you know, even to get into a place where you were able to have the conversation with somebody about starting a company?

Neeti Mehta Shukla: 12:02

Um, that's an interesting question. Um, but I think just like all innovation, it comes from trying to understand what problem you're trying to solve. And uh, and then you just go after that problem. So if the problem in our case was how do we enable humans to work more effectively and really fuel that uh productivity gain that will come from that, how do we make them do more knowledge-based work versus manual work and really uh look upon it um as a as a way of working, uh a way of getting work done, then you find many ways to tackle that problem. And one of the ways that we focused on was okay, how do we create that level of intelligence so that the boring manual repetitive work, of course, gets done? And that was the advent of the RPA, and then of course, bringing more intelligence and artificial intelligence into it so that we can take it to the next level of um a really increasing productivity at an X factor. Looking at that problem consistently, constantly, and continuously, and learning all the different mediums that we can bring into that problem to solve it and make it most absorbable for the market, for the industry, I think is what fueled us. Um I hope that answers your question.

Alex Kotran: 13:20

No, it does. And and I yeah, I because I think what you're describing is it's really sort of at the heart of Silicon Valley and really advice that like all these startup founders are getting. And I think that there's a lot of folks who assume that, you know, being involved in technology means you're a STEM person, means that you're a hardcore engineer. Um I think what really draw me, drew me to you was, you know, the this focus that you have on social impact, which is a decidedly I think there's uh obviously a technology component to it, but it's also really bringing in the humanities and these questions of ethics. And and so I I I I'm curious like if if you like do you buy that, that this sort of like as we move into sort of this the next phase, like sort of the next technology revolution, that um you don't have to be a STEM kid necessarily to be able to identify those problems, to be able to think about solutions and sort of like have a role in sort of shaping the future.

Neeti Mehta Shukla: 14:14

Yes, and no. I think uh you you can be anything you want to be in this world. Uh I tell my children that, and I truly believe it. Um so I think you may or may not be in STEM, but what you need to be is somebody who looks at something and is able to solve for it. Um that's one aspect of it. The other aspect of it, and uh I am a techie at heart, I guess. Um, and I feel like it is a language, it is like English or French or something, you know, where you if you understand code, even if it is in a very basic way, it enables you to understand how to solve for certain things. So it's a it's a it's a mechanism that teaches you how to find solutions and look at a problem in different lights. Um so I would encourage everybody, uh, even if it's not native to you, just to kind of dabble in it, even if you can, you know. And then, of course, if you take to it, and I think as you put it, this generation is born AI native. So they are very, very clear on um how to deal with technology. And so coding might help or might not help them. Um, but I think uh that's important for me. But but career-wise, um, look, I'm not an engineer, but I do know how to code. Um, I learned to code when I was in high school, and I continued coding for HTML and other things for from a marketing aspect, which is what my career was in. Um, but it enabled me again to look at problems from different solutions and how to structure them, how to framework it, how to deliver it. And uh I think it has made me a better marketer for that. And then now moving into impact, um, I see uh, you know, we work with nonprofits and we have a huge arm of reskilling that we do. And what I see is that when when people are equipped with uh platforms like ours, um, they are able to do more as a nonprofit or they are able to get skilled, even if they've never I'll give you an example for reskilling. Uh, we work with refugees, and we have this one organization we work with who brings refugees out of Afghanistan. And uh, you know, the way it works is they they land in whichever country, obviously, that takes them in, and they land in Japan. Now, if you're an Afghan national in Japan, um, and you can hardly speak Japanese. So you can't work in the gig economy, you can't get a job at Starbucks, um, but you can talk code. So if you know a little bit of technology, and that's what we've done, we've you know worked with these refugees through these social organizations to help them upskill on our platform for about three months, and they're able to land a job, even living in Japan, uh, knowing of Ghani. Um, and so it's just it's to me, it's it's uh it's something that brings people together as well, um, and allows for collaboration and engagement at another level. So if you can, I think you must learn to code, uh, even if it's at the basic level, uh, understand STEM in that sense, and I'm using STEM very broadly here. Um, but it enables you to do more. So curiosity for that is important.

Alex Kotran: 17:17

And I find this fascinating because there's there's been a lot of rhetoric around, well, because large language models are really good at coding or writing code, that that's you know, I think there are some who are asking the question, well, do kids need even need to learn computer science anymore? And my intuition is actually that we're gonna see a lot more examples like the one you shared, where, you know, whether you're hiring a marketer or a, you know, a customer success manager or uh, you know, a salesperson, I think having the technical, the computational thinking skills, the computational literacy, also the problem solving that you build, that like the the coding is just a bunch of problem solving and iteration, like sort of like constantly. Um there's all these like durable skills in addition to the computational thinking that you build in CS, that it's not that you can't in some way get that, but it's just a very if you have the opportunity in front of you, it's just a very powerful way to build that. But that's like actually a bit of a contrarian take. And I'm like, I you know, because there's a lot of other CEOs of tech companies that are saying, yeah, you know, I wouldn't tell my daughter to bother learning computer science. And I I'm opposite I I'm I feel oppositional to that. Um and it's it's refreshing to hear that from you. I'm curious, like, have you seen it, you know, at your company? I mean, is there have you seen the value of coding decrease? Maybe like that might be one thing that we might if this is playing out the way some are claiming, you know, are are you starting to hire people that just have vibe coding experience without actually knowing CS?

Neeti Mehta Shukla: 18:47

Um again, yes or no. So yes, absolutely. We are seeing a lot of coding being auto-generated, uh, even at Automation Anywhere, anybody elsewhere, right? Um, but to your point, you know, let's look at a coding degree over the last uh 10 years, for example. Even that instructional educational uh curriculum is going to have to morph and change. So what you typically learned in a computer science course or a coding uh diploma uh might change a little bit. It might be the basics of coding and how to use these tools more effectively and then and then add a layer of strategic frameworking or prompt engineering or whatever else it may be to get it right. Um, but uh it's it's a little bit like, in my opinion, like math or art. Uh you know, math, art, literature, philosophy, uh, coding uh or STEM in some form or fashion, I think are all essential human skills that enable us to do better and understand the world around us better, and then produce better work uh product. And so having some element of it is important, whether it is at the exact same way it has been over the last 10 years, I think probably not. I think it's going to morph and change. And we're seeing universities and vocational training and continuous training change to deal with that. So the answer is yes and no. A traditional computer science coding degree from 10 years ago might not look the same tomorrow. It will look a little bit different.

Alex Kotran: 20:18

Yeah, it was uh f Philip Calligan at the Raspberry Pi Foundation and I had this conversation actually, like it was like two years ago. And I was asking him basically the same question. And he was like, Well, Alex, you know, we had, you know, GitHub and there were a lot of, you know, and Stack Overflow. And there's been like all these sort of advances that have made it significantly easier to code. You know, a lot of coding was, you know, it may not have been automated by AI, but a lot of it was sort of automated by, you know, just like, you know, developer operations and other process improvements. And all of those corresponded with an increase in the the value of computer science, not a decrease.

Neeti Mehta Shukla: 20:54

Correct. And it also increases what is possible. Because, you know, if if you were to do it the traditional way, I mean, I I look at maths, right? Like, I mean, if you didn't have the calculator, for example, and you had to do everything by hand, it is going you'll still do it, but you'll take that much longer to do it. And the fact that you have a co that you have a calculator and now a computer and now something else just enables you to do that much, much faster. And that allows you to actually uh innovate even more. You know, uh maybe there's uh there's that much more research in space because of that. And there's that much more research in biotech and healthcare because of that. So um it it it is about uh evolution of any of the STEM disciplines and uh the tools available to every human uh to get to the next level in that discipline.

Alex Kotran: 21:44

You you also meant you you said something that was important. It was you you you mentioned CS alongside you know math and and literature and sort of these other subjects that we I think consider to be sort of like fundamental to learning. Certainly when I was in school, uh computer science felt a lot more like a vocational track. You know, like you go into CS to get a job and at a tech company. Um and you said something that really stood out to me, which is like CS is a way of understanding the world around you, which you know, it's like everybody learns physics in school. And you know, it's it's I don't know that I use physics every day, but it is sort of I think like math. It's it's it's one of those things where there's sort of intrinsic value in understanding the world. Um to say nothing of the actual other skills that you develop in the process. Like how how often do you sort of like run into challenges with people even like being aware of you know some of the both like say the possibilities of technology or maybe the challenges that it poses? Um my sense is that we're really not quite, you know, I I think most people don't don't actually understand what's sort of happening. You know, they kind of like they have they have these magical tools that they use. Um, but I'm just from your vantage point, I'm just curious.

Neeti Mehta Shukla: 22:55

No, absolutely. I think uh you're right. I think like we live obviously in Silicon Valley, and so um we see the world with a with tech glasses, if that makes sense, right? And we see everything and understand the technologies behind certain things or how complex something might be, or how how uncomplex it might be, or simple it might be. Um I think um, you know, the more products and services um utilize these new technologies. So I'll give you an example. If you're a farmer, let's say in rural India and you're utilizing AI to figure out automatically what the uh water requirement of your uh field is, um, and it's it's on a day-to-day basis using satellite imagery as well as uh soil sampling and a hundred other things, which you couldn't do before. So you would you would understand the value it provides, you understand that the science behind it. You may not understand the full science behind it, you may just look at it upon a tool that delivered for you. Um, but you have to engage with that tool. You have to engage with that science and you have to understand and be part of that ecosystem. So the more products and services that you utilize, and I think we already do, right? From healthcare, biotech, pharma, uh, logistics, uh, governments, I mean, um, across the board, all these services now utilize tech in some form or fashion. Um so whether you are an end recipient of that and you understand that there's something behind it, and that might be the most rudimentary way. And then, or you're a scientist or you're a tech uh technologist in Silicon Valley and you understand it fully and wholesomely, um, I think there's always a range. Um, but I think the world is understanding that digital and technology is an integral part of a lot of things we do now. Um, you know, I mean, look at the mobile phone and what it did, you know. Um and if you if you look at uh there's there's an example always from Africa that says uh they never went through the ATM revolution because their banking went, you know, leapfrogged and went straight into mobile technology. But they understand that there's tech involved there. Uh, and they understand that the value of that tech that they bring. So to some extent, I think they understand it. Uh they may not comprehend it fully. Um, but I think people people by and large understand that there's value to be had from this.

Alex Kotran: 25:15

Yeah, and and like like on that thread, there's you know, as I've been thinking about sort of like how to talk about the future of work and the future of let's say, like, let's say tech jobs. Um, you know, one one thing that I've heard people raise is this uh the Jabins paradox, this idea that like as the cost of certain commodities comes down, you actually see an increase in demand. Uh and that was the case for like vehicle fuel efficiency standards. We consume more gas as fuel fuel efficiency went up, um, because it was people more people could then drive and you could drive further. And I I think about small businesses, which like right now in most small business, you know, the the cost of having a team of an engineering team is like astronomical. You know, like and you need a front end and a back end developer, then a system architect. Um if in the future we could have engineering capabilities with, let's say, one or two people on staff instead of like five or six or I don't even know how many dozens or maybe even hundreds that your company employs. Um I bet there's a huge long tail of s of businesses that actually could do a lot with um an engineering team that had, you know, that was sort of augmented by AI. Um are you seeing a bit like are there any sort of signals that you might be seeing just from automation anywhere's work, like or businesses that maybe people wouldn't expect to be technology forward that are able to kind of use these tools?

Neeti Mehta Shukla: 26:41

Absolutely. I mean, um, you know, I work uh in the impact side, uh, on the impact side and uh obviously with a lot of nonprofits and um, you know, I I feel uh uh you know, nonprofits, the the requirements that have come to nonprofits over the last 10 years has just been phenomenal. So whether it's from a capacity perspective or the speed of delivery, for example, if you're uh, you know, if you're the Red Cross and you you there's just that many more natural disasters, there's that many more wars, there's that many more people that you have to serve very instantly, or um, you know, uh, et cetera, right? So the the demand, healthcare, I mean, you just name any nonprofit from education, right? The capacity requirement is just double, tripled, quadrupled uh in very short periods of time. And uh so when they embrace technology uh and there's a light bulb moment when they realize um how it can help them do more because they're so mission-driven, obviously, um, and they want to kind of uh uh accomplish more towards their mission. So I'll give you one example. We work with a nonprofit in India uh called Akshay Patra, and they are they they provide uh food meals, the the lunch meal for about uh 2.4 million children every day, every day. Um, and they run 70 kitchens around the world, etc., etc. Now, their requirement is that within five years they've got to hit five million children. Um, and so now how do you build that? Uh, you know, you can't just throw money at a problem and make it happen because there's just so much other things going on. Uh, not to mention capital is hard to get as well for nonprofits, and grants are hard to get. Um, but we we work with them in order to increase the efficiency and productivity of that, uh, of their entire operations right now. And we're hoping to kind of uh help them to get there because we can get faster productivity. So, whether it's grant management, vendor management, fleet management, supply chain, there's just so many things that they have to do that we can directly impact the bottom line of a nonprofit. Um, and so we're seeing, and once once you have somebody in their leadership who understands, of course, this has a vision behind it, and then they see the value or the ROI that uh a tech company like ours can deliver to their uh operations, then they immediately obviously become believers, but they have a plan of action. Okay, we can utilize this in order to get where we want to go. Um, and that's that's significant. Um, another example I'd like to give you would be um, you know, a smaller nonprofit that we work with. Um, they're an aid agency, stepped with hope. Uh, in uh, you know, they basically set up these aid tents in war areas or you know, where IDPs or refugees can come up and basically request uh diabetes medication or whatever. Um, and we helped automate the intake process, and they were able to deliver 400% more aid at any given time than they could before. Fantastic opportunity. But that was not the cool part. The cool part was the humans on the ground who were not tech native, the volunteers on the ground, realized that, okay, now that we've automated this process, we are able to get the results obviously very immediately, and we're touching three systems. So why are we not flagging for trafficking victims when they walk in through the door? So if I walk in through the door with a 10-year-old child and ask for aid, uh have I actually filed a tax return with that child, et cetera, et cetera, right? So um now again, uh not tech native uh understands the value that is being given and is able to innovate and deliver so much more uh to humanity and society because of how they think and innovate around it, right? So um I think we're seeing across the board um a lot of organizations. And of course, the corporate side is uh is uh well documented. But um I'll give you one more example from the corporate side, which I found very interesting. Um we have a large uh energy uh company that's a customer, and their tax department decided to, you know, create um an LLM, an agent, uh that, and they fed it the entire tax code of uh Brazil. It happens to be in Brazil, um, and then had a human at the helm, you know, basically take care of uh ambiguities and things like this. And then it fed the agent the tax filing that they had for the year. And then the agent was able to spew out basically areas to re-relook at and find and decide. And they were able to serve $120 million in savings in three weeks end-to-end. Again, cool part is that $120 million that that energy company saved, hopefully will go into clean energy RD, because that money otherwise would not exist for that program. So um, again, just fantastic use cases of again, uh call it human innovation, of how to use these technologies to get to that next level. Uh, and yes, we see it across the board, small businesses, large businesses. Um, we have uh one all-volunteer organization in New Jersey, um, Jersey STEMs, they run a science STEM program for after school for kids in New Jersey. Um, and uh they automated quite a few of their processes. And given its volunteer run, those volunteers were then able to do a lot more than they could before, of course, run more programs in more schools. Um, not to mention, when a volunteer joins, again, they're not joined to transfer data between Excel and the database, right? They want to kind of do the more touchy-feely and emotionally high um uh work uh that is involved. Uh so fantastic and so many use cases. And this is just with our technology. So imagine all the other technologies and innovations that are coming out and uh what can be done. It's uh it's an amazing time.

Alex Kotran: 32:35

It's funny because you don't hear about these stories as much. I think we hear a lot about you know companies that are replacing people with AI. And even that, I'm there's a lot of fuzziness to the data, right, in terms of like what how much of that was actually like people being replaced versus just sort of cyclical layoffs. Um and and I think we hear about you know the frontiers of science. So the idea of AI maybe helping cure cancer, um you know, things like Alpha Fold, like what you're describing is, you know, in some ways, some of the more boring stuff that happens in the background, and yet, you know, when you're talking about a 400% increase in uh, you know, like scale and impact for nonprofit, I mean, most of the time achieving a 400% increase corresponds with raising 400% more money. I mean, like it's really hard to grow like that. And what are there any sort of common threads? Do you think about some of these different organizations that you support that that sort of are are sort of like strong, maybe leading indicators of their ability to like harness the tech technology really effectively? I mean, does this come down to like different individuals within organizations or sort of innovation culture or cultures of innovation?

Neeti Mehta Shukla: 33:44

Um absolutely. I mean, there are many things, and many things put together can make great success or great failure, right? Um so absolutely. I think we call them uh champions within organizations who want to kind of embrace a new technology or understand it and see how it can be applied. Um, definitely that helps. Um, I think what also helps is um when a customer um doesn't necessarily go after, see, when you're trying something new, um you don't want to go after the most complex problem uh because your teams are not ready to tackle it. So if you go with a with a with a good starting point, a leveler in a way, um then you have a better chance of success. So you get quick early wins so that the team one understands what's involved, uh believes in it, um, has then you know things fall in place, there's this uh collaboration and you know computation within the organization that has to happen. And then you can tackle a really large problem. So sometimes we see that uh uh make a difference as well. Um then yes, absolutely, there's internal change management that's required in many cases if it's a very large organization and people are worried uh because of uh, you know, the job losses that are coming or something like that. And some of it might be true, as you said, and some of it might actually be just uh, you know, being attributed to AI, but it's something else uh within the organization. Um so definitely some level of change management. And I find that organizations that do a lot of training for their employees on new tools and new software and make them comfortable with trying them out, uh, have better success of it. Um so all of the above, in a way, um, can lead to success. In a nonprofit's case, uh, it's a little bit uh I would say nonprofit and healthcare. Um, they're both areas where we see that the mission is so strong within the organizations uh to obviously provide service in some form or fashion, um, that is as long as they know that this is going to enable them to achieve their mission better, faster, easier, then they are believers. Um, sometimes not tech native. So there's a little bit more hand-holding or more training that's required. Uh, but they also have the biggest ROIs.

Alex Kotran: 36:06

Aaron Powell Are there any examples of nonprofits that you think we need to be doing a better job, sort of like bringing them into this sort of like spirit of innovation? Like maybe there's like untapped opportunities for social impact. And and perhaps even at the latest advances in sort of AI technology, you know, might have enabled that were it were it possible, you know, five years ago.

Neeti Mehta Shukla: 36:27

I mean, all of them, if you ask me. Um, you know, uh but but that's my tech hat uh talking. When I wear my impact officer hat, I I feel for them because um they're, you know, these are fantastic people who so clearly believe in the mission. Uh anything is a distraction if it's not mission-driven, you know. So to some extent to pause what you're doing to get your tech stack ready or work on the back office integration or work on application API or whatever else it may be is hard, you know, and I understand that. Um it's not easy, and I'm glad they do it the way they do it because they serve us better by doing it, serve society better by doing it. Um, but having somebody in the organization who um who is tech driven is important uh in these cases because again, from our vantage point, we feel the ROI is, you know, I mean, we're talking two, three months of ROI, not even um, you know, not even a year, two years or five years, which was traditional, right? For a lot of uh software development uh to provide ROI if you had if you had to hire an engineer and have him code something for you, and then that, you know, by the time it actually gets to market for that nonprofit, it used to be a two-year time frame. Uh now it's two months, three months. So um I think um talking to them more, enabling them more, having volunteers who understand tech contribute to them more, uh, many ways that uh that it can be um uh achieved.

Alex Kotran: 38:05

Now that makes sense. Are there any um you mentioned one use case in education? I I was curious if there was any others. You know, we we work with a lot of a lot of peer nonprofits, but also a lot of schools. And this this question of like what are the ways that you know AI can can support learners is coming up more and more. Well, this is a STEM program in New Jersey, I think you had brought up.

Neeti Mehta Shukla: 38:26

Correct. Um we work with so many academic institutions. So um, like in the US, we work with the University of Florida, we have UMish, uh, Carnegie Mellon, we have about 160 universities worldwide. Um in, for example, in uh um Australia, we're working with RMIT and University of Melbourne. With RMIT, they had a goal of uh improving student experience. That was their goal. And what what are the things we can automate so that students have a better experience? And uh I don't have all the use cases uh at the top of my or the tip of my fingers, but there's a there's a case study on our website that talks about it. Um and it's it's about that and how they are improving student experiences by making sure they're responsive, uh they're quick to deliver whatever they have to deliver to the students, uh, you know, financial planning and if you're if you're dispersing scholarships, um, how do you get that faster, better, without errors? Um, these are all things that make or break a university's um operations, and uh we are part of it. Um and there's just a plethora of institutes that uh utilize uh automation and AI in the regular operations, even in the intake process, and so forth.

Alex Kotran: 39:43

Yeah, I I think a lot about you know, schools are especially in K 12, you know, they're always struggling with um, you know, how to engage stakeholders, especially parents. Um they're also struggling with student engagement and just you know a a worrying number. Of students are not showing up to school. And it's kind of across the board. It's you know, it used to be that like underperforming students used to do that. And now there's even, even you know, good students are just like, they just like, I don't see the value. I think schools often have traditional mediums, like channels to communicate, like you know, you have a newsletter, maybe a bullish board literally. And what you're describing is a thing much more like responsive uh in like sort of like real-time systems that can, you know, especially with like I'm thinking about like parent back and forth. Like a lot of teachers' time is spent just responding to parents. What I mean, what advice would you have for a, you know, a leader of a nonprofit, a school? Um, if they're thinking about, okay, how do I want to get myself set up so that we can be one of those exemplars that, you know, whether it's automation anywhere or sort of like any technology provider that can come in? You mentioned having an internal champion. You mentioned training. Is there anything else? And maybe it's that simple, but is is there anything else that you would you would share? And and I I say this as as myself, someone who's, you know, trying to figure out the answer to that question.

Neeti Mehta Shukla: 41:01

You know, I mean, there's no two institutes that are alike, uh, only because uh there's just so much of uh differences in the way they operate or the culture um and uh how they're funded and other things, of course. But um again, I think if the end goal, it's just like any other institution or organization, if the end goal is very clear, um, like let's say you're saying I want to increase student experience, uh, speed of delivery by 10%, um, then that that goal setting is super important because I think that it allows you to go in one direction versus um doing a hundred things and not seeing the benefit come through. Um so I think that's important. So strategizing around it uh is super important. I think the ROI will speak to itself very quickly. Um at least in our platform, we see that uh the aha moment come very quickly once they start the journey, because you're like, oh, if I could do this, I could do five more things and I could do 10 more things. And um, they never want to go back to the old way of doing it because they see the value, of course, but they become more human-like, in my opinion, when they stop doing uh things that AI can do, which uh which is uh interesting and beneficial. I'm trying to think uh bringing it into the curriculum is important, I think, also, because again, you know, at like for automation anywhere, for example, we use our own product and we call ourselves Customer Zero and we document what we've learned and the ROI we're we're seeing and how it portrays and so forth. So when you self-learn, uh I think you bring out a better product or solution. And so if any institute also is learning themselves, uh training their students or training their professors on it, then that that also comes back into that ecosystem, you know. So um many things that you can do there. Uh and the larger the organization, obviously, the more processes and more compliance and governance and more everything um which can be done well.

Alex Kotran: 43:00

Yeah, I like this idea of starting small and picking something where you can and what you said is important about this, like RO, like seeing the ROI in just a few months, because what you need is even if you have your champion, you know, you want to be able to win up win over the rest of the organization. And that and it's you you want to point them to something measurable and tangible. I think part of the challenge with large language models is they are they're so multifaceted and multimodal. And um I think there's a sense of and also I think very high expectations that were set, um, certainly a year ago. And so I think people have this assumption that they need to be going in, like truly transforming uh or placing entire jobs. And what you're describing is is much more tactical. It's like, you know, find something just like that that and the fact that it's boring maybe actually is gonna be important because people will that's not gonna be a a task that people will will ask, oh, is this something that a human should be doing? It's like your example of like importing an Excel spreadsheet. Nobody wants to import an Excel spreadsheet by hand, obviously. Yes. And then this idea of like documenting learning is I I wish that more orgs were doing it because I you know, right now the challenge, you know, for AI EDU is as we think about our own digital transformation and we go to look for examples. Um, we can find orgs that have done it, right? But then you you try to understand, okay, well, how did you how did you get there? And it's like, well, it's actually kind of complicated. And we had, you know, like a look, you had someone on our C suite that was like really pushing this, but then we also had, you know, we internal learning groups that sort of met. And um I always I there have been a few times where I think to myself, I wish they just literally like documented all of this and and now you can just put it into an LLM, I guess, and probably ask some questions. But you described it as not just documentation for the sake of sharing externally, but also as a as a process for encouraging learning, which really makes sense. It's like even even if even if you're automating things, you you also want to be building expertise across the organization, um, being more tech forward. No, this is it's very validating to be honest, to like hear uh and I think it's important that you've been doing this work, you know, before Chat GPT. So it gives you credibility. Uh this is not just like some new thing that you're trying to pitch, like this is proven. Correct.

Neeti Mehta Shukla: 45:19

Um, and you know, um, I was gonna say that uh but with the Impact Office, even when we started our mission anywhere, one of our key factors was okay, if we really do believe in this uh the the way this is going to work out and how industry is going to use it, and we do believe in reskilling and upskilling, then how do we make sure that everybody can become part of that ecosystem? So there's again the strategy aspect of it. And so what we've done is uh we have something called Automation Anyway University, and we put in all our impact um funding into creating uh bite-sized learning that's free of cost, um, that can be taken by anybody, right? So it can be taken by university, it can be taken by a social um uh learning uh platform for refugees. It just doesn't matter. It's free of cost, it's there, it's bite-sized, you can take, play, do whatever you need with it. Then we also realize that uh, you know, like most people, uh, people have to have the uh chance to play with it. Otherwise, it's just like watching a YouTube video, it's not gonna help you, you know, after a while. You really need to play with it. So we have a free licensing model as well that people can use. Um, and then we have instructor manuals and things like this. But our our strategy was let's take away the barriers to learning. And let's take away any barrier for anybody in the world to really become part of the tech ecosystem as much as possible by automation anywhere. Um, and that has been, you know, really successful for us. Um, and very good uh results uh coming out of the academic institutions we work with, our own community of partners and customers, and also these impact learners that we have, right? So I think coming at it from that strategy uh has been important for us and hopefully is helping make a difference in the community.

Alex Kotran: 47:06

And you have like you have three certifications, right? It's like Essentials, Advanced, and Master. Correct. Um, is this do you have to have a tech background or a computer science background?

Neeti Mehta Shukla: 47:16

Oh, I tell the stories I can tell you, Alex. Um, they're the these are the human stories that touch your heart. I, you know, we like I said, we we trained one uh lady who fled the Ministry of Education in Afghanistan, landed in Japan, had to suddenly uh, you know, find a job and keep her family floated in Japan and uh learnt our systems in three months as a working, talking, um, learning uh model now that she manages and does and um has a great job. We had one person, so we set up an RPA Center of Excellence, an AI Center of Excellence uh in the Mississippi Delta with another social partner, People Shores. Um, and we've had use cases there where people were literally for 15 years flipping burgers at McDonald's because that was the only employer in a 200-mile radius, go from there to a 120k job because tech can be remote. And it once you get trained, uh, you know, uh we've had single mothers, uh, it's been a great one because if you have bite-sized learning, for example, I don't know a single mother who can take a year off um work in order to train herself and also provide for the family at the same time. Uh, but bite-sized learning allows her to do that, and then um she can land a job in three to six months. She was uh employed and uh didn't have to work nights and et cetera, et cetera, better, better, better life for her and her family. But it lifts the entire community when something like that happens. So just fantastic use cases all around. We've had uh amazing stories uh of courage, uh, of uh persistence, of uh wanting to really be um trained in this. And uh they always uh surprise and uh uh inspire us so much.

Alex Kotran: 49:04

I think that's really important. It's like because only what I think sub 4%, maybe even less, 2% of Americans actually work in you know technology fields. And so a lot of the folks who are gonna be, you know, navigating through disruption and that they're not tech people. Um but I think you know, the these these certifications you you mentioned, like bite-sized learning, it it it feels like it's gonna be more and more important as there's more disruption. Because like to your point, like there's gonna be, we don't know what the jobs of the future are. Like the one thing we can bet on is there's gonna be just transition of some kind that people are gonna have to be reinventing themselves to some degree or another. And not everybody necessarily the single mother is a great example of not everybody can just go back to college. You know, that's that that will be a solution for some. Yeah, Niti has been this has been really awesome. Is there anything else that you, you know, that you would share, and especially with an eye towards, you know, the folks who are listening in are you know, I think it's a mix of parents, it's it's educators, and it's also decision makers within sort of like the education apparatus that are, I think, feeling a bit overwhelmed by all of the um Yeah, all of the change that's coming and and and maybe looking for some, you know, either a hopeful or at least a instructive message to kind of like help them figure out what to be focused on.

Neeti Mehta Shukla: 50:11

I think uh I think knowing that the industry is undergoing this transformation is an important uh understanding and learning it is important because um then you understand that it's temporary or it's short term. Um I I, you know, in three to five years, again, the number of jobs that are expected to increase is uh two million more jobs, is I think what the jobs report said from World Economic Forum. Um and so things like this, but it it is a transition. So knowing that I think helps. Two is I'm a big believer, and this may be a personal belief, but uh, no education is wasted. Um, somehow, somewhere, it all comes together in how you uh perform, whether it's a job or uh for innovation or as an entrepreneur, it doesn't matter. So um I think learning is always a good thing, and there's so much of free learning available as well as uh paid learning. Um, but there is there's just a lot of information available now. And so you really utilize that, you know, take advantage of it uh and be part of that ecosystem. And you know, I'm a big believer that the uh, you know, especially with large language models and others, but it we have to have more and more people uh engage with these new AI products and services. Because if we don't, then the new innovation that comes out will cater to the few that were engaged. And that's really not what we want. Um, we would really like for healthcare to, you know, be for everyone and uh pharma to consider, you know, uh uh uh drugs for not just the um male body, but the female body as well, etc. Right. There's just the more we engage with these systems, the better the products and services that will come out of it for the next 50 years, even. So um being aware, being, you know, and whatever, wherever you're comfortable, whether a little bit or a lot, um, I think is important.

Alex Kotran: 52:07

Yeah, I couldn't have said it better myself. Just get on the learning journey wherever you are.

Neeti Mehta Shukla: 52:11

It's doesn't matter how far you want to go, yeah, but just get on it. And I don't know if it's relevant to this audience, but uh responsible AI. So one of the things that we do with the Impact Office is um we run the responsible AI council within automation anywhere. And um, that's important because I think there's so much new AI and so much new data and so many products and services, and you have to have a framework of compliance, governance, and responsibility. Um, and I think that's um that's also good to learn. So if you're a student or a university or um uh a training institute, it doesn't matter. Understanding and teaching the students about responsible AI governance is important. Um, and understanding that is important. So uh that's something we take very much to heart, and we have a lot of programs around that internally for automation anywhere. Um, but I think it's important for society at large.

Alex Kotran: 53:04

Does it does it intersect with your like when you do work, for example, with NGOs, um, do you help them kind of navigate some of these like responsible AI questions along with like the technology?

Neeti Mehta Shukla: 53:14

Uh some do. We are happy to share what we have done or what we do, but um, a lot of times the compliance and governance will be different. So we're not experts in the nonprofit field, of course, and things like this, but having that um having that framework, understanding that, okay, this is how we look at data, this is how we look at privacy and cybersecurity and transparency and whatever else may be. Um, that allows them also to look at, okay, what should our policy be internally? How should we set this up? Um I think having it at the top of mind is important because this is a new area. And we've learned with tech over the last 30 years that we we didn't do very well with certain things, including social media for children, um, that um that we can do better with AI. So um, you know, take that learning and create those frameworks that enable us to be a little bit more protected as society is important.

Alex Kotran: 54:08

Yeah, I mean it bring bringing it back to what you're saying about um, you know, having leadership and having sort of like internal champions that can, you know, make it a priority. But yeah, like the the responsible AI for, you know, a health organization versus an education organization would be really different.

Neeti Mehta Shukla: 54:24

Yeah, we just completed ISO 42001, which is the responsible AI certification for ISO. Um, and I think we are one of uh less than a hundred companies, 75 companies in the world that has it. And and that's why I think it's important because I feel um to we have to deliver amazing things, but we have to deliver it very responsibly.

Alex Kotran: 54:44

That's wild, only a hundred. Excellent. Well, Eti, thank you so much again.

Neeti Mehta Shukla: 54:49

It's absolutely a pleasure, Alex. Thank you so much for having me.