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Scaling With People
Why Most AI Projects Fail Before They Start with Ghazenfer Mansoor
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Most companies are approaching AI the wrong way.
They buy new tools, experiment with prompts, and expect breakthrough results. Then they wonder why productivity barely moves and expensive AI initiatives quietly stall.
In this episode, Ghazenfer Mansoor, CEO of Technology Rivers and author of Beyond the Download, explains why successful AI adoption has less to do with the latest technology and more to do with the systems already running your business.
We discuss:
• Why most AI projects fail before they generate meaningful ROI
• The critical role of clean data, workflow design, and business context
• Why AI hallucinates and how poor inputs create costly mistakes
• How strong processes become a competitive advantage competitors can't easily copy
• The connection between operational efficiency, profitability, and company valuation
• How leaders can overcome employee resistance and fear around AI adoption
• Practical governance and compliance considerations for regulated industries
• A simple 30-day framework for identifying automation opportunities and building an AI roadmap
One of the biggest mistakes companies make is treating AI as a technology project instead of a business transformation project. Ghazenfer shares a practical approach to improving one workflow at a time, creating momentum, reducing risk, and generating measurable results.
If you're a founder, CEO, or business leader trying to scale without adding complexity, this conversation provides a roadmap for turning AI from a shiny object into a genuine growth engine.
Follow Scaling with People for more conversations on leadership, growth, systems, and building companies that scale without breaking.
Welcome And The Big AI Question
Welcome to Skilling with People, your weekly playbook for turning chaos into compounding growth. Each week we go under the hood with battle test experts in all areas of business, from marketing to sales, operation finance, and people, plus product and leadership to unpack the plays, numbers, and systems that turn chaos into compounding growth. Learn straight from founders and experts who've done it and continue to do it successfully. There's zero fluff, just moves that you can still immediately. This podcast is brought to you by Guide to HR. Human expertise, AI-powered impact. Welcome everyone to today's Skelling with People Podcast. I'm Guinevere Curry, your host and founder and CEO to Guide to HR. If AI is a rocket fuel, why are so many companies still crawling? On this episode, we sit down with Ginzenfer Montur, CEO of Technology Rivers and author of Beyond the Download How to Build Mobile Apps That People Love, Use, and Share Every Day. ConZenfer and his team are helping founders turn clunky operations into high performance engines with AI and smart software. We're heading through the hype to show how real tenant growth actually happens, not through more tools, but through building technology that works with your people and not against them. Well, welcome, ConZenfer. I'm so excited to have you on the show today. Before we get to dive in, please introduce yourself to the audience. Thanks for having me. Yeah, I'm excited to be part of this podcast. So my background, I run a software development company, Technology Rivers. We help businesses improve operations through AI and technology. We also help businesses build software products primarily in the healthcare space. That's where work with physician, entrepreneurs, health tech companies building HIPAA compliant software products. Awesome. Well, I can't wait to dive into the AI conversation because I love it. I'm a junkie. But before we do, as a founder, I love putting my founders on the hot seat. Would you mind sharing a lesson learned from like your own experience of building your business? Absolutely.
The Costly Mistake Of Building First
Before starting this business in 2015, um, I founded a startup which was in a recruitment space. It was a recruitment software. And I think the lesson learned from my set was like we build a really strong, scalable product. We build the product first, then we started looking for a customer. And as we started looking for a customer, we did get customer, we went through different iterations, but there was a lot of stuff that we had to discard after that. We went after the feature is building strong foundation for something that people were not going to use. So a lot of energy, a lot of money was spent on things that were uh not useful. So for my side, the lesson learned is, and these are also the experiences that I learned along with after working with so many founders when I started Technology Rivers to build something what your customer needs. So if I have to start another startup, I would not write a single line of code until I have the customer. So to me, the lesson learned is finding a customer post before building anything. And that's kind of really knowing your audience and the problems they're trying to solve instead of thinking this problem is solvable and solve it and then have no one to sell it to, right? Absolutely. Yeah, I love that. Thank you so much. I mean, that is a big deal. Um, and I've seen some founders do this really successfully and some that have not. So I hope for those listening, you definitely take this to heart because it is a way to make sure that you can create a successful business.
Why AI Fails Without Clean Data
So as we dive into the topic of AI, most founders think AI equals efficiency. But what are they missing that's actually limiting their growth? So AI is definitely considered as uh a growth, but at the same time, most people are not using it right. Most people are using it as a search, more people are just relying on AI and assuming AI is gonna just give them everything. Unfortunately, AI is giving you something what you're giving it. So it's your data is the key. So if you don't have the right data that you train AI on, you're not gonna get the right results. So there's a lot of hallucination. That's the term you probably heard a lot. So AI is gonna make mistakes, AI is gonna uh give you our wrong data, AI is gonna hallucinate because it does not have the right data. So it is important uh that your data is clean, your workflows are mapped, and at the same time, you are providing the right context of what do you want? Like, and this is a common problem even in outside AI as well. You ask a problem in such a way everybody would understand it differently. You ask 10 people the same question, you'll get 10 different answers because you're not giving the right context or you're not able to write articulate it right, you're not gonna going to get the right answers. Yeah, that makes a lot of sense. And where do you see, like as you're working with founders and just having conversations with other business owners, where are you seeing companies wasting money on AI right now and not really realizing it? It's the same part where companies are just assuming that AI is just gonna solve their problem by just plugging in. And the default assumption is, oh, AI is probably just like a Chat GPT or Cloud. You just load your documents and it will give you the right answers. No, then those are the lessons learned along the way. So that's where we see like majority of the AI projects fail. So if 90% of the projects are failing, what are the reasons behind that? Because most people don't know how to use the AI. Most people are so there are different strategies that you have to use to build uh the right AI application. Because again, as I said already, the context is important. Um, so think of this way: so you you have a huge set of data, you have hundreds of documents. If you load those, are you think AI is gonna give you the right responses? Right, like even if you load five documents in Chat GPT and you query, you will quickly realize that you're getting answers from one or two documents, not all the documents. And then you have to be a little bit more specific because it's not gonna go search all of those. So when so you have to prepare your data accordingly and then have your queries accordingly. So you have to know what kind of responses your users are going to be answer asking. So you prepare your data accordingly, and then so those are the mistakes that I see a lot more common people are are making. So this is where, and and some of these are very similar to even non-AI based as well. You build something you don't know, and that means you made a mistake, you failed, you try again. So that's where you start spending a lot of money on those things without realizing that oh, you are going on a wrong path. And at the same time, another mistake and not understanding the amount of data it takes and amount of the cost it would take. So if you have your own data and if you have tons of data, it definitely would require a much bigger servers, and that's where the cost would come in. So again, you can't compare everything with Chat GPT. Yeah, it's uh very true. You have to you know stay on top of it and do your work. Um, and then when you're done, don't just put it aside and think it's gonna work perfectly. You have to constantly be looking at it. So when you say uh 10x growth through AI, what specifically changes inside of a company if they're able to execute on that, or when they're able to execute on that?
Workflow Advantage And 10x Growth
So look at this way. So every company has access to different tools, uh AI, non-AI, whether it's a CRM, whether uh it's the recruitment software, HR software, any software that you're running in your business, your competitor also has access to that. So everybody has access. What is your differentiator? Your business is running, whether it's HR, whether it's uh plumbing business, any business that you're running, any uh um whether it's any healthcare. So you you and your competitors are the same. Are you a better service? Uh, do you have better people? Is your cost low? All these differences, like your competitor have already access to that. What is the difference? The difference is how your workflow is mapped, how much efficiency in your processes where you can do things better. And that's where technology and I can make a difference. Your competitor can copy another software, but they cannot compare, they cannot clone your workflows. That's what you can do. So, how data and processes change hands from like your lead came up to your delivery finished. There are hundreds of steps that happen in between. There are a lot of manual steps. There are probably 50 different software being used, data is being shared, data is being lost along the way, there are many people involved. There are so many manual steps, there are many bottom legs, there are many slow processes. What you can do to optimize those processes, and that's where the technology comes in. And as you have that technology, that brings more efficiency, meaning you have less mistakes, your productivity increases, your profitability increases, your valuation increases. So I'm thinking about this as a founder, and like, yes, I need to increase that. And yes, I have these problems and these and these different workflows I want to put into place. Uh, maybe even when you work with a client for the first time, what is the like, how do you help structure the framework for a founder to know, like, this is the area you need to focus on first? Because obviously there's there's the fast approach, right, where you can implement something and have a quick win versus the longer approach, which is like this is gonna have a bigger win, it's just gonna take more time. So, how do you help the founders define what to focus on? Because we have a lot of noise in our world, and there's probably a lot of inefficiencies in every org. How do they pick, how do you help them pick what to focus on first?
Picking The First Automation Win
So there's no one solution for everybody. Every company has its own DNA, every company has its own processes. This is where the strategy comes in. What works for you specifically? Whatever works for you may not work for somebody else, or and vice versa. So you have to look at your specific processes, your specific uh flows. In some cases, your people may have a different capability, and you're really good at one thing versus another one. So, yes, there's a bottleneck, there is improvement needed, but you may not need something right away versus something that needs to be solved right now. Do you have a problem on the delivery side? Do you have a problem on the sales side or nurturing? Whatever is that process. So there is there's no right or wrong. There's there's no um, I would say first or second. You just have to. But the most important part is you don't want to be looking at as a whole project, because that's where I've seen people get confused. Okay, we want to automate everything, but then you realize oh, it's a huge project, and then suddenly you're scared. You want to have a very small processes. So we want to you want to start with small wins, small processes. It could be starting with just one AI agent that may improve one thing. It could be scheduling, it could be um some automation in your email process, it could be anything. So, but as long as you're doing one thing at a time, gradually you are building your confidence. And this is where also, you know, like change is difficult. Your team always will will have a pushback on any of those bigger projects. There's a fear of replacement, there's a fear of uh capabilities, fear, like there are doubts of will we be able to do it? Will there be a mistake? So you start with just one small thing at a time. And as you start implementing those small at a time, you realize oh, gradually, these all of these individual items becoming a big project. You don't even have to worry about the integrating those on the first step. All you do is start automating small pieces, and that will eventually become a bigger project, and then gradually you can integrate and bring it into a one-tech. I love that advice because it also helps bring your employees along, right? The people along. They're able to consume it and work on it, and it's not so fearful, it's just a little bit now. Learn that, okay, and then keep going, right? So I love that. That's
Change Management And Team Buy In
great advice. But speaking about like people and technology, what what is the real constraint that you have seen inside of a business? Is it technology? Is it leadership and decision making? Is it the employees? Like, what's the real bottleneck on companies moving forward and getting AI implemented to help them be more efficient and effective? It's a change. So change at every level. It's the um uh it's the fear of um bringing any new technology because it people have a fear of getting replaced, people have a fear of not doing it right, some people have a different perspective. Um, some people don't want to even learn. They said, well, we are used to doing things the X way. Now there's another thing. So but AI is pushing people to have all of those new learning. So yeah, there I would say it's it's at a different level and different places. So uh it's it's important that you bring those people along with you by doing these small, small things. So look at this way like if so, if like if you can just improve the productivity of one person with one small thing without having that person a fear of that this big change is gonna impact their job, we realize that they are more excited when they start getting certain things done much better. Yeah, so we all always have 10 additional things that we can handle. So with AI, it's not about replacing people, it's about empowering people. So as you impover those people by bringing AI that's helping them doing 10 things 10 times more than what they were used to, now suddenly they are more excited about. So it's about how do you bring that change into your people so that they are more excited and they are not pushing back. Yeah. Yeah. And I think it's also you get a couple of people that do it and then share how they did it. Then you're getting a little bit more buy-in, you get a couple more people doing it, and all of a sudden you have this wave of the majority of your employees taking it on. I've seen so many times where employees are using AI, but they're so scared to say that they are and how they're using it, that they don't share that and help each other learn and grow. And a culture that creates the environment of trust and safety so that you can communicate that and share that is one where I've seen it really flourish and AI really takes off. Yeah, absolutely. And I mean, one of the things I say, let's say we all know, let's say, for example, on the content side, it's being used the most because let's say whether it's writing email, yes, if that part is even helping, at least that give people some confidence. Now, more than the email, then you start getting into maybe the proposal writing, maybe into optimizing some other documents or creating some stuff, some plans. So gradually you're doing it without even having the fear of, oh, this is gonna replace or become a big project. This is about this one small thing that's previously was taking because now they had to do these things in three days. Now you can do it in two hours or one hour. But only that thing is much better, and they can do a lot more things. So you want to have their buy-in, and that is the most important part, how people are having a buy-in and they are more excited about uh about that. Yeah, that's true. And and there's so many pros to AI, but on the flip side, what have you seen as being the most expensive mistake uh that founders make when investing in software or AI into their business?
Avoiding Expensive Software And AI Spend
The most expensive mistake is not working on the foundation or the strategy, but just getting into the weeds and just implementing something without knowing is this gonna work? Because I mean, look at this way. If we all look at in our company and say, well, how many subscription software we have? So probably, I mean, you'll be shocked if you do the search. I mean, I did when I look at my QuickBooks, so like how much money we're spending on those. So yeah, and then most of these software will have one or two overlapping features among the others. So that means we are we are using so many different software and we're not uh we're not using all the features. And then how do you sync the data among all of those? Then there's a lot of integration efforts. Do we really need all of those? Do we need one of those? So, like thinking through knowing before what you want to build versus just get it and try to get it work. Those are two different things. So what I realize, people are not doing, and this is a common problem um across many industries, many people, is we're not doing the right discovery. We're not really figuring it out what do we really need, what problems are we trying to solve? Oh, we need another HR software, we need another recruitment software, or another, we need a CRM. Why do we need it? What problem are we trying to solve? Not saying that you don't need it, but what features do you need? And each will have some um overlap. So by never by looking at your specific needs, your workflow, then you realize what do you need, which software do you need, where do you need AI, and even what like just like everything, like even you don't know, like do you need cloud, do you need open AI, do you need uh Gemini? Each will have some features. And each of these have are good in certain things. Not everything is. Do you need on-premise? Do you need cloud? Once you start building investing in, let's say, cloud, and then you realize, oh, we're not even allowed to deploy on the cloud, and now we need an on-premise solution, suddenly all of those things are gone. So all of your RD effort is gone, or vice versa. So knowing uh your boundaries, knowing your the regulation, uh, the compliance requirements in your industry, all of those do make a difference. In our business, we work a lot uh with healthcare. So obviously HIPAA compliance is a big part. So any tool we use, we have to look at the main thing. Oh, can they sign BAs? And what are their HIPAA compliant version for whatever, whether it's analytics, whether it's any tracking thing, right? All the tools we are integrating, and you realize that later on suddenly that cost is too high. Yeah, I I uh completely agree. I see um on the flip side with the people, right, is that the founders and CEOs will go out and say, everyone use AI or get off the boat, get off the ship, whatever you want to call it, but they don't actually have the strategy behind, well, what does that mean? What what are the guardwells? What are the systems and tools you're giving your people that they can execute on that? And what does good look like for them? What does that mean in regards to, well, everyone's using AI in some capacity to write their emails? Okay, is that sufficient? Is that enough that I can stay on, right? Or are you talking about workflows and agents and all these other things? So I think part of that too, of what you were sharing is the strategy of like, what are you trying to solve and how are you going to solve it? And then what does that mean for your employees? What do you expect your employees to do and give them that roadmap and give them those guardrails and let and then let them go and do it, execute on it. And you know, there's a good point of guardrail, so the governance and ethics part, all of those, because people are blindly uploading the data uh in AI without realizing the consequences of those. So it's important that as your business is growing, as you're touching your customers' data and using AI, how do you use it? Um, you have to have that governance, you have to have that those policies so that the data is not misused. Yeah, yeah.
Governance And Data Privacy Guardrails
So I'm curious from your perspective, if a listener was to go out and execute uh an automation today, and I know every company in business is a little different, but is there one process that you see consistently over and over again that every company could automate and maybe even automate it like this quarter or this year? Well, that's a hard question. Uh I can't think of any anything on top of my head. But I think the basic business operations things uh that everybody can do, you don't even need to even write a code. So many of those could be like a simple AI agents that you can use with cloud code or any of those. Like for us, we we use it everywhere in our email, in our proposal writing. So those are the areas where when your lead generation doing some research, any of those things, those are the ones that you can simple start with. And there are many that you can just find available online. So yeah, I would say start with very simple, basic ones you start where you can really see the value of those and you start seeing the time difference. Yeah. I was thinking maybe like something like um, you know, your engagement with your clients, with your employees, with your um, and even like with the vendors. I know so many founders, one of their hot buttons is uh on the finance side, invoicing and getting the invoicing right, one, right? And then number two is the for those clients that don't pay on time, that follow up and the follow through to get them to pay. I know so many finance teams that they just I feel like they just spin their wheels constantly reaching out and trying to get people to pay those invoices. There's got to be a way to somewhat automate that. So I don't know. I was thinking maybe that might be one way too. Yeah, there are a lot of those smaller agents being created. Like, so I mean, we build so many internally, some for our own, some for our customers, uh primarily more on the healthcare side. Um, but you're right. Like those are the small use cases that you have to identify. What is your bottle next? Like, for example, in our case, that may not be a problem. In your case, it may be. So if you need that, what are the things and how different it is? Like, so some of those maybe uh your automation is already there. So in some cases, you do need more custom work to do certain things. Yeah. Okay, that makes sense.
Simple Automations And AI Agents
And I know you uh are the author of Beyond the Download. What did you learn while you're writing that book that most founders ignore? So, Beyond the Download, how to build mobile apps that people love, use, and share every day. I think this is one of my passion projects that I started three years ago. This is based on the lessons learned that we created over 60 different applications as part of my business, as well as my own experience in the mobile, even well before starting this business. So, over the years, built so many different mobile apps and seen them grown, failed. So, this book talks about different strategies that how to build a mobile app that's not just another app that's downloaded on your phone, but also that gets retention. People come back to it again and again. How do you engage those users? So, those are the different strategies that we that I talk talk about. I think the bottom line of all of this is you want to build an app that is a remarkable app, which has a greater user experience, greater design, but at the same time easy to use, but keeping people engaged. That's the most important. How do you have different ways of uh in the app that it keeps exciting for users? And it could be some of those online and like some of those offline strategies as well that may not be part of your app, but they are related to the app. So, and a lot of those principles can be applied on a non-mobile application as well. Oh, that's so true. I didn't even think about that. So, as we wrap up today's episode, if we were to go and give a founder 30 days to complete, you know, some AI workflow of some sort, where should they start with AI to see real results in their business? I would say go back to AI for that advice as well. Like maybe asking a Claude, and Claude can give you uh a roadmap and a plan to start your first because again, so you have to first give your own context who you are. So if I'm putting my my chat GPT and my Claude knows about me, your case, your knows. So a lot of that information about okay, who I am, what company I work with, what kind of stuff I've done, what can I do, and then having that right context, then it will give you there are certain things you want to do, there are certain things you don't want to do. So uh, and this is goes back to also some of the things we're talking about in terms of mistakes, because AI is not about just asking a question, it's about giving the right context. So sometimes it takes time to tweak that. So you want to so I treat AI as just like my um my thinking partner or my system where I keep giving instruction, I got something, and then okay, no, I want this thing. So keep optimizing based off of that. So your plan is also one of those that could be uh optimized. So you want to know what workflow,
Building Apps People Keep Using
because your AI knows, has all the memory about what your business does. So it'll give you some ideas of that. And I did that for my own business as well. But that doesn't mean I'll just implement all this. Then I narrow down based on those my preferences. Here is what I want, here's what I don't want. Can you remove this? Can you change this? So doing through this iteration helped me got to where what I wanted. That's so smart. And I I never really thought about it from that perspective. I use that all the time with how to how should I market this? How should I communicate this? I use it as a thought partner. Um, and so for those that are listening, if you haven't used AI as a thought partner, that's what I would push you to start doing in your first 30 days, is just give it the context. Um, use Claude. It sounds like I use ChatGPT. I love the product, the project functionality because you can really like narrow the focus of what it's looking through in regards to how it's going to answer you. But then don't don't just then maybe throw in the same information to Claude or Gemini or Perplexy, whatever it is you use. Maybe try using two or three AI where you're kind of getting maybe different results, but ultimately you combine that together and that could get you your roadmap. So uh great suggestion, really appreciate that. And for those listening, I hope you got some great tips on how to get AI flowing into your business. Don't be scared. It is a great tool that can help make you and your team more efficient and effective so you can grow your business 10 times faster. Thanks so much for joining us today, and we look forward to having you on the next podcast. And until then, have a great afternoon and day. That's a wrap for today's episode of Scaling with People. If you got value from this conversation, do me a favor, share it with someone building something big. And hey, I'd love to hear your take. Drop a comment, share with me a message, or start a conversation. And don't forget to subscribe so you never miss the bold, unfiltered strategies we drop every week. I'm Gwynberg Crury, founder and CEO of Guide2HR, where we help high growth companies
A 30 Day AI Roadmap Using AI
scale smart with people for strategies and AI powered systems that don't just keep up, they lead. If you're building fast and want your HR to move faster, head to guide2hr.com and let's talk. And remember, scale isn't just about speed, it's about people. Until next time, have a great one.
