AI Implementation in Business Operations: Start With One Task, with Ammarah Ahmed

Listeners, picture this. You walk into your business on a Monday morning, and instead of drowning in spreadsheets and manual tasks, you watch systems that actually understand what you need, anticipate problems before they surface and give you the breathing room to focus on the work that you can do. That shift from grinding through operations to orchestrating intelligent systems is happening right now in businesses of every single size. And the gap between those who figure this out early or who wait is widening faster than most people here like. (upbeat music) Welcome to AIBiz, where we explore how artificial intelligence is reshaping the way businesses actually work. In Navya and each week, we sit down with people who are navigating this transformation, not will hype or theory, but will real decisions, will results, and real lessons learned along the way. Today I'm joined by Amara Ahmed, someone who understands both the promise and the practical realities of bringing AI into business operations. Hi Amara, it's great to have you here with us. - I know, Vets, lovely to be here. Thank you so much for having me. - Thank you. So Amara, before we begin, any quick introduction for our listeners to know you better. - Yeah, I am Amara. We run procession consulting, we're a CRO and product UX UI consultancy. We're a boutique consultancy, so we're very, very lean, which means that we have to make do with the very little resources and, you know, I think what you mentioned earlier, we're really kind of making the AI part count in terms of the work, but at the same time, like, you know, letting people do the good work as well is super important for us. And I think, yeah, we've come around at a good time in terms of tech. - Thank you so much, that's lovely. So, you know, Amara, let's just hit it off with like a very basic thing. You know, when business owners first think about using AI in their operations, what, according to you, is the biggest misconception they walk in with. And, you know, how does that misconception usually creep them off? - I think the biggest thing, to be honest, that people get wrong when it comes to automating their tasks, you know, when AI is, they think that they can do a large chunk, you know, in one go. And they also think that they are going to be able to run entire loops, you know, without involvement. And they don't really take the time to understand what exactly it is that they are trying to automate. So, they put too much emphasis on the intelligence and not enough on the artificial part of artificial intelligence, you know. And I think that's the biggest problem. It doesn't come with all the years of experience in underseining of, you know, humans in psychology and all of that and the nuances that exist in today's world. So, it has a lot of technical information and there's a lot it can do, but then there's a lot it can't do as well. So, I think there's a learning curve to it. And you need to go in with a certain level of patients going and, you know, time for testing, for playing around with it. And really building those processes step by step. - Right. So, when somebody realizes that that's not how it actually works, what is the first mental shift that they need to make to approach this more effectively? - I think the biggest mental shift is that it's not like you're going to be, you know, sitting in bed and your company is gonna run, right? Whoever goes around like selling that policy, it's not a curve, right? If you are running a business, you have to be involved. And so, that's the first thing I think you gotta, like you gotta your head. What it's here to do is take care of their manual or the, you know, operational repeatable tasks. So, if something can be done again and again, right? If you can put it down in a very simple SOP, if you can just, it's repeatable, it's boring, it's operational as hell. And all it does is just consume your time and none of your brain cells. Then that work belongs to the AI. But where your creativity is required, where nuance has come, where clients and people in stuff like that is involved, then that's where you yourself are required, right? And that stuff should not go to your AI. - Exactly, I agree. You know what I mean? The human creativity and the attention to detail that us as humans can offer. I think AI gives you a very generic output when it comes to whatever prompt you've given. I think as humans or as people who have that ability to pay attention towards the little details of a certain thing. - Yeah, it doesn't occur to the aspect, yeah, right? - Absolutely. I mean, you're asking creativity from a system that's just running off of trained material. All it can do is give you reproduced versions of everything it's been fed. It cannot produce something new the way you can, right? You actually have that ability to do so, where you have a brain and it can come up with new things and new concepts and new ideas. This is a system that's just trained on material and it can find ways to reproduce it in different directions and ways, but it can't come up with a new thing altogether. - Right, and you know, it's interesting because we tend to create the new technology, like it's a magic switch. And I mean, in reality, it's more like learning a new language for how work gets done. - That's so well put, that's so well put. I completely agree with you. - Yeah, so moving forward. I mean, what do you think sits underneath the surface when any sort of business struggles to integrate AI? Even when they have the budget and the tools that are available, what are the deeper patterns that make this so hard for a lot of business companies in operation? - I think what happens is a lot of people don't really take the time to create the framework and the structure first. And they just go in and say that, okay, this is something that I need automated, right? And if you don't have an existing process, you can't automate something. - Right. - And I can, a lot of places we do that first, we try to automate a thing that doesn't even exist today. So we're about to launch a process and we're immediately seeing actually where day one is going to be automated. That doesn't work because there's going to be loopholes, there's going to be issues in it and you're thinking of creating this sort of a thing that's working an ideal way. It cannot cater to edge cases. It cannot cater to anything along those lines. It's gonna fry it, right? So you need to kind of have a process first. You need to have done the manual stuff first. And once you've done that, then you need to automate it in pieces because what that allows you to do is really test and iterate every park and create those maker checker loops. The thing, there's a reason we have that sort of a system in business that. And the same leads to exist in your AI businesses as well. Everybody goes around saying things like, oh my god, yeah, I made an agent for this and an agent for that. But how many of us actually understand what that means, right? We need to have agentic loops for these things. There need to be checkers and makers and policies in place so that you don't spend all the time just redoing all the work that your AI was supposed to do. - Yeah, exactly. - And you will do that if you haven't spent the time in actually creating the process first because how are you gonna explain to the AI when you yourself don't know what needs to be done? - Right, it's a very enthusiastic junior intern, right? It'll do everything you tell it to, but it has no information. You need to be at, you need to tell it calm down. I have to teach you everything. they have to monitor everything exactly and again that is also possible if and only if the one who's heading the team or you know managing the entire operations is very well aware of the things going on inside the team oh absolutely absolutely like if you don't know the definition of good and what is it that you're looking for and you just expect you know to to get taught by AI then then again you're you're walking in um you know for for a failure because if you're assuming like you can now skip the entire path for learning altogether then then that's not a realistic expectation what AI has done is it has added a lot of democracy right and access to a lot of tools so somebody who you know wanted to be able to create an app today does not need to you know put together funds and hide you know higher developers and all of that but do you still need to spend time and research and understand what development is what goes into an app and you know learn the basics and everything and then go and create one absolutely otherwise you're just you know creating chaos that's going to go nowhere that is such a beautiful point because again you know I think the biggest problem that people face is assuming that AI is here to solve everything all at once and you know you just give it one single prompt and each and every concept thought it for you but that is not the case in the algorithm there could be a lot of things which you as a human I mean you could do it better than just AI and you know aren't like a magic one yeah or there are so many times like honestly like I've you know when when we were first you know trying to like automate certain things at the office I spent you know time building these like internal apps and when I tell you that it took us months to get them to the stage where they are today when you know we can just come in and spend like 10 minutes on each and and you know the work is done but initially I literally would have to sometimes spend half a day trying to figure out you know what's broken how I fix it because it doesn't understand on its own right you have to figure out what exactly you need out of it and you can't figure that out if you don't do the research yourself wide is the same important right and so many times you'll realize that the answers it's giving you are are done right stupid right or done right wrong and when you finally do put when you read you know you do your research and you figure it out and you go like oh actually what you've said to me it's completely wrong it's gonna be like oh yeah actually yeah I'm sorry and if you haven't done your research you're gonna be going down a completely wrong path and there's no way for you to figure it out and it's God forbid if you're you know you're you're you're the CEO or something in your you know you're leading the team then you're leading the entire team down your bubble do you all right so you that intellectual humility needs to exist that your your need to learn needs to exist that sort of curiosity needs to exist none of that can go away what can go away is kind spent doing repetitive you know boring tasks um so that you know my team does feels more fulfilled at the end of the day because they've done work that makes them feel like they've added value right and they're not busy feeling like like all I do is feel excel sheets all there right no they've they've done work where they feel like you know they they've applied themselves they've you know done creative work they've produced amazing stuff for the clients that's the stuff where their time is supposed to be skunt yeah definitely so uh you know for somebody who's running a business day to day what does it look like when AI is working well in operations versus you know when it's just another tool that is gathering all sorts of digital dust my first version of this honestly is how much more time do I have to spend um you know like for me and the team to spend with the clients and on the actual client work versus you know the the housekeeping work that we like to say right so how much time do each of us get where we're doing stuff like that versus stuff that we actually want to work on and how much can we do like obviously like I said we're boutique um consultancy right so we how how many more clients and brands can we work with without having to do extra hire is for you know tasks like these so if if that's green then then that means we're good so if I don't have to bring in people for doing you know tasks like the the crabby stuff of like you know so show media management which is just searching and scheduling in you know um doing the the posting and I actually just have the designers who get to do the creative stuff where they're they get to design and all of that and then everything just goes in and the scheduling and everything happens itself right so they don't their time doesn't get wasted on that and similarly you know the developers they don't have to worry about you know doing wasting their time in prototypes they're working on the final results because all of us when we're doing our UX work or and we're showing you know mockups and everything to our our clients then we can build our own prototypes or we don't need necessarily like you know um too many analysts because we have very detailed you know automation put up so the things sort of analysis that you know would take us maybe like three four days when a new client was onboarded not only takes us a day because the larger chunk you know of the work for yeah the analysis automated so key only now has to you know like do a bit of the review and you know he just has to kind of you know do a sense check put together a few insights um and then kind of you know send it over to us and we can then actually do more of this thinking work like okay this is the data now how do we kind of you know figure out what our next steps are going to be so we need to spend a lot more time doing you know the brainstorming and the working um and I think that's the sort of check in that I keep doing know with the team as well as how much time are you able to spend on on that sort of stuff then of course you know there's there's always still going to be certain stuff that you have to do because you know we just haven't been able to automate it yet or we just haven't had the time or whatever um but I think for me that's that's the best way you know to to gauge um are we using it correctly you know we aren't replacing people where people truly add value um and we're taking away the work where you know it just wafes their time yeah definitely I love that you know and I think this is what makes it so concrete I mean it is not about replacing people or automating everything that you have in plain sight it's more about identifying the repetitive friction points and you know letting the art intelligence handle those so that the humans in the room can do the thinking that actually moves things forward and add that human touch to it of course absolutely and I think you should work with your teams to upskill them so that you're not the ones you know figuring out these automations yourself I think they're you know better equipped to figure out what can be automated there do in these workflows day in day out so uh you should be working alongside them to figure out you know what it needs to be automated how do we automate it what can be the edge cases what can go wrong um and I think when you include the not only you come up with you know better workflows but there's also just you know more trust in in the team uh and the new tools aren't let that with with doubt or concern um because they know that it's it's something that's here to help them it's a tool for them not a tool in place of them right definitely I strongly agree with you so um Amara just telling me this one thing when you work with somebody who's ready to bring AI into their operations more intentionally what is that one practical or reflective approach that you recommend them to start with you know not not like the full roll outs or of the thing but the first real step because often that is the most difficult thing people find. I would say start with one, pick just one task, right? Just figure out one task that's eating a lot of your time but does not really need, you know, a lot of your judgment. So for example, for me, it had to do with a lot of compiling the report like I had a very clear template or scheduling our content. So we already had everything created but then just spending time scheduling everything on five different platforms was just a waste of time, right? So pick something very, very simple. That just takes up your time but does not really require your judgment. And you know, it's not going to be the flashy thing. You know, people assume that you're going to automate something that's going to like move in same KPIs. It's not going to be that. It's going to be a boring thing. It's going to be a repetitive task that's just sitting in front of your face. But it's what makes the difference. It what it's what frees up your time to do the flashy thing yourself, right? And in that range, start from. And I think it also sort of like minimizes, you know, the rest because it's such a simple and boring task that you get to learn it more easily. There's minimum, you know, risk in terms of if anything, you know, goes wrong along the way. And of course, well, you know, when you're first getting started, it definitely will. And don't, you know, start with too many. Like I said, just pick one thing and just start with that first. Yeah. It's beautiful because you know, it sounds like the key is starting with clarity and not ambition when you talk about it. I mean, knowing what problem you're solving and being honest about whether the solution is actually making that problem smaller. That kind of focus probably saves people from a lot of expensive mistakes. Yeah. And simplicity just starts simple. I think really as humans, we seem to really confuse, you know, complication with something that's, you know, bound for success or something that's bound to amaze people. That's when that's truly not the case. You know, just people understand simplicity. Simplicity is what wins at the end of the day. So just stick with the simplicity. Beautiful. So what do you tell somebody who feels like that behind, like, you know, everyone else has figured this out and they're still trying to make sense of where to even begin with. Oh, they're, I mean, I feel like, you know, it doesn't matter if it's AI. It doesn't matter what it is. I think at all times, we, people find some reason or the other to feel like we're behind on something. You know, it's just in our nature. But I don't, I don't think we are. Look as long as you have that sort of, you know, interest in proactiveness in you to go out and learn and a little bit of, you know, things can, to look like a fool, even if it's just, you know, adamant thing with these. Yeah. Most of the times, I mean, if you're sitting on your computer at night, who are you going to look like a fool to nobody? But, you know, where we, as we grow up, I think we get so scared of trying new things. We're so very of, you know, if I don't know how to do this, then I'm going to feel stupid. Forget even look stupid. We don't even like to feel stupid, you know? And I think so we, we stop ourselves before we can even try it out. And I think that's, that's what blocks us. What went, all of this is, you know, fairly simple. And for anybody who feels like they're behind, you're not. I, most of the people in the world have not begun with it. I think, you know, you see, only data points shared across, you know, in news articles and across the internet that such a small percentage of the world, you know, it has actually started to use AI or even has access to AI, you know, today. So you're, you're in the majority. The only differences, are you, you know, now going to be interested in learning. And again, it's, it's not just about this. It's about everything that's going to come up next. Are you open to learning the new things coming around you? Are you open to feelings stupid in a moment and asking somebody a question just so that you can learn something? All right. It's open to doing that. Then, then you're going to go a long, long way. Right. I agree because, you know, this is not a race with like a finish line. I mean, it is always about those DB steps that you take because there's an ongoing process of learning, right? And especially learning about what works in your context. I mean, the businesses that do this well, they aren't necessarily the ones with the most advanced tools. They're the ones that are willing to keep experimenting as we talk about and, you know, just keep adjusting and keep asking better questions. Absolutely. Like because you have to keep learning and you have to keep growing. If you don't keep growing and learning, then I mean, what's what's the point? You know, you can, you're as good as a rock. You're just stuck in a place. Yes. I agree. So, you know, one thing that I can most definitely say about this entire conversation is that the real opportunity is not in having the smartest AI. It's annoying how to ask it the right questions and integrate its answers into the work that markets. Definitely, definitely. I think you put it really well. Right. Thank you so much. So, Amara, thank you. Thank you so much for walking us through this. So, thoughtfully. So, if people want to continue this conversation with you or learn more about the work that you're doing, where is the best place for them to find you? You can find us at GoPrecision.co. That's where we have a giant insights hub filled with three resources for anybody who wants to start their learning journey. You can request a free audit. You can, you know, book a call, knock yourselves out. Right. And thank you. Firstly, thank you so much for having, you know, taking out the time to be here with us. And one thing that I want to say to everybody who's listening, whether wherever you are in this journey, whether you're just starting to explore what AI means for your business or you're already deep in the weeds of implementation. Remember that the most powerful tool you have is not the technology itself. It's your willingness to stay curious, to test assumptions, and to keep learning what works in your mind. So, thank you for being here and we'll see you next time on AIBIS. Amara, so high.