The number one question I get from business owners, CEOs, founders, solarreneurs, even coaches, consultants or anyone who wants to add AI within their business is where should I start with this AI thing? Their biggest concerns is I don't want to face reputational risk where I look bad if something goes wrong towards my customers or even have my competitors laugh at me if something goes wrong as well within my since I used AI. So, in this video, I'm going to show you a six step-by-step process which I sold for $25,000 to a client, which is a workshop plus consultation. I'm going to give it all to you for free so you can add it within your business and find your first AI use case today.
So, let's talk about machine zero. This is your first AI use case which you're going to implement today. And this is exactly what I sold for $25,000 as consultation plus workshop. In simpler terms, we answered one question saying that how can we add AI within our business today without ruining or risking our reputation.
And where do we start or what's the element should we look at and start? So in this video I'm going to talk to you about three main things. Point number one is the six-step process to add AI within your business no matter how big or small you are. Whether you're a coach, consultant, solopreneur, or a big organization or you're a governmental entity.
I'm going to show you where in this process you can tweak in order to make it work for you. And point number two, I'm going to give you a space NGC inspired which is navigation guidance and control inspired framework and systematic thinking to do it without ruining your risk or risking your reputation. Because one of the biggest concerns of businesses right now is that I don't want to implement AI because this is customerf facing. I have existing customers and I don't want to look bad in front of my customers by doing something wrong and losing the leads that I have making less revenue and so on.
That's not the point of AI. So I'm going to show you how to go about all of this. And the third point being here is a very time-sensitive point which is governmental entities particularly in the UAE right now are mandated to have one AI use case and businesses behind closed doors are having meetings talking how can we implement AI within our business because our competitor is adding AI within their business and we're going to lose market share and point number three over here individuals are trying to capture the wave in any way possible whether they're AI consultants we see a lot of those right now and whether they're MVP agencies or those people who sell N8N or small workflow automations for small D enterprises even big entities as well AI agents now is the talk of the town so let's use that term just for the sake of it so why should you listen to me for the past 10 years I've been in the business and entrepreneurship realm I've built a couple of businesses raised a couple of funding I've pursued my PhD in space I've launched a couple satellites into outer space I'm a very technical guy I've done machine learning algorithms I've done neural networks work with drones robotics and so on but then I got into business and that In particular, for the past two years, I've been helping businesses here in the UAE launch and scale. In 2023, we did 50 plus businesses.
We were featured in the news over here, and we were featured in Entrepreneur Middle East. And then now, we're leveraging AI to build our business and scale our business. And we're always looking at everything from a business first perspective. This is a very important point.
This is not a demo on how to use an NAT workflow. This is how can we use AI or whatever comes in the future in the right mindset and right thinking and systematic thinking process to get more business at the end of the day and this is something that I extracted from my school community which is over here we're going to go through that process and why should you care today if you're in the UA everyone every UA government right now is mandated to implement at least one AI use case very important for you who if you're doing education consulting or coaching or even if you're helping can make this e execute on this and make this practical. This is very very important for you because there's massive opportunities over here. Dubai and Abu Dhabi are already launched a bunch of AI PL pilots.
These are some names that have AI systems live right now. And the use cases span between diagnostic analytics, chat bots, fraud detection, urban planning, drone inspections, education and so on. If if you've been watching the news, you can see a lot of things happening and it's happening really fast. So let's begin with the process right now.
So machine zero your first AI use case and it's very important to start with machine zero properly because this is the like if if you're a business owner remember how it was when you got your first client it broke a bunch of limiting beliefs where everything after becomes very much easier. So this is machine zero. The main objective of machine zero is to break all the barriers you have towards leveraging AI and adding it within your business. So everything becomes easier and you build machine 1 2 3 4 and inshallah machine 100 in the future.
So step number one is your AI number. This is very important and we should always have a why behind why are we adding AI within our business. Otherwise it's going to stay as a hobby. And your AI number is how big should the reward be for you from machine zero to make AI worth it in your business.
And I look at it as as a threshold over here. So the reward most of the time is then it translates to money. So less time spent on certain tasks equal more money. Less headcount equal more money and so on.
And to keep it very simple what I do with every entity and even coaches and consultants as well. I say think of it in 10,000 increments which is 10k increments but change the time frame of it roughly and why I use this number is because roughly the salary the average salary or headcount salary per month is $10,000 and I know you may argue right now at this point and maybe drop a comment below saying no the average salary is $2,000 $3,000 or 6,000 depends where you are within the world and which industry you are in but we're taking the 10k and I said roughly over And then once you have that 10k number in your head, which is your AI number, think of it in terms of time frames. Is it per year? Do you want 10K per year?
Do you want 10K per quarter? Do you want 10K per month or 10K per week? Or even 10K per day? And this will define how big your business is and what makes this lucrative enough for you to go after in terms of AI and so on.
And the profits you're going to make over here, this is just a simple formula, is that AI number you choose. For example, I choose 10K per month. I want 10K per month. how much does it cost for me to run this AI system and that's the profits I'm going to make out of this and this makes it lucrative for me. So step number one very very important know your AI number.
How much do you want to make or how what's the big number that would would that would make you take action on this today because this is very important and you're going to see how every other step ties to this over here and everyone has a threshold by the way. So think about your threshold. Step number two is opportunity exploit. So you're going to see now your business.
You're going to look at it from a very high level and see where or what gaps do I have within my business or opportunities do I have within my business to add AI right now. And I'm going to give you a couple of things that I realized that have been super helpful for me to look at this and specify exactly the gaps within the business to add AI. So point number one is labeling the opportunities. So you have two types of opportunities right now in your business for AI is personal productivity that's one of them and business performance.
Personal productivity are for individuals where for example you're using chat GPT to write emails today that's personal productivity and you're using it for your personal reasons that not necessarily will drive revenue for you or more money to your business or even help you reach your AI number. But the second type over here is business performance. And this is where you take a workflow or you take a process where many people are involved in it or many tasks are involved in it and you may use AI there to streamline these this workflow or this process that you have and drives you more or closer towards your AI number. So this is very very important because these two go hand in hand.
For example, let's say you have employees within your organization. They don't know how to use AI which is personal productivity over here. They don't know how to use these tools over here. And most videos, by the way, on YouTube talk about these tools and how to use it and the knowledge behind it and so on.
They can't use the AI tool or the entire AI integration that you're going to make within or add within your business to drive revenue or more revenue for you. And this is where coaches, consultants, and trainers come in. They help the employees understand this is AI. This is how you use it.
This is a tool. This is how you prompt it and XY Z. And then at the end of the day, you have something bigger that's happening to drive business performance. This does not drive business performance.
Very very important. Writing a better email does not drive your business performance. This is you need to label the opportunities as it is if you're looking to make money. Otherwise, if you're going if you want to have fun and you want to have it as a hobby, you can focus on this.
So once you understand the different types of opportunities that you may have within your business right now to add implement AI. So you want that string to so you can pull on so you can enter within your business and look where could I add AI and what are the opportunities and so on. So you have three entry points over here and these are your starting points. You can look at it at from three perspective.
This is a perspective I love to look at which is an organization level. I have the most fun in this level over here. But you can look at it at other levels as well. So let me just explain what each is to you.
So if you're a coach, consultant, CEO, governmental leader, founder or you have in this strategic position where you're overseeing everything, this is the best level you could start with which is the organization level where you look at the organization you see okay these are different organizations and I want to add AI within this organization or to this bottleneck to this painoint and so on. This is very important and we're going to focus on this in this video as an example but you can apply the same thing to any other level. This level over here is more for an operational level where whether you're a department head or you have a functional role where you look at the process that's involved and you try to streamline that. Then you have the product level.
For example, you have a SAS, you have this product. This product has feature one, feature two, feature three and feature four. Under that there are multiple workflows or lines of work that's going to happen and that's good for product managers, software engineers and so on. This is our focus of the video.
I created a video approximately 30 days ago which is about how can you tr use AI instead of your organization where AI employees and so on. It was over here and this is the process I did not explain how did I do that. This is the explanation of how I did that in that video. This is just an idea over here.
So now let's look at it from this perspective which is the organization level which is the focus of this video. And let's look at the strategy lens. And this works again as I told you for any size of business and it's most importantly you have to have an AI number and that defines of how this all will work for example and you're going to say okay I'm a solarreneur I'm a coach I'm a consultant I don't have a CTO CFO board of directors marketing head operations head and so on I just have me so you're everything so that's how you look at it it's the same structure the same task because the main point of all of this and this organizational structure is that you start from the very top all the way to the bottom from strategy to operations to task level and everything comes down to a task. Everything within the business like if you really go down to the bottom level of everything that's done within any business it comes down to a single task and this is exactly why you do this.
So from organization level you put the CEO the C level and usually put yourself somewhere here. You look at the department heads, look at the employees, and you look at what the tasks each employee is doing. And then you look at what tasks are aligned or dependent to each other. For example, marketing is dependent to a sales department somewhere there.
And then you're going to just say, okay, these are the tasks that are aligned and these are the tasks that it comes down to. Let's see how can we add AI within this. For example, and I'm going to show you now exactly what I mean by this. For example, and this is a real AI use case within big entities right now and governmental entities.
They're receiving a lot of emails. let's say 500 emails per day and that's a task. How can we answer these emails fast every single day? This is one task. So this may be a marketing department or customer service department and so on.
So this is just an example. So you can see this is from an organizational level. So then once you see all of this from a very high level you look at three steps. Point number one is you say okay where is the main pain points within all of this and where is the main bottlenecks within all of this.
So pain points is today, my current problems. Bottlenecks are future problems that may occur if I don't solve the pain points today. And point number two is you're going to mark the areas that you're going to solve that will highly contribute to getting you to your AI number because not every problem or pain point or bottleneck that you solve will get you to your AI number. So you want to see which one will get you closer to that number and that's why it was super important.
Then third point is we define the feasibility of this. Whether it's very complex to implement, do we need training? what do we need to do exactly and who will take care of this in order to integrate it within our business and this is very important because we're going to come down to the details of all of this so I look at this usually in terms of revenue cost opportunities and risk what's the revenue we're going to save or make or just add to our business if we do this what's the cost that we're going to save how many employees are doing this or are we having too many employees doing a certain task that they're not needed and so on what's the opportunities that we may unlock and what risk are we getting rid of or adding with to our business and that will define the feasibility for me. So let me show you very quickly over here how I look at this. So point number one as I said the pains the pains I look at it into four departments and of course just a note here this is much much more detailed that what I'm showing you here and if I'm going to explain the whole thing that what we did within the consultation and workshop is going to take a lot of time.
It's going to take a couple of hours for me just to explain to you every single detail to this process. But this is enough. What I'm giving you is enough to get you started and add AI within your business. So pains, you have cost pains.
This is too costly. We're paying so much every month and we need to get rid of this. This is one point of pain. Quality pains.
The quality of the vendor is not good. XY Z. So the customer sees us as a lowquality people or whatever it is. Efficiency.
This is very unefficient process. We're using five people to do one task. Can we make it more efficient? Or speed pains.
This is very slow right now. How can we make it faster for anyone? So, everyone enjoys this. The bottlenecks, for example, our bottleneck right now is the capacity.
We have too much work coming in. We have too much clients coming in, but we can't cater to all of them because we don't have enough headcount or we don't have enough employees or whatever within capacity within our business or organization. Point number two is knowledge. Okay, everything AI is coming in, but nobody has clue how to add AI or what AI even is.
Nobody knows how what an LLM is or an agent is. So we have a knowledge bottleneck. And in the long term, this is very important. Bottlenecks are long-term thing.
In the long term, if we don't solve this problem, our competitor will use AI. They will have the capacity and knowledge. They will hire or fire the people and they will be compliant and they will also solve for all the risk and they're going to beat us like we're going to go out of market. So this is bottlenecks, future things, and these are current things.
And then once you list everything down, you look at the cost and you look at the benefit of it and you start looking at through a chart and you're going to choose three main things from over here which you're going to say okay the outcome of all of this is that I'm going to get my three high leverage task that I need and I'm going to show you example on that. I'm going to take a three high leverage task over here and replace it within my entity. So this brings us to point number three which is step number three and this is the fun part for me because when I was doing navigation guidance and control in the space systems I used to always draw these flowcharts input output then a feedback system then some kind of controller then we have disturbances coming from the top and then write a bunch of equations. Okay this makes sense let's put it in the satellite instead of outer space.
So this is something similar and you're going to see over here but we're doing it for business cases. So a quick legend over here is that plus means it's going to hit your AI number. X means it does not hit your AI number. So you're going to take three of the highest leverage tasks from above over here after analyzing and seeing the opportunities and start drawing flowcharts out of them.
For example, one of the bottlenecks was was within a business saying that content does not scale for business and there's a high cost of staff and we're paying influencers a lot because we want attention. We want people to know we exist. We want interactions within our brand but this is a bottleneck right now and we're we're there's a bunch of pain points involved with it and we if we solve it right now we're going to increase our revenue by XY Z. So then what you come and do is you say okay let me draw a workflow on how this would look like.
So you put the inputs over here the outputs over here and then you put all the plan the manual task or manual subtask that you do to get this outcome over here. So the input here is topics. We have topics and we want to turn them into interactions where the audience interacts with my brand right now. So let's think about it in a content way.
So we have content planning, content creation, content distribution, performance tracking and then content review and then we get we will get those interactions if we did a good job on all this substeps over here. So then what you do is you look at each one of them. What's the pain point right now of each one of them? for example, and at the beginning you won't have these checks and X's over here because you're going to analyze them later on. But at the beginning, you're going to say, "Okay, content creation.
Right now, I'm paying I'm paying some experts to create some content for me, but they're not creating doing a good job and they're underutilized right now." That's a pain point. Another pain point is content distribution. It's very time consuming. We're using five employees right now to each distribute on Instagram, YouTube, LinkedIn, Tik Tok and all these platforms and changing the format and it's taking too much time and too much manpower.
Another pain over here is performance tracking. So people lack the skill and the capacity and the expertise to track the data that's coming from the content and they can't identify what exactly is going wrong. And then content review is okay we posted this content we got this impression likes subscribers followers whatever it is and engagements and interactions and we need to now review our content one whether we did a good job or not and point number two does it match the regulations because meta maybe changed this policy and said hey guys you use this kind of content and this is going against the policy and we know how popular this is especially if you've run ads in the past I've faced this issue a lot and And if especially if you're coming from the SMMA space, you you're going to know this really well. So then you get into that this outcome or outputs being that interactions.
So these are pain points. The next step, what you would do is you're going to look at each of the pain points and you're going to ask yourself, if I solve this painoint, will it hit my AI number or not? If it's a yes, then you put a tick on it. If it's a no, then you put an X on it and you just skip it for now.
So you're going to come up with a bunch of things. You're not just going to do it for one part which but you're going to do it for three because you have three highest leverage task over here. So you're going to do one, two, three and you're going to think in terms of the following. So when I think of this, what are the skills of AI?
What can AI do for us today? One, AI has intelligence which is human intelligence. You can add that human intelligence towards a certain system which is dumb initially and add that human intelligence and make it smarter. So you can make smarter decisions and decide on its own and so on.
You can test things. You can uh put in audio and listen to audio or do whatever. You can send images, read images, look at computer vision and so on. And then you can do some hybrid approach of all of these.
So these are the AI skills. Then I start thinking okay what types of solutions you have. Do you have we have assistants, we have co-pilots, we have agents, we have autopilots. What will be best for this case?
And then I start writing down what would the ideal scenario look like if this pain is solved by an AI. Knowing that I know these skills, I know the solution types that exist. What is the ideal scenario to and I'm not looking at complex complexity or feasibility at this point, but I'm looking at what will be the possible solutions over here. So one solution is for content creation.
AI will analyze the content drafts that I'm going to give it. It's going to check for potential errors. It's going to flag only the relevant areas and need that need manual review and tell me, okay, just review it so I can go to the next step. This is point number one.
For performance tracking for example, AI checks existing content, analyzes content best practices for different platforms. I think this should be go go go here. So this is for content distribution and generates variations of content accordingly. This is point number one.
This is another way to solve this. And this content review AI detects changes in regulation. I did not do this because this was um it's not does not hit my AI number, but this is for here. So AI detects changes in regulation automatically and flags content that needs to be changed and suggest changes.
So this is AI doing and monitoring the policies and so on. And then once I'm done with these, I'm going to say okay, how complex this is to implement. What is the feasibility of all of this? And what's the difference between this manual flow and this AI flow over here?
So that's what I'm going to draw out. And in terms of complexity, I'm going to come to a couple of points to keep in mind when you think of complexity. But at this point, just say, do I have the manpower for it? Do I have the tools for it?
Do I have the knowledge for it? Who's going to do it? Do I have the team for it or not? And what what exactly should I do?
Don't think about how to implement it at this point. So this is just giving you a number in terms of a score. I have a table for it. How to score every single AI use case and how to score every single idea in order to understand how easy or hard it is to implement.
And then you're going to come up with this table or this graph over here telling you that okay, you have one, two, three, four, five waves ways of solving this. And what you're going to implement is one because it's over here in terms of being it's highly feasible and it's highly impactful as well. Then you can come to point number two then point number three then number four and number five. So for this example and this case we're going to look at priority being number one.
And now after this exercise, after doing this for each of the three that we got over here, you're going to have a road map saying that okay, we're going to do this, then we're going to do this, then we're going to do this, then we're going to do this, then we're going to do this. You have a road map. So you're going to forget everything else. You're going to take one and bring it over here, which is step number four, which is a solution concept development.
And now you know exactly where to start. You have a road map right now. So your next step is give me a concept or think about a concept that this solution is like how can I implement the solution and how can I validate whether this is true or not. So I do it in three steps.
Point number one is I understand the current workflow. So manually what are we doing right now which we have from above. I just look at it again and then I look at the AI workflow which is what we mentioned above as well uh in terms of the two workflows. And then we're going to think about who will build it moving forward.
And you do not need to overthink it. This is just one piece of paper saying that okay this is how it looks like. This is what we're going to build and this is then the parties or the people that we're going to assign it to in order to move it forward and so on. Then you have a solution concept over here.
So most of the heavy lifting is done in step one to two to three. And now in step number four you have everything. You're just plug and playing from above. Then in step number five what you do is you look at the feasibility of the solution.
So now you've been thinking about all these amazing ideas with your solution concept and so on and now we bring you back to ground and say okay you've been in the sky now come back to ground and let's see if this is possible to implement today so four questions go into this and it's of course again this is a detailed process I have flowcharts for this I have schematics for this I have boards I have equations I have cards I have everything for this but what I'm showing you in this part over here in particular is that how can you do it really So I ask four questions. The first question is do you already use the right tools or no code platforms to support this? Do you have the tools? Do you have the tech or not?
Do you have any expertise on the tools and the tech or not? Is the data accessible and in the right format? Do you have data to access this? For example, many entities right now governmental entities and even solopreneurs have no data.
That's what I've realized, but most of them like that's most of them. I'm not going to generalize. But is the data accessible in the right format? Because there's something in the industry of system engineering saying that garbage in garbage out.
GGO meaning that if you have garbage data that means you're going to get garbage output. So the data should be clean should be accessible in the right format and so on otherwise AI would be useless in this case. Point number three is will it require some custom development or can it be done offtheshelf tools such as the tools that we have online or should you create something for ourselves and point number four is who's going to build it and whether it's you someone in the team you're going to get external help do you have the budget for the external help or not or not and these are the questions that's going to get you on ground and see okay this is a feasible solution let's try to implement it because I think it's very feasible for us to implement and then we come to step number six over here which is understanding it's feasible. So very very important point.
There's a big misconception that you need to be a coder, programmer, developer or something in order to add AI within your business. You don't need to be any of that because we're in 2025 right now. And there are tools or ways of doing things without using code or using any of those skills that you need. So now there are two ways to go down with this.
And believe it or not, custom GPS can do the job most of the time. And they're not highly re recommended if you're t talking about um highly confidential data and so on. But if it's about writing better emails, planning a certain thing for content and so on, you can use custom GPTs. If not, you can host for example an NA10 workflow.
This is just an example of an NA10 workflow of a no code tool where you connect a bunch of nodes together and just host it locally on your servers instead of being on the net or on the on the cloud itself. And then once you host it locally, you can do whatever you want with your data. And then after you implement it and you know what you're going to go, the route you're going to choose in terms of custom GPTs or offtheshelf tools or no code tools and so on, you're going to measure the outcome and say, "Okay, how much time did I save? How much money did I save?
How much money revenue did it make? What task did this automate or take on? And then you go back and say, okay, we had this target of AI number. We implemented this for one one month, let's say, or 3 months, and we did not hit that target yet.
So, there must be something wrong within whatever we did above or we hit that number, and now let's move on to the next stage. And this process by itself, it should take you like just this process, if we do it in full details, it it takes half a day or let's say one full day. But if you're going to do it yourself in the short version that I showed you, it should take you one to two hours max. So it's not a complicated process.
You're going to think and say, "Oh, this is too much steps. I I don't have time for this." If it's going to make you $10,000 per week or per month, I think it's worth it. So once you implement it and you see everything working and you see, okay, now I know exactly what AI is capable, you'll have this rush of ideas in your head and saying, okay, now there is many things within my business that I can do. and repeat the same process towards and this is where your machine one two three and n will be born and you can add within your business. So we just answered the question of I want to add AI within my business and I don't know where to start and you have the six stepby-step process exactly how I've done it for other people and many people charge you a lot of money for this by the way and you have it right now.
So, if you're planning to add AI within your business or whatever you want to do with AI, follow the six step-by-step process and share it with your team, come up with a report, or even if you don't have a team, do it for yourself, and you're going to see how much you can leverage AI within the gaps within your business to automate everything. And maybe, just maybe, you may say, I don't need any more employees than if everything is possible with this AI thing that's coming up. And that's a point we're trying to get to in the future.