Transcription
If you've ever thought about starting an AI consulting business, I want to tell you the truth. Not the internet version, but the real one. The kind that you only learn when you've done it yourself or you've watched hundreds or thousands of people actually try it. Because I've done both a few weeks ago inside my community, the AI business trailblazers hive. We ran a live six-day challenge. Could you go from idea to your first AI consulting offer in less than a week? And over six days, hundreds of founders joined. Some built working systems, wrote proposals, pitched real clients, and others didn't. They needed more time. They hit walls. And that's okay because this was not about perfection. It was about seeing what it actually takes to turn your AI knowledge into a business. So, in this video, you are going to get the full breakdown of the challenge day by day, and you will see what worked, what failed, and what surprised us. And if you do want to experience it yourself, the entire challenge is still live. It is completely free inside the hive. You can join today and you can build your business alongside the rest of the group.
But first I want to give you context. So I've been a business consultant for more than 20 years. Big four, big tech, startups, governments, and I have helped scale companies across many industries across 50 plus countries. I actually started working in AI in 2017, long before it was trending. And in 2018, I led the first large-scale AI training for students at the big tech company that I was working for, which was actually the first that they had ever done globally. It went viral. We had newspapers, television, hundreds of students. And it taught me something really important. People don't fear AI when they understand it. And that insight has changed my entire career. I spent more years building AI strategy inside that company before leaving to help founders do it for themselves. And today, more than 12,000 entrepreneurs have gone through our programs, our challenges. They've automated workflows. They've built offers. They've launched to real businesses.
But this challenge, this one was different. It wasn't just about tools or tactics. It was an experiment in clarity. It was basically about what happens when you give people a framework, a deadline, and a community, a group of other people, and then you ask them to build something real. It was about what happens when you treat AI not as a technology or as a tool, but as a magnet, a catalyst. So, that's the story of this video. What it really takes to become an AI consultant, the three realities that most people miss, and the exact six-day journey that showed us what's possible.
When the challenge began, I thought it was testing a process, a framework. But what actually happened inside those six days taught me far more than I expected. Because, as I said, hundreds of founders joined from every background imaginable. Marketers, developers, realtors, teachers, designers, even doctors, all trying to turn what they knew into something valuable with AI. And I watched people who had never built before design real systems. And others who'd been in business for years realized that they'd been solving the wrong problems. I thought this was going to be a lesson in speed, which I've talked about a lot on this channel, but it became a study in clarity. And through it, three big massive truths actually emerged. These are basically the three realities that decide whether someone actually becomes an AI consultant or just stays curious about it.
So here are the three realities of building an AI consulting business.
Number one, it is not about the tools. When people first joined the challenge, they expected to spend the week learning tools: GPT and Make and Zapier and NA10 and Notion and prompting, all of it. But the people who built the fastest, they didn't start with tools. They started with questions: with who is wasting time every day, and what tasks keep repeating, and where does effort leak? Because at the end of the day, AI consulting is not about building automations. It's about translating problems into leverage or solutions. And the best participants were not the most technical. Interestingly, they were the most curious. They were the ones who listened to clients before they built for them. Because once you can translate pain into process, the tools become obvious. AI is just the language you use to express the solution.
So, reality number two is that speed is a test, not a shortcut. So, we called it a six-day challenge, but it doesn't mean that everybody finished in six days. Actually, some did cross the line on time, but many didn't. They needed extra days, extra weeks at times. And that's not failure, that's iteration. Speed reveals the friction, and friction is feedback. In consulting, the goal is not to move fast. It is to remove confusion. And sure, some people did build quick prototypes and then they broke. And then others spent longer mapping real workflows, and those systems probably still running today. Speed shows you where your clarity ends. What you do after that is what makes you a consultant.
And then reality number three that came out of this challenge, I think that's the hardest part. Most people didn't struggle with prompting, even though they thought they would. They struggled with permission, their own permission. They would say, "Who am I to be an AI consultant?" And I would remind them that consulting is not about knowing everything. It is about guiding decision-making and discovery. The moment that someone sees you help them understand their own problem, you've already begun consulting. The people who shifted fastest weren't those who mastered the tools or prompting. They were the ones who started speaking like problem solvers. Uh, they were the ones who stopped saying, "I can't automate this for you," and they began thinking about, "How can we eliminate this bottleneck together?" That's the big leap from someone who does to someone who thinks, from user to translator. And once that identity clicks, AI becomes your partner, not your project anymore.
So these are the three realities that shaped everything that happened next. Because when you see AI is not a trend but a mirror, the fact that it shows you where your thinking needs to evolve, you realize that there's more to it. And over six days, we built that evolution step by step. And I'm going to walk you through everything next. But if you do want to take part in the challenge, like I said, you can still join the community. It is completely free. And this way you can get all the prompts and you can talk to everybody else who's on the exact same path as you are.
So let's get started because we've got a lot to cover. Day number one sets the foundation for everything else. Before you talk to clients, before you build systems, before you touch a single tool, you need one extremely important thing, and that is direction. And most people skip this part. So don't be one of those. Most people chase, you know, anyone who's willing to pay, and then they end up solving problems that nobody cares about. The truth is that if you try to help everyone, you help no one. And if you pick the wrong space, no amount of AI is going to save you. So basically, day one is not yet about building. It is about deciding and choosing. So start with what you already know: the industries that you understand, the work that you've done so far, the people whose pain you feel to your bones and you feel comfortable solving, and go from there because that's your unfair advantage. So don't look for the hype, just look for the problem, look for the friction. Okay? Where are teams drowning in repetitive work, or where are mistakes expensive, or where is time leaking every single day? That is where AI can create visible and quick wins.
Now plot these industries on a very simple curve: Innovators, early adopters, early majority, late majority, and laggards. You don't want the extremes. So put those to the side because innovators, they don't need you. They've already advanced. And laggards, I mean, you're going to fight every single step with them in order to convince them that AI is what they need. So you don't have time for that. Now, the sweet spot is in the middle, the early adopters and the early majority because they know AI matters. They just don't know how to make it work specifically for them. So that is why a consultant would be able to earn their trust and build long-term relationships. And then you want to dig into what's already happening in that space. Okay? That's not to copy anybody, but you want to understand the direction of change. You want to read the studies, read the data, go through the use cases because every statistic tells you what people are willing to pay for. And you need to understand that AI consulting is not about being the smartest in the room. It's about seeing the room clearly. And then finally, ask yourself, is this industry digital enough to let AI plug in easily? Or are they still running on spreadsheets and chaos? Because if the foundations are not there, they will need education before automation. That is still valuable, but it's a different offer. Okay? So, you need to be aware of that. And by the end of day one, your goal is pretty simple: Know exactly who you serve, why it matters to them, and where AI can move the needle fastest. You don't want to rush this part because clarity is not fast. Confusion is. And if you want your AI consulting business to scale, clarity is your first asset.
Okay, so let's move to day number two. So this one is about understanding the business maturity model, uh, the core frameworks, and creating your pitch deck. And I know it sounds like a lot. So I'm going to walk you through everything step by step. Okay, this is where we separate builders from consultants. Building is not the purpose of this challenge. Okay? Anyone can use AI tools, but very few can walk into a business or into a room and look at the chaos and say, "I know exactly what's broken and what to fix first." That is what you're learning today. Okay? So, before you automate anything, you have to understand how this business actually runs. Okay? Where it's strong, where it's fragile, where it's bleeding, whether it's time or money or focus or energy. Because if you try to automate a broken process, I don't know how many times to say it, but you are just making the mess bigger, faster, and more chaotic. Okay?
So let's talk about the business maturity model. I've talked about this one in one of the hive holes. Everybody was crazy about it. So, I thought I would bring it back, but if you want um, the longer version of this, you can always join the community. You can go back and watch the full uh, hive hole where I explained the whole framework, or let me know in the comments below and I can make a video about it if you think it's uh, necessary to go even more in depth. What do I mean when I say business maturity model? Well, the thing is, every business is on a journey, okay? From figuring it out to scaling it sustainably. And if you don't know where they are on that path, you cannot meet them with the right solution. Okay? At the early stages, for example, they need clarity. At mid-stage, they need systems. At growth stage, they need automation. And at scale, they need insight. You see? So it's different pains, different priorities. And if you treat a startup like a corporation, you will overwhelm them. But if you treat a corporation like a startup, you're going to insult them. So your first job as an AI consultant is diagnosis. It's not implementation. We're not there. Okay? You want to learn to read where the business is in their maturity and then meet them there. Okay?
So let's talk about how you do that. Before you start recommending automations or agents, right? You need to figure out which type of business you're looking at. The find stage founder has completely different needs than a scale stage CEO. And as I said, if you apply the same strategy to both, you're going to lose trust instantly. And this model is going to help you assess where a business is in their operational evolution. And what kind of AI interventions make sense? Okay.
So a find stage company, they are in the ideation and validation stage. These early founders or creators, they still search for product-market fit. They're struggling with clarity. Well, what do I sell? To whom do I sell? And your AI opportunities are customer and market research, niche brainstorming, MVP testing, because your role is essentially to help them clarify, not optimize yet. They have nothing to optimize at this stage.
Stage number two is their launch phase, the visibility and revenue stage. This is where they know their offer, but they need consistent sales. And the symptoms are basically they have inconsistent marketing, manual follow-ups, poor conversions. And the AI opportunities that you can pursue are content generation, lead magnets, email automation, because your role is to help them systematize visibility and selling.
And this is a business that has revenue but also chaos behind the scenes. Okay? So symptoms could be manual operations, hiring overwhelm, communication bottlenecks, and the opportunities are SOPs, standard operating procedures, process automation, inbox, HR, support agents, because basically your role here is to help them buy back time through automation. This is by far the best type of customer you would be looking to get.
And then four is about scaling, the systematized growth stage. This is a company that has teams and systems in place, but decisions and management are slow. And here the systems are strategic overload and too many meetings and KPI tracking gaps. And your opportunities here with AI are to create dashboards and reporting agents and chief of staff AI kind of um, automations to help them automize decision quality and focus.
So once you see the landscape, you need lenses that help you think clearly. And that's what real consultants use. You know this type of frameworks. One of them is MECE. I talked about it in a previous video. This one breaks chaos into clean buckets so that nothing overlaps and nothing is missed. Another one is OODA. Observe, orient, decide, and act. It's how you move fast without having to guess. Design thinking. I don't even need to mention it. It's absolutely critical. You lead with empathy and you automate after that. We don't have time for me to teach you every single one of them. You can research them. There's lots of information out there. But essentially, these are the difference between sounding like a strategist and sounding like a, I don't know, novice. Clients don't pay you for tools. They pay you for clarity, for confidence, for control. And mastering these frameworks is going to give you that.
But I'll be very quick and I'll try to explain a little bit just so you get the the gist. So MECE means mutually exclusive, collectively exhaustive. And basically what that means is that you break complex business problems into clean, uh, non-overlapping parts so that nothing is missed. So basically what that looks like in practice is that you would divide a client's workflow into marketing, operations, finance, HR. You see there's no overlap. And then you identify gaps or redundancies within each of the areas. You can also use MECE to structure your process maps, consulting decks. Uh, then OODA is about observe, orient, decide and act. And originally this was a military decision loop and now it's used in consulting. Basically, observe means you gather data, processes, reports, conversations. Orient means you make sense of what's happening and where AI could fit. Decide means you choose one high-leverage intervention, and act means you implement and then measure the results. And you can use OODA for lots of things, but you can run AI pilots and then you can test value quickly without overplanning. And design thinking. Oh god, we could probably do an entire training on this. It's an empathy-first innovation model. So you need to empathize to understand users' frustrations, and then define, frame the real problem, not just the symptoms. And then step three is to ideate. So you want to brainstorm solutions with AI and uh, enhanced by AI creatively. Then you prototype. So you build a quick demo using Notion's API, Chat GPT, whatever is more um, accessible to you. Then you test, you validate feedback before scaling. And you can use design thinking to co-create AI solutions that teams actually use. You can use it to do your first workshop with your clients. You can take notes and then reuse these explanations in your later presentation.
Now, let's talk about your three-step consulting process because every consultant has a signature process. And it doesn't need to be complicated. It just needs to make sense. Okay? So, it could be as simple as discovery, design, implementation. You know, uh, discovery could mean that you map operations and you identify bottlenecks and you assess AI readiness. And then design could mean that you apply frameworks to propose AI-driven improvements. And implementation could mean that you deploy, you measure, and then you refine with feedback loops. Because if you can't explain your process in three slides, you don't have a process. You just have chaos with branding. So you need to keep it simple, keep it concise. I don't know, three slides or paragraphs maximum. And then you can work on your pitch deck. You can now finally put everything together. So all the research from day one becomes your evidence. Your frameworks from today become your method. Uh, because you're not just showing the slides. What you're doing is you're telling a story about how your client can move from confusion to clarity, from manual to intelligent. So you can have your slide number one as a way to phrase and frame the problem. Number two would be a slide on the inside, and number three would be the path forward. That's it. You don't have to complicate it more than that. People want direction. And after this day, you will sound and think like the consultant who can give it to them.
Okay. Now day number three. So this is basically the day where you put on your consultant glasses and you see the world like a consultant. Before you recommend a single tool or automation or agent, you need to understand how the business actually works. Not how the founder describes it, not how the SOP says it should happen, but what it really happens. Okay? Day-to-day, step by step, in real life. Because the truth is that if you skip diagnosis, everything you prescribe will be guesswork dressed as strategy that will never work and nobody's going to implement. Most people jump straight into fixing. But the real consultants start by watching. Okay.
So here, ideally, you want to choose a business, any business. It could be a client, it could be a friend's company, or even a case study that you make up. I don't care. But the goal is not to be perfect. It's to observe. To look for a process that is messy enough to learn from, but simple enough to map. It could be sales, it could be onboarding, it could be reporting, it could be customer support. And then do not ask, "What can I automate?" Okay? Ask, "Where does this process break down?" That question will change how you see every business from now on. Okay?
So, in order to map the as-is workflow, what you want to do is grab a whiteboard or a mirror or Canva, whatever, a piece of paper, and start at the customer and trace what happens. Who touches what? Which tools move data? Where does work stall or wait or get duplicated? And you don't need to fix anything at this point, okay? You just need to see it. You need to understand everything because until you can describe a system clearly, you have no business trying to improve it. Trust me, this is the moment that most people get uncomfortable because they realize how much chaos hides in "we've always done it this way." If I had a cent for every single time I heard that.
Now, we need to bring back the frameworks, and I'm going to teach you a couple more because once you've mapped reality, you need to run through two lenses. One of them is the value chain. You want to trace where the business actually creates value for customers and where time gets lost in the support work. So, if it doesn't create or protect value, it is a candidate for change. And then you want to use the three-lens diagnostic: So repetition, meaning automation potential; delay, meaning integration or workflow fixes; and decision complexity, meaning where AI can assist human judgment. And once you do this, you're going to start seeing patterns. Okay? Tasks that repeat daily, steps that wait on approvals, decisions that are made from gut feeling instead of data. And that is your gold mine because AI does not replace the people, but it replaces the friction within those bottlenecks.
And now we go back to the map and mark what we see. Okay? So, um, you can do it as easy as using some emojis like um, this can be automated. This is where it needs a human uh, intervention. This is a bottleneck that's slowing everything down. You don't worry about the tools at this point, right? The insight is the value. This annotated map is your first consulting deliverable, actually, because it's proof that you can see what others are missing. Because when you can walk into any business and say, "Here's where your system is leaking time, here is how AI can help, and here's what to fix first," then you are no longer just a freelancer. You are a strategist. Okay? And I think that's the entire point of day three. It is to train your eyes to see leverage that is hiding in plain sight.
Now day number four is about designing the to-be, the future state. Okay? This is where we no longer analyze, but we go into architecting. Okay? Because yesterday, so the day before that, we mapped the chaos, the mess. But today we design the masterpiece. This is the point where we are not a fixer, but we start thinking like a builder. This is only when we start building. Most people use AI to patch broken systems. Consultants use it to redesign them. So your main job right now is to imagine what the business could look like when every repetitive, every low-value task is handled by AI, and humans focus on judgment, on creativity, and on connection. Because that is the real future of work. I believe AI handles repetition, and humans handle strategy and direction and creativity and imagination.
And I have another framework to throw in for you. This is the CDA loop. So the capture, design, and automate. This is a simple framework that keeps you grounded. So capture stands for where does information enter the system: emails, forms, spreadsheets, chat messages, every entry point is an opportunity to automate. Then design: once you capture, how should information move? Then you look at who needs it, uh, what format it is required in, and so forth. And then automate: finally, you need to look at what can AI take over completely. You're not looking to add tools at this point. You're looking to build a logic for how work should flow. Automation without this architecture is just AI duct tape.
When we build the to-be map, we need to take the process that we mapped the day before, the messy manual version, and redraw it for the world we would actually want to work in, or our clients to work in. And as I said, you need to mark what stays human, what becomes human-AI collaboration, so human-in-the-loop, and what runs fully automated. So this will become your to-be map. This is a visual version of how you can help them transform. And I do understand that the first time you do this, it might feel abstract. But the second time and the times after, you will realize that it becomes addictive. Because once you can see how the system should run, you can never unsee the inefficiency that it goes through at the moment. And only now we select the tools and agents. Okay? Because now that we've designed the flow, we can fill in the process or the gaps. So we get to pick what matches, you know, the problem and the solution, whether it's NA10 or Zapier or Make for moving data or automations, GPT for cognitive support, Relevance AI, or maybe it's Airtable, or Asana, or Notion for operational visibility. It depends a lot on the use case. Okay? So I can't give you all the tools that exist out there or that we use because we use a lot of them, but specific ones for specific outcomes. And I think the bottom line here is that you don't want to use every tool. You want to orchestrate a system that feels simple enough and effortless. Great consultants do not collect apps. They compose. They design. They architect those systems.
Now, once your new system is running, you don't walk away. You iterate. Okay? You need to go back to your OODA and observe what's working, what's failing. Orient: what does the data tell you? Decide: what's the next small improvement? And act: implement it again, and test again. This is how your clients are going to see progress every week instead of every quarter. Okay? Because the best AI systems are not perfect. They're living. They're alive. When you build with loops like the OODA loop, you design systems that think with you, and not for you. You don't want to get there. Okay? So by the end of day four, you will have something that most consultants never create. You'll have a clear visual blueprint of what a business can become after AI transformation, an architecture, if you will. And clients don't buy automation, you know, they buy clarity that they can see, and this helps them see everything clearly.
Now we get to move to something just as exciting. So day five is about the proof of ROI. Okay? Because we need to make sure that your ideas become investments. That you've designed the future state, but that it's not just a smart and clean AI-powered version of a business. It is also something that drives ROI. ROI stands for return on investment. And that's because no matter how creative your vision is, if you can't prove that it saves time or makes money, it's just another pretty deck and a dream. Executives don't buy AI, they buy the outcomes. And your job is now to translate potential into proof. Okay?
You can think of the AI ROI canvas as your translator. It can convert the tech excitement into business clarity. Because you don't need to say, "AI will automate reports." You should say, "AI will save your team 5 hours a week and cut reporting costs by 40%." That is the difference between being heard and being hired. Every good ROI story has five parts: Problem, what's painful? Process, where does it happen? Metric, how can we measure it? Benefit, what does it improve? And tool, how does AI make that happen? Because the more specific your numbers are, the faster people will trust you. Because clarity doesn't just sell, it scales.
So, next you want to calculate the impact. Okay? You don't need a finance degree to prove ROI. You just need a calculator and a bit of common sense. You need to look at how many hours are saved times the hourly rate, or how many mistakes are reduced times the correction cost, or uh, what is the speed improvement times the volume gain. You want to keep it simple and credible and real. So, for example, if an AI tool saves um, let's say 12 hours a week for $33 an hour, and then times 52 weeks, that's about $21,000 a year that are saved. So, you're not selling software, you're selling the result. And once you show the math, the authority multiplies. Data doesn't persuade, but clarity, data with intention does.
So, now you need a one-page proposal. Okay? We need to wrap it all into something that decision-makers can say yes to. And you want to keep it tight. Just one page, one offer, one outcome: who they are, what's broken, what you'll fix, why it is important to them, and what happens next. Don't bury them in a lot of tech. You want to speak their language. You want to speak efficiency, profitability, scalability. And we can validate this in a one-week proof of concept. That single sentence gets you more "yeses" than any buzzword ever will. Because if you can't explain your value on one page, you don't understand it yet. And you want to make it visual, okay? You want to make it visible. You want to turn your proof of value into a before-and-after slide, ideally. And if you can say, "Here's how it was, and here's how it will be." Numbers make people think. Visuals are going to make them believe. Okay? So when you can hand a CEO a one-slide ROI summary that shows time saved and money gained or errors eliminated, you are uh, becoming a partner in their strategy, and that is the level that you're aiming for. So by the end of day five, you will be able to do what probably the majority of AI enthusiasts can't. You can prove the value of your ideas in dollars and decisions. Because the future does not belong to the people who know AI. It belongs to the ones who can justify it. Okay? Who, who can sell the value of the result.
Now day six is where we define the offer, the methodology, and we build a lead generation plan. This is the data that all comes together because you will have spent at least the last five days thinking like a strategist, researching, mapping, designing, proving. But today you need to start positioning yourself because ideas don't build businesses. Offers do. Clarity of offer is what separates professionals from aspiring entrepreneurs and pretenders. You can be brilliant with AI, but if people can't describe what you do in one sentence, they'll never buy it. So today is about turning your knowledge into a message that the market understands and is willing to pay for.
So step number one: Define your value proposition. And you can start simple. You can say, "I help this type of businesses achieve this type of result using AI to do this." You don't have to overthink. You don't have to overcomplicate. It's just ego in disguise. So you can say something like, "I help real estate teams close more deals using AI to qualify leads automatically." That is direct. It's simple. It's specific. It's measurable. Because if your offer can't fit in your LinkedIn headline, it's not ready for the world.
Now, step number two is designing your consulting methodology. Every credible consultant has a named process. This is what's going to give you authority and positioning. Your methodology is what turns a freelancer with AI skills into a trusted advisor with a system. Okay? So, you want to pick three to five phases and give them names that reflect how you work. So you could say, um, "I capture and design and automate," or the "3D Consulting Method: Discover, Design, Deploy." Whatever you call it, it doesn't matter. It's less important, but it needs to answer one client question: "Can this person guide me from confusion to result?" People don't buy AI skills, they buy certainty of results. Okay? And that is one extra layer of giving them that certainty.
Now, step number three is about creating your offer package. Um, packages turn expertise into income. There is no other way. And you can start very, very simple. You can have a strategy package: So a short audit, clarity deliverable, fast wins. You can have a design and implementation package where you build the system, measure the ROI. And you can have a retainer advisory where you stay on board as their AI partner for continuous improvement. Don't hide behind custom quotes yet. Uh, define ranges, set expectations, and own your value. If you don't price your work, the market will, and it'll be lower than you deserve. So do yourself a favor here.
Now, step number four is about building your lead generation plan. And again, we could probably make a whole course on this. You don't need a website. You don't need um, anything too complicated. You just need momentum. So, the simplest way you can get started is to start where your people already are. So, post your insights on LinkedIn or on X, even if it's once a week. Share a before-and-after screenshot from your challenge work. Um, offer a free AI process audit to start conversations. DM five people in your niche with a personalized note. But don't wait to feel ready. You get clarity from conversations, not from planning or thinking. You don't need followers. You just need the proof of results. And the first client is going to give you that. And probably even more important, they're going to give you momentum. Okay?
So, by the end of day six, you will have what most people spend months avoiding: a clear offer, a repeatable methodology, and a real plan to find clients. When the challenge ended, we didn't close a chapter. We opened one. Because what most people discovered wasn't how to start an AI consulting business. It was how to think like a consultant. And as I said, some people finished in six days, and others are still refining their systems for what I know, you know. But all of them learned that this is not a one-time sprint. It is a lifelong skill that basically teaches you to see problems as processes and processes as leverage. That is what separates those who use AI from those who build with it. AI consulting isn't about being first. It's about staying in the game long enough to become irreplaceable. Because once you know how to find pain, design systems, and deliver results, you're always going to have work. You will always create value. And that is what this community is about.
Okay? The six-day challenge that we have created and that I've just walked you through, it is still live. It's free. And you can start it right now inside the hive. You're going to find every prompt, every template, every framework. But more importantly, I think you will find people who are on the same path, who are testing, who are building, who are iterating together. Because building an AI consulting business isn't about racing ahead. It's about learning faster with others. So if this video gave you clarity, come build it with us. Your next client, your next system, your next leap in confidence. It might just be six days away. I am going to see you on the other side inside our free school community, the AI business trailblazers hive. And I look forward to welcoming you there, to seeing you in our community calls every two weeks, answering your questions, and supporting you along the way. Thank you so so much for watching this video. I really hope that this longer form gave you a lot more value, a lot more clarity. I really hope that it inspires you to take action. And like this video if you did. Be sure to subscribe if you haven't done so, and also share it with anyone in your circle of friends or family who you think might be a good fit to become an AI business consultant and who would benefit from watching this video. Thank you so so much again. I really appreciate you giving us your time. I know how valuable it is, and I do not take it lightly. And I hope to see you in the community. Bye.