# How I'd Make Money with AI in 2026 (Top 3 AI Offers)

Channel: Ben AI
Video: https://www.youtube.com/watch?v=XYHqQOX4ivs
Duration: 17 min
Language: English
Words: 3458
Transcript page: https://viewrankai.com/tools/youtube-transcript/XYHqQOX4ivs

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[0:00] In 2026, 90% of businesses have dedicated AI budgets and according to an AWS survey, 65% is planning to rely on thirdparty providers. Many businesses are behind. So being just a few weeks ahead of the curve allows AI freelancers and AI agencies to tap into this demand. But across more than a thousand sales calls in my AI agency last year, we're also seeing firsthand that buyers are becoming more skeptical, are sick of AI hype, and want to see real ROI fast. So, in this video, I'll show you what businesses actually need from AI service providers in 2026, the new way to pitch AI services, and the three simple AI

[0:36] offers that get skeptical businesses through the door. So, as I said, for almost all businesses, AI is one of the main priorities in 2026. Boards are pushing, CEOs need to have AI strategies in place, and there's a lot of FOMO. Most companies just don't have the in-house expertise to start implementing it themselves. And this is why we're seeing stats like 65% planning to rely on third party providers. But in 2026, we're mostly not selling to the early adopters anymore. Most of the early adopters, the risktakers, uh the businesses that like to experiment are already implementing AI internally or working with AI partners. So if you want

[1:10] to sell AI implementation to businesses in 2026, you're now mostly selling to the early majority. And the early majority buyer is different. They're less educated on AI. They're less risk-taking and far more skeptical. They're also not as willing to experiment and they want to see real ROI and they want to see it fast. And the point I made in my last video is that in order to get real ROI out of most AI solutions at the moment, AI providers

[1:34] shouldn't just provide AI development. Because what businesses actually need are long-term AI partners that provide a mix of continuous strategy, education, and implementation. Because if you skip strategy, you often build the wrong thing. If you skip enablement, the team often doesn't use it. And if nobody owns it internally, adoption dies usually after the launch. So if you sell this service layer, strategy, enablement, and implementation, you often become a company's long-term AI partner. This is also how you actually get a stable AI business off the ground. Most of my AI accelerator members who get to 10K a month consistently get there by working with two to four long-term clients on AI

[2:13] partnerships instead of dozens of one-off projects. And we see the same in my AI agency. We have clients on multiple six-figure a month retainers that are relying on us for AI adoption in their companies. And these are huge yearly revenue deals for my agency. And the majority of our annual revenue now comes from these recurring AI partnership deals. But this creates a little bit of a paradox, right? Because on the one hand, many of the early majority buyers want to see ROI fast, but in order to deliver it to them, we need time, commitment, and investment from the company. Because if you think about it, for many AI projects,

[2:46] realistically, a timeline to see ROI out of a custom AI implementation can take months, right? An average process with a midsized business or even a small business can look like this. Two to six weeks in the scoping and proposal process, two weeks in onboarding, one to three months in development, another month in testing, and then another two or three months till it actually becomes clear to a business owner if there is ROI. That's easily 6 months of time invested, a lot of money spent for a type of buyer that is still very uncertain around reliability and compliance. And for an early majority buyer, this is a terrible value

[3:20] proposition. And besides that, there are many other blockers that make this even harder. Many businesses have no idea where to start or what's possible yet. Many still run on legacy software or the data infrastructure just isn't set up to get started with AI yet. They also need to trust you as a vendor, deploy and allocate internal team members to manage this. And all of these factors combined make the chance of converting these more skeptical buyers onto custom AI automation builds or AI partnerships

[3:46] very low. We've seen this firsthand. We've had hundreds of businesses not converting for one of these reasons above. So, the question becomes, how do we get a foot in the door with these more skeptical clients to win their trust and eventually get into a long-term AI partnership? Just like in other technological revolutions, what and how we pitch should change when we cross what they call the chasm. It's a book that I recently read which talks exactly about this concept. Highly recommend reading it if you're interested. I'll put a link in the description, but it basically means that the mainstream market is more pragmatic and it means we can't just throw AI at

[4:19] them and a vague timeline of ROI and expect them to close. If we pitch that to a more pragmatic buyer, it's like asking someone to marry you on the first date. So what we need is a starting offer that d-risks it for the client, gives them certainty and lowers the friction to get started. Now in my AI agency and across my AI accelerator, we found three offers that are best as initial offers to get skeptical businesses through the door and can naturally lead into AI partnerships. Now the first one is to offer a quick win productized solution. Now, we landed on this sort of by accident because besides

[4:52] my AI agency, I also sell a productized AI SEO solution and a productized recruiting solution. These are essentially pre-made NAN automation systems that automate SEO and recruiting. Now, they all target different businesses, but there are three things we noticed. First of all, many businesses that weren't necessarily even looking for SEO or recruiting solutions booked calls for these

[5:13] solutions instead of our custom agency. Second, our productized offers have far higher conversion rates for us than our custom agency at 30%. And lastly, many who started with our SEO system or recruiting system then continue to work with our AI agency after. Now, the these don't have to be perfectly productized or or a SAS yet. I'll get to that in a second. But why does this happen? I believe it's because these productized solutions really talk to the needs of the early majority. First of all, because through these more productized solutions and demos, businesses immediately see what can be done for them. Many buyers are still undereducated in AI. And it reminds me a

[5:49] lot of uh the Steve Jobs quote, "People don't know what they want until you show it to them." And I think that quote is very fitting in AI and automation because many buyers simply don't know what's possible yet. And this is why demos on YouTube and LinkedIn work so well because you show businesses what's actually possible for them. Second, through these more productized solutions, ROI can be proven a lot faster. Our SEO and recruiting systems can be deployed, for example, in less than a week. We even sometimes give them a sandbox so they can play around and try the product before buying. And this speeds up the deployment a lot. And of

[6:20] course, an ROI return can be expected a lot faster. And thirdly, one really interesting thing we noticed is that because we also give them training and consulting on how to use the system and work with AI for 45 days, we automatically educate the team a bit. And more importantly, we get an AI operator in place that is in charge of using the tool. And what we've seen is that this often gets the momentum going in the company. It opens the eyes of the team and the business owner on what's possible, how to work with these tools, what can be achieved with AI, which leads to a far higher commitment

[6:51] internally to invest in expanding with AI. We've seen uh even nontechnical people start to build on top of our NAN solutions to expand its capabilities or customize it more. And for many of these businesses, the natural transition was to continue working with our AI agency to expand beyond this initial use case. Now, does this mean you have to have a perfectly productized solution? No. What it means is basically you want to identify a repeatable use case for your niche that you know can deliver ROI and ideally fast. It means you want to show them demos to see what's possible in the sales process, even on your website, and

[7:25] in your marketing. I've gotten in so many clients uh in the beginning and and still just by showing and building stuff I thought could be helpful for businesses in my niche. Even if you have no idea of a specific solution yet, the same principle applies when you talk to a client. You always want to try to find and spot the quickest win possible as a first project with any client. Instead of trying to pitch a massive deal that will take months to deliver, your initial goal is to get them invested and build the trust and the relationship and in order to get that long-term AI partnership. But what if you're just

[7:56] starting and you don't have any idea of a specific solution yet? The second one that's working really well right now is to offer AI audits. We've recently started this and it's one of the highest converting initial offers for AI agencies at the moment. And it makes honestly perfect sense why. Uh first of all, because an audit gives the early

[8:13] majority buyer exactly what they need. They get clarity on the ROI because through an audit, you and them will understand what to automate first, what the potential ROI can be. even if they still arrange, it's still 10 times clearer than let's just build and see what happens. Second, we remove a lot of the risk for the client because through an audit, you show them that you understand their business, the data, the compliance, and their constraints, and

[8:36] you show them that you're professional. And thirdly, it's low friction. It's usually a short engagement with a clear deliverable in usually around two weeks with a lower investment for the company, not a six-month gamble. So, these AI audits can be done anywhere between $2,000 to $10,000 or even more depending on the company's size or can even be done completely for free with the right clients because the money will be made again in the partnership later on. And although it might sound complicated to do, it's not. In fact, most agencies or people that have built something for a business already have already done this in some shape or form. So, how do you do

[9:10] it? I recommend doing it in around two weeks where you do three things. First, you interview the business. You don't just interview the CEO. You also talk to the people doing the work. So ideally you talk to five to 10 stakeholders or managers depending on the company size in all the main business departments. So in marketing, sales, delivery and support, you're basically just asking questions about their processes, their current pain points and bottlenecks. For example, uh where's your time being burned right now? Uh what errors are happening in your workflows? What data is still moving manually? And these can be like 30 to 45 minute interviews. And

[9:43] with the call transcripts, you can do a lot already. Now once you have that you map the current workflows in the business and find the opportunities. Ideally you diagram the main processes in the business in acquisition delivery and support. Then you translate what you learned into a process map and in there you can identify AI and automation opportunities. And you don't need or

[10:03] want to give them 50 different ideas. You want to prioritize and show them the lowhanging fruit use cases. And then lastly you create a nice slide deck with the opportunities and the potential ROI. Ideally, you show them uh the top three to five opportunities. You show them the quick wins versus the bigger projects and then a plan or a road map where you prioritize quick wins and you show them what the ROI for each of the projects could look like. Again, this is sometimes hard, but even if it's a broad

[10:29] range, again, it is 10 times clearer. Then let's build something and see. And this is why audits are such a natural setup for long-term partnerships because at the end of an audit, you're basically saying here's the plan we build together. If you want results, the next uh step is implementation. And we've seen 70% conversion rates to AI partnerships after AI audits. Now, if you're interested in understanding exactly how we do our AI audits, I prepared a free guide in the link in the description which you can download. Now, what if you have no experience yet? An AI audit might sound a little bit intimidating uh still and you might not

[11:00] have a good use case for a productiz solution yet. Now, a third one that is really good for beginners to do are AI workshops. Now, AI workshops are one of the best foot in the door offers for these early majority buyers because it's really one of the safest yeses. They might be skeptical of custom builds, uh, big projects or investments yet, but almost all businesses are willing to invest in education, especially around AI right now because they know they need internal capability and it's generally low investment and completely risk-f free for the business. you're not touching their data or their software and workshops actually work great to get

[11:35] businesses to convert into AI partnerships because first of all it creates that bottomup adoption which I talked about before the best use cases often don't come from CEOs or manager level but they come from the employees living in the actual work and the workflows and when a team experiments starts building things and gets uh one or two small wins it tends to spread internally leadership gets pulled in and when employees want more of it becomes really a no-brainer container for CEOs and we've seen this firsthand again a lot of businesses including enterprise clients that we work with came through their employees they were the ones self-educating through my YouTube

[12:11] channel they started experimenting with automation in their own company sharing it internally to the managers and when momentum grew in the company and they wanted to expand on AI my name came up and second it turns AI into something more concrete for them again most of the world doesn't really know or understand what's possible and what not if you know you're still in a bubble. 90 99% doesn't uh and a workshop can really open their eyes. They start to see what's possible inside their workflows with their bottlenecks because often these generic AI demos don't really apply to the company's day-to-day. And thirdly, it can really reduce the replacement fear

[12:47] because funnily enough, and not a lot of people talk about this, but we see this a lot. A lot of teams and companies really think AI means replacement and that's a big reason for the sort of passive resistance still and a good workshop can really flip that. It shows them that AI really is leverage that it can help them focus on higher value work and the boring stuff can be automated and when employees stop feeling this

[13:10] threat the adoption tends to go up too. Now how do you do an AI workshop? And the key is to not make them generic and a simple structure you can follow is before the workshop you send them a short survey to the entire team with a couple of questions right it can be really short you basically ask them what are your biggest time drains uh what do you hate doing every day uh or where are your biggest inefficiencies once you have that in the actual workshop which you ideally do for the entire team in the company uh you can do this online or on site if you're able to but first of

[13:40] all you want to teach the fundamentals right you teach them uh the AI automation basics use cases, demos, where works and where it fails. Remember again, most businesses have no idea about this yet. So, you want to keep this sort of surface level. And then what you want to do is show one or two real uh demo use cases of AI and automation live based on the bottlenecks you found in the survey. So, they see what what's possible for them immediately. And this can really give them that wow moment and again lead that to that internal adoption. And the same thing happens here. All right. After

[14:10] this initial step, excitement and momentum grows and the next step becomes clearer. Some companies want to go deeper on training which is uh for example uh something that 9X does. Uh their next step is to sell courses and hackathons with the internal team. But an obvious next step is to also use it as a trigger to do an AI audit or move straight into implementation if they are uh already bought in. Now really the point of all of these offers is not to cash in big on them. The point is to warm up the customer. It's a low-risk investment, but it really can build that trust and relationship, which is the key

[14:41] factor to working with businesses over the long term, which is what actually is going to give you that consistent cash flow in order to build a sustainable business. Now, do you want to start working on all of these types of offers? Probably not. You're never going to be great at all of them, and you don't really need to be. You probably do want to focus on one, at least initially, to improve conversion rates and adoption from these more skeptical early majority buyers. So if you already have some experience and know a repeatable use case, start pitching productized solutions more and more in your content on your website, in your sales calls,

[15:12] and you really might see higher booking rates and conversion rates. If you have business experience, start pitching AI audits again as your CTA in your content on your website. Uh you don't need to do Mckenzie style consulting presentations. You can just take a template, do the first one or two for free to learn, and you'll see that some of these clients might actually already convert into long-term clients. And if you know AI tools but have less experience, start pitching AI workshops more in your CTAs and socials. Another strategy is to partner up. There are a lot of agencies uh popping up right now. My community is

[15:42] full of people building and scaling their agencies. Some people are more focused on education, some more on consulting and some more on implementation. And partnering up with uh people to be able to provide this mix of services or offers makes a lot of sense too. We do this for example because we don't really focus on uh AI workshops and internal training. So we partner with companies like 9X that are extremely good at the business education side of AI and this can really become a mutual beneficial collaboration. Now if you want more help a network with people who are building and scaling their own agencies and and AI businesses, help on

[16:15] how to acquire customers and offer these types of products. You can also check out my AI accelerator where we go in a lot more depth around all of this. Remember I have a full um guide on how we do AI audits in the in the description below too. And this is all great, but you still have to learn how to actually close deals, scope projects, and build automations. So, if you want to learn how to do all of that, you can check out my free 5h hour AI agency

[16:37] course here above. Thank you.

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