Imagine a world where the very magic we create with AI. Well, it starts automating us. Kind of sounds like science fiction, doesn't it? A bit unsettling, maybe. It definitely can feel that way. But here's where it gets really interesting, especially if you're in this space. This isn't some dead end, not at all. It's actually this huge new opportunity opening up. A real lifeboat, you could say, in what's already like a $50 billion
market. Welcome to the Deep Dive. Today, we're really going to get into the changing landscape of AI services and specifically this crucial pivot moving away from just building AI automations towards offering high value AI consulting. That's the core of it. We're going to unpack why, you know, traditional AI development work is becoming a commodity, basically. Then we'll hit you with some. Pretty surprising stats about AI projects
that just don't deliver. We'll walk through a real case study and agency that made this pivot work big time. And finally, we'll break down the exact playbook step by step for how you can land these high value AI consulting deals yourself. Yeah, our mission today is pretty clear. Give you a solid roadmap, throw in some surprising facts along the way and help you navigate this shift. Maybe even claim your piece of this growing
market. So let's get into it. OK, so for years, if you ran an AI agency, man, it was like you had a golden ticket, right? Businesses were just desperate for help. They pay for almost anything you could build. Oh, absolutely. The demand felt endless. But the ground has fundamentally shifted under our feet. The real problem now, the AI tools themselves, they're eating the development work. I mean, think about it. You've got tools
like Claude. advanced AI assistants that can spit out complex visual automation flows like NAN workflows from just one sentence. It's wild. Yeah, or Microsoft Copilot just watching you do something and then building the automation for you. Exactly. And even for the coders, you've got environments like Cursor, these AI coding assistants, making developers massively more productive. It's a different world than even a year ago. And what's really interesting is
the clients, they're getting smarter, too. It's not this black box anymore. They're using these tools themselves, getting rough drafts of automations for free, basically. And they're starting to ask, you know, pretty logically, why am I paying you thousands for this? Precisely. And that leads straight to this race to the bottom on price for the simple stuff. If your only value is the technical build, uh -oh, that's a dangerous place to be. You just can't compete on price alone
against an AI. It really does feel like a freight train. Commoditization just barreling down on businesses that are only focused on building. It's a real wake -up call. So, okay, if building is getting squeezed, what is it that businesses really need? What are they actually looking for in this AI space now? You know, it's less about just finding a builder. What they're really seeking is, well, a guide. Someone to give them a clear strategy. And crucially, someone to train their
teams. That idea of a freight train. It might sound a bit doom and gloom, but here's the flip side, the opportunity. While that technical work is getting commoditized, the strategic work, that's becoming more valuable than ever. It's fascinating, isn't it? Businesses have these incredibly powerful tools now, but that doesn't automatically mean they have winning strategy. They're often just stuff. And the numbers, frankly,
they're kind of staggering. Estimates suggest something like 80 % of corporate AI projects, they fail to deliver what they promised. And get this, in 2024, 42 % of businesses said they actually scrapped AI initiatives after starting them. 42%. Wow. And when you ask why, over half point to the same thing. Lack of internal skills, lack of expertise. That's the number one barrier.
It's like you said before. It's like they've got the keys to a Formula One car, super powerful, but they have no clue how to drive it or even where the racetrack is. What's the goal? They're just spinning their wheels. And that situation, it's created this massive underserved gap in the market. Businesses don't just need builders
anymore. They desperately need trusted advisors, strategic partners, people who can help them cut through the confusion, make sense of the AI world, and actually create a clear, actionable roadmap that leads to real results. And that is your lifeboat, the AI consulting market. It's absolutely exploding. We're talking growth projections heading towards, what, over $73 billion by 2033? And here's the kicker. The big traditional consulting firms, they're kind of missing the boat here.
They're too slow, often too expensive. It's genuinely a wide open field right now for smaller, more agile players. OK, so the need is clear. The market's there. How did one agency actually do it? How did they make that pivot and start cashing in on this? Well, they learned by doing. They actually took a bit of a hit up front to gain that crucial experience. All right, let's walk through this agency's journey. It really shows how you can go from, well, losing money to landing
these really significant deals. It's quite the story. So, stage one. They called it the $30 ,000 learning experience. Their first shot at an AI consulting audit was with this big company, Asmus Steel, in New Zealand. They were keen for a big name, right? So they made a classic mistake, offered an eight -week comprehensive audit, totally free. Ouch. Yeah. The result, a net loss of about $30 ,000. Painful, for sure, but also a necessary lesson in valuing your own expertise. But here's
the twist, right? That $30K loss. Probably the best investment they ever made. Because that free audit was so good, so thorough, it generated a quarter million dollar development pipeline for them. They found like 15 high impact opportunities, all with super clear ROI calculations laid out. The client was basically ready to sign on the spot. So the lesson was, sometimes you got to invest in learning, even if it costs you up front. It was like a real world MBA in AI consulting
paid for the hard way. Exactly. Then came stage two, the first paid success. Armed with that experience, those frameworks, they landed their first paid audit. This time, they charged $30 ,000 for a six -week engagement. They were faster, more confident, and it proved businesses were absolutely willing to pay a premium for that strategic clarity. And now, stage three and four. They've hit the sweet spot. They're consistently landing $60 ,000 four week audits. They've even
got proposals out for $80 plus engagements. They're building a multimillion dollar practice, really. Yeah. And these high value audits have become the perfect way in. They set up these long term partnerships and the big development deals just flow naturally from that initial strategic work. That's a serious transformation. But OK, for someone listening, thinking about trying this. Where do you even start? How do you find the right clients for this kind of strategic work?
It really comes down to understanding their size, their structure and what they genuinely need right now. And what they found, which is really useful, is that there are basically two distinct markets. for this kind of AI consulting. Getting this distinction right, it changes your whole approach. Right. First up, you've got what they call the small smalls. Think businesses with maybe one to 50 employees, usually founder -led, pretty agile. They're often running on modern
cloud tools already, Make .com, Airtable, Slack, that kind of stuff. What they want, immediate ROI, quick wins, now. They don't need a huge strategic plan. Exactly. So for them, a shorter two -week AI opportunity assessment is the perfect fit. price point, maybe $5 ,000 to $15 ,000. It's all about speed, tangible results, fast. Okay. And then there's the other group. Then you've got the big smalls, more established companies, right? Maybe 100, 200, maybe more employees,
multiple departments. Decision -making is more complex. And they probably have a mix of systems, some new, some legacy. Yep. And while they definitely want ROI, too, their primary need is often different. It's education. It's long -term strategic planning. They need to understand how AI fits into the whole picture. So for this group, the full four -week AI audit makes sense. And the budget reflects that anywhere from $30 ,000 up to $100 ,000 or even more. So tailoring your pitch, your offering,
to whichever group you're talking to. That dramatically increases your chances of closing, right? Because you're hitting their specific pain points. Absolutely. You're speaking their language. Okay. Knowing your customer is key. So let's focus on those bigger deals for a second. What does that full, say, $60 ,000 AI audit actually involve? What's the structure? Right. It's a really structured four phase process. It's designed to take a client from feeling confused and overwhelmed to having
like absolute clarity on their AI path. So phase one is all about discovery and scoping, usually the first two weeks. The goal here is just to understand the business like really deeply. You're doing stakeholder interviews, talking to everyone, CEO down to the people on the front lines. And critically, you're not asking what AI do you want? No. You're asking about problems. Exactly. What takes up most of your time? Where are the
biggest bottlenecks? If you had a magic wand, what frustrating thing would you just zap away? That kind of stuff. And your mapping processes, too. Oh, yeah. Visually mapping critical business processes, lead gen, sales, onboarding, whatever it is, that alone often reveals shocking inefficiencies they didn't even know were there. Plus a tech audit, right? Yeah. Looking at their current stack. Data. Yep. Got to get the full picture.
There's CRM, project management tools, where their data lives, how clean it is, all of it. That's phase one. Okay. Then phase two. Phase two is the deep dive analysis, usually week three. This is where you kind of go into your cave with all that info you gathered. You identify every single task, every process that could potentially be automated or boosted with AI. Then you prioritize them. Simple grid. Potential impact, one to five, versus implementation effort, one to five. Looking
for the sweet spot. Exactly. You're hunting for the quick wins, high impact, low effort, stuff that builds immediate momentum and shows ROI fast. Get those on the board first. Makes sense. Then week four is phase three. Phase three, opportunity and roadmap creation. Week four. This is where you pull it all together into that clear strategic plan. For the top three to five opportunities you found, you flesh out detailed use cases. Like, here's the current messy state. Here's
the proposed future with AI. And here are the specific measurable benefits. Like, this will cut client onboarding time by 15 hours a week, saving the company $30 ,000 a year. Really concrete stuff. And then you build the roadmap. Phase out, starting with those quick wins you identify. Yep. And finally, phase four is the deliverable itself, the AI transformation plan. And look, this isn't just some dusty report they stick on a shelf. It's a comprehensive executive level
presentation. It gives them everything, the audit findings, those detailed use cases, the implementation roadmap, and crucially, a clear financial projection of the ROI. It really shows them the path forward, give them confidence. That sounds incredibly thorough, a really solid structure. But you mentioned something like a secret sauce. What really elevates this? Yes. It's the depth of that process mapping, that forensic level analysis. That's the key.
This is really what separates, you know, the amateurs from the pros in this consulting game. The depth of the process mapping you do back in phase one. It's not just drawing a few boxes and arrows. It's like forensic business analysis. You're basically a detective hunting for inefficiency. Right. Because without really understanding how work gets done, how information flows. Any solution you propose is just a guess, really, a shot in the dark. You need to meticulously map out the
core arteries of the business. Customer acquisition from that first ad click all the way to a signed contract. Where does data get dropped? Where do follow -ups fail? Service delivery, too, right? Sale to project completion. Absolutely. Where are the manual handoffs? Where are the delays? Customer support ticket to resolution. How often does a customer have to repeat their issue? That's a big one. Even internal stuff, like decision -making processes. Where do approval... Tools
get stuck. And super critical, internal data flow. How does information move? Where is it created, stored, lost, maybe entered incorrectly? You map it all. And the goal through all of this is finding the bottlenecks, the choke points, places where things slow down, break, or just involve tedious manual work. Exactly. Those bottlenecks, they're gold mines. Absolute gold mines for finding high impact AI opportunities. Without that complete holistic picture, you're just guessing. It really
is the foundation. It's the absolute foundation. Okay. So that deep mapping is clearly the differentiator for the big audits. But what if someone's just starting? Maybe doesn't have the resources of the client for that $60K deep dive yet. Is there a smaller way in? Totally. That's where the two -week opportunity assessment comes in. It's the perfect entry point. Yeah, you're right. Not everyone can or should jump straight into a $60 ,000 four -week monster audit. That's why this
foot -in -the -door offering is so smart. The two -week AI opportunity assessment, it's perfect for those small, smalls, remember, the 1050 employee businesses. And the price point is much more accessible, maybe $5 ,000 to $10 ,000. And the goal here is different too, right? It's about delivering really tangible value super quickly. Build that trust. Right. And create a roadmap that might lead to bigger things later. It's a way to prove your value without asking for
a huge upfront commitment. Exactly. So week one is still discovery and analysis, just condensed. You'll do maybe three to five focused interviews, 30, 45 minutes each, really digging into pain points. And you'll do that forensic mapping, but maybe just focus on one core process, like their customer acquisition funnel, for instance. Map the data flows, find the system. And deliverables
for week one. By the end of week one, you give them something concrete, an interview summary document, and a detailed process flow diagram for that core process you analyzed. Instant value. They see progress immediately. Okay, then week two. Week two is a solution design and validation. You take those pain points, those bottlenecks you found, and you start brainstorming potential AI or automation solutions. Quick wins, mostly. Then you refine those ideas based on their feedback
leading up to your final presentation. Right. And the week two deliverables are key here. You give them the final AI transformation plan report, smaller scale, obviously. It includes your top three AI opportunities with use cases and ROI, a clear 90 -day implementation roadmap for those quick wins, and maybe a sketch of a six -month strategic roadmap for bigger potential projects down the line. That sounds like a really solid,
manageable starting point. So whether it's the two -week or the four -week version, turning these findings into compelling pitches. What are the crucial strategic tools you need in your toolkit? Yeah, you need a way to prioritize effectively, calculate that all -important ROI, and position yourself not just as a consultant, but as a long -term partner, sponsor. All right, let's talk
about the strategic frameworks. These are the tools that take your analysis from just being a list of interesting ideas to becoming a really compelling business case that executives basically can't ignore. Okay, first up. The impact versus difficulty matrix. Sounds fancy, but it's just a simple two by two grid, right? Super helpful for clarity. In that top left box, high impact, low difficulty. Those are your quick wins. That's your goldmine. Stuff that's fast, relatively
cheap, and shows immediate ROI. Like AI transcription for sales calls, maybe automated email responses, cleaning up CRM data, that kind of thing. Exactly. That stuff forms your 90 -day roadmap. Then you've got the top right box. High impact, high difficulty. These are your big swings. Complex, longer -term projects that can really transform the business. Maybe custom AI agents for customer service, integrating multiple legacy systems, stuff like that. that. That's your six -month, 12 -month
roadmap. You briefly touch on the other two quadrants, low impact, low difficulty, low hanging fruit, and low impact, high difficulty, avoid. But you really focus the client on those top two, quick wins and big swings. Right. Now, the next tool, this sounds like the real game changer, the ROI
calculation. Oh, absolutely. This is what makes your consulting just... irresistible for every major recommendation especially those quick wins you have to build a clear business case often it's time based you figure out okay how many hours per week does a team spend on this manual task right now what's the average hourly cost of those employees multiply that out for the year that's your annual savings potential then you subtract your implementation cost right so
annual savings implementation cost implementation cost 100 gives you your roi percentage let's say an admin spends 10 hours a week on manual data entry Maybe they cost $25 an hour. That's $13 ,000 a year right there in potential savings. If your solution costs $8 ,000 to implement, the first year ROI is 62 .5%. It pays for itself in, what, just over seven months. Whoa. Okay.
Just imagining presenting that, showing a client that kind of concrete value, knowing your work will literally pay for itself in months and then just keep saving them money year after year. That's incredibly powerful. It shifts the whole conversation. It really does. It moves it from being seen as a cost to being seen as a clear investment. Okay. And the third piece of this toolkit, positioning. Yeah. Positioning yourself
as an AI transformation partner. You're not just a vendor selling a one -off service or product. You're a guide. You're taking them on a journey. Think of it in three phases. Discovery, as your audit, your road mapping. Then implementation, where you actually build the systems or help them implement tools. And then partnership, ongoing optimization, training, maybe a monthly retainer for support. That complete end -to -end journey. It offers clients huge peace of mind. They know
you're with them for the long haul. These tools are fantastic for structuring the insights. But they all rely on getting good information in the first place, right? Which brings us back to those stakeholder interviews. How do you master that art? You nailed it. Your success with these audits honestly lives or dies based on the quality of information you gather in those interviews. It is absolutely foundational. So preparation
is everything, I guess. Preparation is key. You got to research the company, understand their industry, know a bit about the person you're talking to, and always, always prepare a structured guide with open -ended questions. Don't just wing it. What are some of those key questions? Things like, can you just walk me through your typical day? Or, what are the two or three most time -consuming, maybe most frustrating tasks you do every week? Also, where do you get stuck?
Like, where do you find yourself waiting for information or approval? And the classic magic wand question. If you could wave a magic wand and fix one frustrating part of your job, what would it be and why? Yeah, and also asking about data. What data do you wish you had access to that would help you do your job better or make better decisions? That often uncovers hidden needs. And best practices during the interview itself. Follow the 80 -20 rule. Listen 80 % of
the time. Talk only 20%. Your job is to listen and absorb. Ask why multiple times. Dig deeper. Don't accept the surface answer. Get to the root cause. And crucially, this is hard sometimes. Do not pitch solutions during the interview. Resist the urge. Your only goal in that moment is gathering information. Analysis comes later. You know, I still wrestle with that sometimes,
making sure I ask enough whys. It's so easy to hear a problem and immediately jump to a solution in your head before you really understand the underlying issue. It takes discipline. It really does. It's a skill you constantly refine. Okay, so we've got the frameworks, understanding the client. Mastering interviews. As someone starts building this consulting practice, what are the common pitfalls they should watch out for? And how do they actually scale this thing? Great
questions. It's definitely helpful to learn from mistakes others have made. Based on what we've seen with agencies doing this, there are a few common traps. Yeah. First pitfall, trying to do everything yourself. AI consulting needs different skills than just pure development, right? You need strong listening, communication, strategic thinking. Maybe you need to hire a partner for some roles. Absolutely. Second, underselling
the value. This is huge. You have to price based on the value you create for the client, not just the hours you put in. Remember that ROI calculation. If your audit finds $100 in savings, charging $20K for it is a bargain for them. Don't undervalue that strategic insight. Third, skipping the deep process mapping. We keep coming back to this, but it's that important. That forensic analysis is your key differentiator. Don't cut corners
there just to save time. So true. And fourth, waiting until the very end, week four, to show your work. Keep the client involved. Validate your findings along the way. Share early drafts. Avoid that big ta -da reveal that might totally miss the mark because you didn't check in. Constant communication is key. Makes sense. And as you start to grow, scaling this. You need a team, presumably. Yeah, eventually you'll likely need
to build a specialized consulting team. Maybe a lead consultant setting strategy, a business analyst doing the deep mapping, a technical analyst checking feasibility, and then implementation specialists for the build phase. It's worth noting, too, consulting is generally more labor -intensive than pure software development, right? It requires more face time, more analysis. Definitely. And the sales process is different, too. You don't lead with, hey, want to buy an AI audit? You
lead with the problem. You sell clarity. You sell navigating the confusion of AI. Use education -based selling. Share case studies, ROI examples, industry insights. Position yourself as the expert guide. And for smaller engagements, maybe that two -week assessment, consider a risk reversal, like a guarantee. Yeah, that can be powerful. We guarantee you will find at least $6 in potential annual savings or you don't pay. It reduces friction
for that first engagement. And always, always have a clear next step to find after any sales conversation. Okay, and then long -term scaling. Once you've got the process down, you can scale by productizing it, creating standard templates, reusable frameworks, checklists, makes you more efficient. You can also specialize by industry, become the go -to AI strategy expert for, say, healthcare or manufacturing. That builds reputation quickly. And finally, create different service
tiers. Offer a range from that initial $5K assessment all the way up to a $100K plus comprehensive transformation program. Meet clients where they are. So the path is definitely there from starting small to building something really significant. With all these insights, what's the big takeaway for our listener to really mull over? I think it comes down to a choice, really. Adapt now or risk getting left behind by this shift. OK, let's try and wrap this up. The core message
from this deep dive today. The AI landscape is shifting fast. pure ai development work it's becoming a commodity right but and this is the big but this huge opportunity has opened up for strategic ai consulting businesses are crying out for guidance not just builders and it's a massive market 50 billion dollars now heading towards 73 billion dollars it's real And the key to tapping into that, it's having a structured,
value -driven approach. That means that deep process mapping we talked about, calculating clear, undeniable ROI, and positioning yourself as more than just a consultant as a long -term AI transformation partner. And don't forget those two customer types, the small smalls needing quick wins and the big smalls needing strategy and education. Know who you're talking to. And remember, there are different ways in that two -week assessment is a great starting point. leading
up to the full audit. Yeah, the window for this AI consulting opportunity, it feels wide open right now, but it probably won't stay that way forever. Now is definitely the time to be thinking about this, to adapt. It really boils down to a choice for anyone in this space. You can keep fighting for those development scraps in a market that's getting tougher and tougher on price. Or you pivot. You become that trusted advisor, the strategic guide that companies are genuinely,
desperately searching for right now. So the only question left for you, the listener, is are you ready to claim your piece of it? Maybe take a moment after this to reflect on your own business, your own services. Could making a strategic pivot like this transform your future? Thank you so much for joining us on this deep dive into the evolving world of AI consulting. Yeah, and if you found this valuable, please share it with anyone else you know who's trying to navigate
this crazy changing world of AI. Out to your own music.