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.