This is the Easiest Way To Use AI As A Consultant

Is AI coming for your consulting gig or is it the sharp new tool that could actually give you an edge? Today, Michael chats with , Head of Growth at Consulting Success, and they get real about all this AI buzz. Michel has seen plenty, working with big-league companies on their tech, seven-, eight-figure outfits. He believes the whole “AI will replace consultants” thing is probably overblown, but – and it’s a big but – consultants just sticking their heads in the sand about AI might be in for a rude awakening sooner than they think.

Michel and Michael really break down this idea. It’s not about AI wiping out consulting altogether, it’s more about AI sidelining the consultants who don’t get with the program. They talk about that human touch – the creative leaps, understanding people’s messy problems. AI isn’t there yet, not even close, but here’s the kicker: thinking AI is just some passing trend is a really bad idea – you could get left in the dust. Michel puts it plainly: “AI will not replace consultants; consultants who know AI will replace consultants.” Simple as that.

In this episode you will learn:

• Why your human smarts and intuition are still gold, and how AI is here to reshape consulting, not scrap it.

• The real pitfall: not AI itself, but consultants sleeping on how quick AI is changing the game.

• Using AI smartly across your business – from finding clients to getting work done.

• The big shift: treating AI like a new team member for faster turnarounds and sharper results.

• Working through AI’s blips and quirks with steady, clear feedback.

• The RACES method for getting AI to give you what you actually want, plus using AI to fine tune your requests.

• Figuring out AI’s ripple effects – for your clients and for your own consulting shop.

• Keeping your practice ahead of the curve with guidance like that offered in Clarity Coaching.

Welcome to the Consulting Success podcast. I’m your host Michael Zipursky, and in this podcast, we’re going to dive deep into the world of elite consultants where you’re going to learn the strategies, tactics and mindset to grow a highly profitable and successful consulting business.

Before we dive into today’s episode. Are you ready to grow and take your consulting business to the next level? Many of the clients that we work with started as podcast listeners just like you, and a consistent theme they have shared with us is that they wished they had reached out sooner about our Clarity Coaching Program rather than waiting for that perfect time. If you’re interested in learning more about how we help consultants just like you, we’re offering a free, no pressure growth session call. On this call, we’re going to dive deep into your goals, challenges and situation and outline a plan that is tailor made just for you. We will also help you identify where you may be making costly and time consuming mistakes to ensure you’re benefiting from the proven methods and strategies to grow your consulting business. 

So don’t wait years to find clarity. If you’re committed and serious about reaching a new level of success in your consulting business, go ahead and schedule your free growth session. Get in touch today. Just visit Consulting Success – Grow to book your free call today.

Michel Fortin, Head of Growth at Consulting Success, is a globally recognized marketing leader with 30+ years of experience who spearheads demand generation, helping businesses achieve transformative success. Fortin has driven organic visibility and boosted revenue across 200+ industries, generating over $1B in career revenue and pioneering record-breaking online campaigns. His expertise lies in SEO, branding, AI, and content strategy. The author of several books and published articles, he excels at unlocking untapped growth and helping clients achieve explosive business growth.

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Hey everyone, welcome back to the Consulting Success podcast, or if you’re checking us out on YouTube or somewhere else, very excited to have you all here today, but especially excited to have Michel join us. Michel is our Head of Growth at Consulting Success. Today, what I thought we would talk about is something that probably none of you have been hearing about or spending any time thinking about at all: the topic of AI. And so yes, that was a joke. You likely have been seeing and hearing people talk a lot about AI.
But I wanted to bring Michel on here today for us to share some ideas with you. This is a topic that we’ve been speaking to clients a lot about recently at Consulting Success, especially inside of our Clarity Coaching program, where Michel has been leading several conversations, discussions, and sharing of best practices. Michel has worked with multiple seven- and eight-figure companies over the years, and he has a very deep and strong understanding of AI. It’s an exciting time; there’s a lot going on, there’s a lot to unpack. So first of all, Michel, welcome.

Thank you, thank you. I appreciate being here.

Yeah, and I appreciate it because we tried to record this a moment ago and I had some technical difficulties, but we’re back. We’re committed to making this work for everybody. So, where I thought we would start off is: if people have been online recently, they’ve almost certainly seen ads or posts where people are saying that AI is going to “eat consulting for lunch,” “consulting is dead,” it’s “not going to exist,” “AI is going to replace everything.” Let’s just start with your take on that whole direction: is AI actually going to take over consulting?

[01:42] – Why Human Expertise Still Beats AI

I think the question that a lot of people need to figure out, first of all, is anytime that we have this pessimistic view about something that’s going to be replacing something, has it actually really replaced it or, when it replaced it, did it open up a whole new can of worms with a whole new industry and a whole new technology or needs anyway from business?

So, I’m reminded a bit of a podcast episode where I remember somebody saying, “I you had a paper to write in university and you had used AI to plagiarize or to write it for you, and the professor didn’t have an AI checker or anything, the professor just simply asked the student, ‘If I quizzed you on topics in your paper for the next thirty minutes, would you be able to sustain a good conversation, answer all those questions?’ And by their answer, he would know if they actually did the research or not using AI.” And that’s my point: consultants have expertise, they have authority, they have experience, they have all the nuances and things that they’ve actually gone through in all of their years as an expert in whatever field they’re consulting on that they bring to the table. There’s creativity; there is the ability to think outside the box.

For example, AI is a learning model. It will learn a lot of data and information based on what you give it. And in fact, you can also give it a vast array of different types of information that it can go into, and it’ll be able to come up – and sometimes what we think creatively (is that the word? Yes, an adjective?) – to come up with some new ideas and some new things that we never thought of. But it still is limited by the data that it’s been trained on, even though we have it come up with new ideas. The expert will understand asking the right kinds of questions, seeing specific situations with their clients and businesses, there’s all the nuance, that messiness that the human condition brings, that a robot will never be able to replace. So yes, AI will replace a lot of the legwork, the heavy lifting, the stuff that we can actually make it do to make our jobs easier, but it’ll never replace actual expertise, actual consulting know-how that we bring as consultants.

[03:47] – The Danger of Ignoring AI’s Rise

And what do you say to the people who have the belief right now that, you know, this is a fad, it’s a trend, everyone’s talking about it, but it’s not necessarily going to last? “If I just kind of keep doing what I’ve always been doing because it’s worked for many years, maybe for even decades, I will be okay.” What’s your warning or your response and feedback to those people?

Well, when the commercial internet began, people said, “I could keep our stores open,” and our retail stores. Obviously they’re still there because there’s a human and social aspect, but a lot of stores had to close down. You know, they didn’t think that the internet would replace a lot of those. But AI is really here to stay. It’s growing so fast. In fact, the competition for it is so fierce that it’s driving up the demand for it to become better and accelerate at an accelerating pace.

And I’m reminded of something, you know, when we talk about pessimism, there was a really interesting talk back in the eighties, I remember, an economist by the name of Paul Zane Pilzer; he said something that caught my attention and it’s very much applicable to this. He said, if you remember back in the seventies, there was this gasoline shortage. We saw, you know, people thought that there was going to be no more gas, and there were lines at the pump, and gas stations were closing down all the time. And then economists back then said, “Oh, based on the current supply and demand, we’re going to run out of gas by the nineties” or whatever the case was at that time. But what they didn’t understand or didn’t predict is something called fuel injection that was invented in the eighties to combat that. And nobody saw that, never predicted that. So it changed the whole idea, and basically, we never really ran out of gasoline. And now, of course, today we’ve got the electric car. But the point being is AI, same idea, is that we’re looking at it as it’s never going to replace or might replace, and there’s a fear and there’s a lot of apprehension around it, but it’s going to open up so much. I think there’s a saying that says, ‘AI will not replace consultants; consultants who know AI will replace consultants,’ and that’s the big difference.

[05:59] – How AI Will Transform, Not Kill, Consulting

And that’s a really important point, right? So what I think we both very much agree on is that AI will not replace consulting, but AI will replace consultants, and the frame or the box of consulting for those that aren’t thinking about how to apply or use AI in their businesses. And to your previous example, about oil or about the internet, I remember back in the day when cell phones first came out as that big block, right? And people looked at it and said, “I would never carry around one of those things.” I mean, first of all, a lot of people couldn’t afford them, but even those that could didn’t necessarily all run out and grab these big—it just seemed so inconvenient. Well, look where we are today, right? We have essentially computers in our pockets. They’re more powerful than anything that people could have imagined back in the day.

We are so early when it comes to artificial intelligence. I think of myself; I always appreciate technology. In some formats, I’m an early adopter. When I first started hearing about AI, go back a year or so ago, when I’d say they started to become a little bit more mainstream, I remember thinking, “Oh, whatever, this is not necessarily…” Like, I didn’t see it right away. I was not a full-on believer of what AI is going to do to the world. But over the last year, my position now is that this is something that every consultant – I don’t care what industry you are in, I don’t care how old you are, I don’t care where in the world you live – I think you have a responsibility to understand and to pay attention to AI in two ways. First, you need to think about how AI impacts your clients and the market that you work in. Second, you need to think about how AI impacts your direct business, competition, and the future. And those that don’t pay attention to both of those, I think, either do a real disservice to the clients that you care about and that you want to add value for, and you also potentially do a real disservice to yourself. And if you have a team, which many people do, then you’re doing a disservice to your team if you’re not paying attention to it. Because you might wake up – you might feel right now you’re okay – but in a few months from now or in a year from now, there’s a very good chance that you’re going to wake up and you will see that the competition has been taking- you know, they’ve been paying attention to what’s going on, and now all of a sudden they’re way ahead of you. They’re putting out things in a way that you can’t because you haven’t been thinking about it.

So what I’d love to kind of get your perspective on, Michel, is what are maybe a few ways that you think AI can be used? What do you think AI might actually replace in the world of consulting and what consultants do? So what are some maybe good examples of what AI can actually replace? How can you actually use AI effectively right now?

[08:43] – 4 Core Business Areas to Automate with AI

Well, I’m going to give you a two-part answer. And the reason is because there are some obvious ways that we can use AI now. In our company, for example, Consulting Success, we have four major pillars in the company: we’ve got sales, we’ve got marketing, we’ve got operations, and we’ve got fulfillment. And we can use AI in any one of those four, or we can find ways to use AI in one of those four, either a) to become more efficient and automate all of the processes, reduce a lot of the time that it takes for a lot of this stuff to be done, because a lot of times we can do research on a topic or we need to do some work on a topic that might be, you know, a couple of weeks; now it can be done in a couple of hours. It’s just that much of a game changer. The number of bodies that we needed in our business, the need for those bodies, has been reduced tremendously. You know, you can have literally an entire company of twenty to one hundred people run by just five people because of AI.

Now, the second part of the question is, AI is growing and is accelerating at such a high speed that it’s impossible to predict the various ways that we can use AI. And one of the best lessons that I have ever learned is AI, you know, it’s kind of what this professor, there’s a YouTube video where he said it best; he says, “A lot of people think that AI is a question-and-answer machine. We ask questions, we do prompts, and it comes out with the answer, comes out whatever output.” And we should not treat it that way. What we should treat it as is a teammate. And the reason is because if you ask AI or a piece of software, any kind of software, and it gives you a response and it’s not really the response you’re looking for, then you’ll have to repeat it or you’re going to go to another piece of software or whatever. If you had a teammate, what do you do? You give it feedback, you give it course correction, you give it some ideas on how you think would be the better response for this or things that you would like it to be better at. And that’s where AI can become a tremendous tool.

And so, you know, we’re talking about AI agent – “agent AI” is the word that is very commonly used – where, you know, you can have AI that can, like, do a summary of a whole bunch of articles for you, create a blog post on LinkedIn, and then you have to go in and edit and check and things, whatever the case is. But also, you could give it feedback. You could come back and then fix the prompt, add more specificity, make the prompt a bit better so that it can come up with a better output. But now we have even another layer of AI that can actually critique itself, come back and fix it, and if it’s not right, come back and fix it. So it’s basically its own little- your teammate, really.

So that’s the answer: sometimes a lot of people say, “Well, how can I use AI?” Use AI to find out how you can use AI. The best prompts I ever saw were like, “You are an AI expert. Please tell me or give me recommendations on how I can best use you in order to do X, Y, and Z,” or “Recommendations on how I can meet these KPIs, these workflows—how can I make these workflows better?” And let AI itself tell you what it could do for you. And it’s really like a tutor and a teammate in one.

[11:55] – Treating AI as a Teammate, Not a Tool

So before you go on, Michel, because I know you have some frameworks that you’ve been sharing with clients in our Clarity Coaching program, and I want to ask you to maybe share at least one of those here today. Just on that topic, because I think consultants, successful consultants, one skill set that they have is they’re very good at asking questions, right? And they know the right questions to ask. And they go beyond the surface level of questions in conversations; they know how to go deep. They know how to have a value conversation with clients throughout different stages of the engagement. That’s where I see one of the advantages that consultants can have when it comes to AI.

I think a lot of people are still using AI, as you mentioned, which is very much like: ask one question, get some feedback. They look at it, or they get an output, they go, “It’s okay,” or “It’s not okay.” But the deeper you go, the more that you ask, the more that you come at it from different perspectives, and you go deeper and you try and refine—like that mindset, that skill set of knowing what to ask and knowing what to look for and bringing in the context and applying that is what, to me, ultimately really will separate those who look at AI and go, “It’s okay, I’m not sure how powerful this will actually be,” from those that- it’s like pouring gasoline on the fire. Like, you can really get something very powerful. I’ve done some stuff with AI and clients look and go, “Like, how did you even do that?” This is the thing that to me is so amazing. It’s like, well, you can do that too. You just need to know and to learn. This is what we’re teaching and trying to show our clients is like, here’s how you can develop a really compelling business case, or here’s how you can develop better messaging, or here’s how you can use this in your marketing. And when you understand and learn these different pieces yourself, right, it becomes really, really powerful for you.

So I don’t know if there’s anything else you want to add to that in terms of any use cases of where you see that AI is replacing things and people should pay attention to that, or how others can use AI maybe more effectively. So I want to ask you that before we go on to maybe talking about a framework or two.

[13:51] – Addressing AI Hallucinations and Inaccuracies

Sure. You know, one of the most common objections that we hear within our own team, for example, and even with clients is that, “Oh, AI hallucinates, sometimes it really gives wrong answers,” whatever the case is. But again, you’re looking at input/output, and that’s it. You’re kind of looking at the output. Well, if it’s not really a good output, you’re thinking that it’s bad, and AI is not that good. But again, you’re not treating it like a teammate, you’re not treating it like a person you can give feedback to.

And so I say this: AI is accelerating to the point right now where it’s hallucinating less and less because AI is getting better at verifying itself, at fact-checking itself, at critiquing itself. And if not, you can use AI to do that for yourself. In fact, I’ve seen a lot of consultants and clients that are using AI to actually go back and – like AI agents – to actually come back and look at a lot of data and the output and correct, whether it’s coding, whether it’s engineering, whether it’s copywriting copy, whatever the case is. So I think what we need to understand is this: the output that AI puts out is no different than if you would hire somebody to write copy for you. What they would expect you to do is come back – it’s a first draft – go back and give it feedback, let it come back with better stuff, fact-check, give you references. “Hey, you’re citing some law cases here.” Let’s say it’s a legal consultant, you’re coming up with some law cases. “I want to make sure these are actual real law cases that are setting precedents. Can you go back and cite those law cases and make sure, and fact-check?” And so it will become better and better that way.

[15:28] – Speeding Up Feedback Loops with AI

That example, or what you bring up right now, I think is so true in my experience and also very important for people to understand because I know, even recently, I was doing some work with AI around forecasting, around business growth and different metrics around leads and conversions and all that, and the output looks really good. But when you start going through, it’s like, “Oh, wait a second, that’s not – that’s not what I- that was not my input,” or something looks off there.

Now, the distinction is that if you were working with just another team member or you had a contractor, you would need to go and communicate back to them, like, “Hey, I’ve received the file that you’ve sent. Here’s my feedback. Something looks off.” Now we have to wait for them to receive it, to go through it, to update it, and to send it back. That all takes time, right? And time is money; it’s resources. The beautiful thing with AI is, in my example, I just went and said, “Hey, can you check this one metric around conversions? Because I didn’t say twenty, I said twenty-five. What is that actually? Can you check that?” And then it comes back and says, “You’re correct. Thanks for pointing that out. I will redo the calculations.” And then, boom! Right? So on the spot, if you know what to pay attention to, if you don’t just accept the first output and instead have the mindset of, “I’m going to always look to improve. I’m going to really think critically at what I get and then give it feedback,” it just gets better and better.

Yeah, exactly. That’s what you have to do. You have to treat it like a teammate, like somebody that you’ve actually outsourced a task to that you give feedback to and then get better output from.

[17:01] – Using the RACES Prompt Framework for Better AI Output

All right, so let’s talk- I know you were sharing with clients recently one of the frameworks that you kind of use and look at, which is RACES. Walk us through what the acronym is, what it stands for, and why it’s valuable.

Yeah, well, when I use AI, I’m thinking, “I’m off to the RACES, right?” So it’s really an acronym that kind of helps me, reminds me of the things that I need to make sure that the AI has information on to make it the best output possible. In fact, you know, Tony Robbins himself said that the quality of the answers is wholly dependent on the quality of the questions, right? And AI is no different. The better the question, the better input that you give it, the better the output.

The RACES framework simply means this: it means Role, Actions, Context, Examples, and Specifications. Here’s what it means. Role: when you start with AI, you give it a role. “Act as an expert email copywriter that has worked with consultants in the engineering space,” or whatever. The next one is Actions: tell it what you want it to do. “I want you to write me twenty-five Ads- copy for twenty-five Google Ads. And I want it to have headlines, I want it to have this word count, I want it to target this audience, and I want it to be in a calendar that will be distributed over a period of time,” whatever the specific—

Before you go on, so do you find the more specific you are with this, it’s always better? Okay, so being lazy and just putting in high level, like, “Create an effective Google Ad for me,” that’s a no-no. You want to be specific.

So, here’s coming back to our previous conversation. If you had a teammate: “Hey, create an ad for me.” You know, that’s basically the same idea, right? Well, how many ads? What kind of ads? Who are we targeting? Where’s it going? How much are we spending? All those things. But so, coming back on the RACES is the Actions you give it, is basically telling it what you want as an output.

C means Context: give it context. So, “We are this company, we’ve been in business doing this. These are major products that we’re selling, they’re flagship products, our signature products,” whatever the case is, “our price points, the target market, who we’re actually catering to, who are we trying to attract for our business, what challenges we’re trying to solve.” Give it context so that it understands the background.

Next is Examples. Sometimes when you give it an action and you tell it what you want it to put out, it may be based on sometimes some presumptions that are maybe false or wrong or misleading. So when you give an actual example: “Here are some examples of ads, of Google Ads from one of my competitors or from a similar industry. But these are the types of ads I’d like to write.” And it also gives you kind of the flavor of the ads if you want it to be not as promotional, a bit more compelling, a bit more whatever they are, conversational type of ads or texts. And that’s Examples.

And then finally, Specifications. Always, always, always, always, always ask AI: “Ask me as many questions as you need to make sure that this output is the best output possible.” And it’ll ask you questions. “Great. Here are five questions.” And then you answer it in the same order, you know, and it’ll say, “Did you want me to create a calendar for you?” or “Did you want the ads to be themed around this idea or this particular challenge?” “Did you want your Google Ads to appear in Google Search? Do you want display ads? Do you want pictures with your ads rather than just text?” You know, basically, it’ll ask you a lot of questions. Sometimes some of the questions are even more specific, depending on how complex it is. And then you answer the questions, and then boom, you’ll get your output. And often it’ll get the best output possible.

But I want to take it one step back. RACES are components of a framework that presumes that you know exactly what you want in those things. And oftentimes if you ask, you know, you say, “Hey,” as the last part, Specifications, which is, “Please ask me any questions you want so I can help you and specify my input so that it comes out with the best output possible.” Sometimes you don’t even know what kind of- what would be the best role, the best context, the best examples. So you can actually use AI to define AI’s framework before you actually come up with the actual output. So you say, “Hey, what would be the best role that would do this X, Y, Z thing?” And so you’re using the framework in order to clarify the framework. You’re actually helping it to specify or to come up with the best inputs possible, so once you put it together, you’re coming out with the best output. So basically, it’s kind of like prompt engineering. You’re using AI to help you create the best prompt possible, to teach it on how to come up with the best output.

And then Actions: “What would be the best actions that would create the best response or results?” “What would be the-” Okay, here’s the context, “What other information that you would need from me from this context that I could add to make it better?” And so on and so forth. So always look at the output. Never, you know, take it first. Use AI in order to fact-check, to critique itself, to come back with better output, but also with the input. Ask AI to help you come up with better inputs if you need to. But if you’re pretty good and you have a good understanding of what goes into the framework, use RACES: R-A-C-E-S.

Love it. I think it’s incredibly powerful. I want to encourage everyone to apply that, see what comes from it, and let us know wherever you’re consuming this content right now. You know, go into the comments and share it with us. If you want to learn more, Michel, if they want some additional resources, some help with this, is there anywhere on Consulting Success that we could send them to or any other kind of resource that we can put in front of them?

[22:47] – Leveraging Clarity Coaching to Future-Proof Consultants

Well, if you’re not subscribed to the podcast, you know, that’d be your first indication, right? We do have a blog, and we’re going to be kind of bringing up some new content on our blog that will be very much AI-driven and AI-forward. I obviously encourage people to learn more a bit about what we offer. I mean, Clarity Coaching™ is one of our best programs. It has the ability to not only bring consultants to the next level, whatever level they’re at, but also to apply a lot of this technology, these changes, and these things that are coming around that, you know, it’s nice to have a finger on the pulse of what’s going on. And this is your best bet. You know, Clarity Coaching™ is one product that I often- obviously, because I work at Consulting Success, but it’s also something I’m very, very proud of.

Well, I appreciate you saying that. And really, this is what we’re talking to our clients a lot about these days. And I think if you have your head in the sand, if you’re not paying attention to it, you will be sorry that you didn’t spend more time on it. So we’re definitely going to be spending a lot more time on this topic with clients.

I’d love to hear from all of you if this was interesting, if it was helpful. Would you like Michel and I to do more of these and to talk more about AI and other aspects of building and growing consulting businesses? So, again, whatever platform you’re on, leave us that feedback and get in touch. We always love to hear from you.

Michel, thanks again so much for coming on, and I’m looking forward to doing this again.

My pleasure. Likewise.

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