Why Simple AI Projects Beat Ambitious Ones, with Michael Zipursky

How this transcript was made

Transcribed by machine from the published audio, then corrected by hand. It is not a verbatim record: the changes below were made, and are counted.

This episode

54 speaker turns, 46 changes.

• opening voiceover replaced with the authored script (match 99%) and attributed to Max
• closing CTA identified as CTA 2 - Subscribe (v4) (match 97%), replaced with the authored script and attributed to Max; the 94 words spoken before it stayed with Michael Zipursky rather than being swallowed by the substitution

What was changed in these transcripts, and what was not

Generated: 2026-09-20 from 2026-09-20-named/, itself transcribed from the audio that is live on the feed. Every change below is mechanical and counted. No sentence was reworded, no claim altered, nothing removed for being awkward.

The editorial decision

Owner's choice, 2026-09-20: light clean. "Um", "uh" and stammered word repeats ("and, and") are removed, because nobody intends to say them. "You know", "I mean", "kind of" and "sort of" are KEPT - they run to roughly 2,300 instances across the catalogue and stripping them would make the page read as somebody else.

Counts across the whole set

Change	Count
stammered repeat removed	667
um / uh removed	654
space before punctuation	241
split contraction	132
guest turn named (Joe Casabona)	101
organization -> organisation	71
diarisation fragment returned to the host	62
ai -> AI	57
empty turn dropped (was filler only)	36
synthetic outro restored from script	21
organizations -> organisations	18
hyphen followed by space	14
realize -> realise	14
A.I. -> AI	10
recognized -> recognised	9
gray -> grey	9
summarize -> summarise	9
color -> colour	9
behavior -> behaviour	8
synthetic intro restored from script	8
analyze -> analyse	7
behavioral -> behavioural	7
recognize -> recognise	6
percent -> %	5
personalized -> personalised	5
skeptical -> sceptical	5
analyzing -> analysing	5
center -> centre	5
optimization -> optimisation	4
realized -> realised	4
favorite -> favourite	4
realizing -> realising	4
canceled -> cancelled	4
recognizing -> recognising	4
announcer turn relabelled from Guest	4
summarizing -> summarising	4
labor -> labour	4
behaviors -> behaviours	4
colors -> colours	4
organizational -> organisational	4
customized -> customised	3
analog -> analogue	3
optimize -> optimise	3
honor -> honour	2
optimizing -> optimising	2
summarizes -> summarises	2
personalize -> personalise	1
prioritize -> prioritise	1
prioritized -> prioritised	1
organize -> organise	1
rumor -> rumour	1
organized -> organised	1
capitalize -> capitalise	1
centered -> centred	1
organizes -> organises	1
emphasize -> emphasise	1
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humor -> humour	1
traveling -> travelling	1
defense -> defence	1
maximize -> maximise	1
Organizations -> Organisations	1
apologize -> apologise	1
digitized -> digitised	1
monetize -> monetise	1
analyzed -> analysed	1
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theater -> theatre	1
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aluminum -> aluminium	1
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spoken domain -> humanspark.ai	0

What was deliberately left alone

• "Program". A computer program keeps that spelling in UK English; only a broadcast or a scheme is a "programme", and only a reader can tell which was meant.
• "License" and "practice". Both have a noun/verb spelling split in UK English that a rule cannot decide.
• Capitalised words mid-sentence that would otherwise have been respelled: 4 of them, most often part of a name. Left as spoken.
• Retired show and brand names. Spoken by the host and guests. A transcript that removes what was said is not a transcript.
• "Co-pilot". Sometimes Microsoft's product, sometimes the metaphor. A rule would corrupt the honest ones.

The synthetic segments

The opening voiceover on the archive episodes and the closing call to action are read by Max, the show's AI narrator, from a script written in advance. Transcribing them means guessing at words already on file, and the guesses were wrong in places - one opener came back as "an AI that boned him up" where the script says "phoned him up". Those passages carry the authored text instead, and are attributed to Max rather than to the guest: the diariser groups Max with the non-host speaker, which would otherwise put a real person's name on words they never said.

MaxYou're listening to Something About AI. Michael Zipursky is unusually candid here about mistakes his own firm made, before he had any advice to give about them.

The moment that stays with you is a sales pitch he received from an AI that phoned him up pretending to be a person,

which leads him to a question most buyers skip entirely: is this thing representing your brand the way you would represent it?

From there it goes somewhere stranger, into recruitment, where the machines have started talking to each other. Here's the conversation.

Alastair McDermottMy strategy too complicated. Many businesses are getting AI wrong. They're building complex solutions when simple ones

Michael ZipurskyMight work better.

Alastair McDermottSo today I'm joined by Michael Zipursky, CEO of Consulting Success, and we're going to discuss practical approaches that are actually working in consulting firms today in building simple AI

that works for business. That's coming next. And today my guest is Michael Zipursky. He is the CEO and co-founder of Consulting Success.

He has advised organisations from startups to billion-dollar corporations across 75 and more industries worldwide.

He has been featured in Forbes, Entrepreneur, Financial Times, Fox Business, and he's the author of several best-selling books, including The Elite Consulting Mind and

Michael ZipurskyConsulting Success.

Alastair McDermottMichael, it's so great to speak with you on a podcast again. Thanks for coming on.

Michael ZipurskyThanks for having me, Alastair.

Alastair McDermottSo let's talk about the primary thing that we were discussing, that AI strategy can just be too complicated.

Can you tell me, when you're talking about that, where do you see this happening and why is it happening or what's

Michael ZipurskyHappening? It's happening because people are excited about it, right? This is a big development.

I think anyone that is sticking their head in the sand and hoping that this goes away or that things will return back to the way that they were pre-AI is out of their mind.

And when you have any new technology, people often rush to try and figure it out. There's a lot of hype.

There's a lot of people talking about how this will revolutionize the world and how it creates massive opportunities.

And while I think many aspects of that are true, when people rush to try and adopt any new technology, there's going to be a level of waste,

a level of inefficiency, a level of let's just throw money at the problem or at the opportunity and hope that something good comes of it.

And in many cases, you and I were speaking before, Alastair, and I've experienced this firsthand because we've made some of these mistakes and we've learned from it that oftentimes it's

overcomplicated, right? That people try and bite off more than they should be.

And that leads to making investments that don't always create the outcome that they are ultimately hoping for, or at least initially hoping for. So we can talk through some of that.

Alastair McDermottYeah, I'm interested to talk about some of the specifics just so the listener can get an idea of what you're talking about when you're talking about building out things that are maybe too

complicated or overinvesting. Can you describe some of those things just so we can get an idea of what you're talking about?

Michael ZipurskyYeah, I think what we've seen and I see and hear this from a lot of other consulting firm owners is the idea of trying to create a big solution.

So you look at your business and you think about what can we do to leverage and use AI in a big way inside of the business.

The problem with that is anytime you try and build a bigger solution, there's a lot that can go wrong. And you're just kind of by nature taking on a lot more, right?

Whereas if you get very specific with one use case, as opposed to, hey, we have five different areas of our business or five different,

let's say, components of our methodology or framework, let's try and build out a solution that covers all of that. Right.

There's a lot more time that is required, a lot more resources, money, people's different people and involvement on your team, as an example.

And just all of that means that you're making a much bigger investment. But there's also a lot more that can go wrong.

And especially when you're doing something brand new, you're learning as you go about it. Even the people who are talking about, hey, I can, you know, I'm an AI person.

A lot of people like the tools are still new. So there's no one that's necessarily mastered this. I think there's those that are completely new. There's those that have a lot more knowledge.

I know in your case, Alastair, like this is your domain. You're doing some really great things for your clients in this space.

But there's still new things coming out every day, every week, every month. And so that's the challenge is people are trying to create much bigger solutions.

And unless you're an actual technology company, unless you actually have the skill set, the background to manage the projects, and you really know what you're getting into.

So my suggestion and my observation and belief is that the better practice is to find one small specific use use case to begin, build out, test that, see how it works for you.

And then if you have success, or you learn from that, then you can decide, do you know, add another use case or a couple of use cases or kind of expand from from that point,

but rather than trying to build out something much bigger from the start.

Alastair McDermottYeah, so I guess there's a few different issues there. There's the excitement that you talked about, and this new technology, and it's so powerful in so many different ways.

There is the need for experimentation, because this is this is new, like the way that this works, is something that is

Michael ZipurskyTotally new.

Alastair McDermottAnd it's something that we're not used to where we're not used to using software or what seems like software that can give us plausible but wrong answers.

That's something that like, as humans, we're not used to experiencing that we're used to the computer saying, no, I can't do that. Or yes, here's the correct answer.

Not, you know, here's something that looks correct, but is wrong.

As the unfortunate lawyer in the US who had to generate some fake references to previous trials, you know, he got in a lot of trouble and got fired.

And yeah, that was a, you know, that's, that's the type of thing that can happen that humans aren't used to these systems doing. But there is that need for experimentation and learning.

Michael ZipurskySo that's something I think that is that, like, we

Alastair McDermottNeed to, we need to protect that as well. We need to protect the experimentation and the learning

Michael ZipurskyParts.

Alastair McDermottSo I guess what I'm taking from what you're saying is, do that on a smaller scale, right?

Michael ZipurskyYeah. And I think if we back up for a moment, the way I view this is really in two parts. So you have the AI that you can customise, you can build. Right.

So that's, you have a problem you're trying to solve, right? Something that you're going after.

And that's the actual kind of creation of your own AI or leveraging some technology to build something custom.

And I think that's where you can really get into trouble, if you will, by getting too excited and trying to build something too big right away.

And in that case, my real recommendation is rather than investing, again, unless you're a very well-funded company and you have kind of the skill set and the chops to take on a project like

that, you'll typically be better served by starting small, building for one use case or solving one part of a bigger problem.

And then as your team and everyone kind of gets the skill set developed and things are running fine-tuned, now you can add to that. So that's kind of group one, I would say.

The second group that we haven't really talked about, but I think is also really important as part of this conversation for anyone who's thinking about using AI are the pre existing tools.

So I just saw something yesterday. Actually, it was funny. I got a phone call from a company pitching this new AI service.

And I thought, oh, it's interesting that they're sending me this message because I didn't answer the phone. I just listened to the voicemail.

And I went to their website just to check it out, just out of interest. And it was pretty compelling. It essentially replaces SDRs, so kind of sales development representatives, right?

It helps you to the goal and the problem that it's solving for is helping you to generate more meetings and appointments with ideal clients. All that sounds fantastic.

They even have the ability to make phone calls and to use AI to respond or to interact with your prospect pretending to be a human being. So that's all exciting.

The problem with that is that some people are going to jump right into that because they like to try the latest things,

what's trendy, what's hot, you know, the allure of, oh, this is gonna make my life and business easier and better and help me to grow.

But what I saw when I, when I went through that website and what kind of hit me right away and thinking about all of our clients that we work with and what is the implications for them as

they start also being kind of enticed into using these tools is how does this really, like, what does this really mean for your business and for your brand, right?

If you start using tools like this without a real strategy in place, if you're not thoughtful about how you use them,

you're going to be potentially damaging your brand in a very significant way. You know, is AI representing your brand in the way that you want?

Is it saying the kind of things that you would say? Is it going to come across as very promotional and salesy?

There's all these considerations that I think are very important when we start to introduce AI. And you know, Alastair, because we talked about this before, I'm a big proponent of AI.

I think this is fantastic. If you use it the right way, I think it's only going to get better from here. But as business owners, it's incredibly important to be thoughtful about technology.

And so we do not find ourselves in a place where we're using technology thinking that it's actually helping us to grow our businesses.

But in fact, it's doing damage or we're trying to accelerate something like setting up appointments and doing outreach. So we're getting in front of more people. There's more volume.

But in doing that, the response rate is lower. The effectiveness is lower.

So in fact, even though we're reaching more people, it's going to take us a lot longer to have the outcome that we want,

which might be the meetings or the conversations, because the effectiveness of the outreach has been lost or degraded through a lack of real personalisation and showing that you actually

care and that you've actually done your homework.

So I think these are all things that are playing out right now in the ecosystem, if you will, and those that figure out how to use this the right way will really benefit from it.

Those that are not thoughtful, I think will wake up going, wow, like I just invested a lot of time and a lot of money. And this is actually not helping our business.

Alastair McDermottYeah, there's a few different things to dig into there.

I do know that as somebody who implements AI and builds AI for clients, one of the most disheartening thing is when somebody comes to me and says effectively,

hey, can you use this to help me spam people better?

You know, and whether that's through outreach phone calls or email or whatever, I think that a lot of automated outreach is going to have to go away because people are simply going to be

inundated with it because these systems make it so much easier to create seemingly personalised outreach that that that isn't. And there's no human in the loop there at all.

Michael ZipurskySo yeah, I'm sorry to jump in and interrupt for one moment. I'll just add to what you're saying, because you're making me think of something that I can't help but not share.

And I think that where we're actually going to the future is going to be AI talking to AI.

You know, everyone's going to have AI and you're going to have these almost like virtual, you know, representatives or people. And so what happens then?

What happens when AI is just talking to another AI? What is the result of that? And, you know, to me, that doesn't feel like a world that I really want to live in.

But I may not have a choice. So I'm not sure how how we're going to tackle that.

But I think that is a very likely outcome of this that, you know, someone sending their AI to do a bunch of outreach,

but then the person who's feeling that and responding, it's not the person in their LinkedIn box anymore or answering their emails, AI that's doing all that.

And so, you know, where do we go from from that from that place? And I'm not quite sure yet.

Alastair McDermottYeah, it's interesting. Another example of that is in the world of recruitment, where we have for quite some time, we've had AI processing the vast amount of applications that they get.

But now that the tables have turned a little bit because some folks have made some open source software, which can give it your your CV, your resume.

It goes on LinkedIn, it sends a customised job application to hundreds of jobs, and all of those are personalised and customised.

And so now job job applicants have the same kind of technology on their side. So now it's it's AI talking to AI for for the whole recruitment process, you know, and that sounds very broken.

And again, I don't have the answers to that. But I just think that it's a it's kind of a similar similar kind of scenario.

I also think that one of the things that one of the reasons why I rebranded my business to be totally about AI is because one of the things that I did previously is marketing and websites.

And I think that websites are going to go away or going to change, at least in the way that they work.

And I think that we're going to have where we set these agents and we ask it to go and perform a task, go book us a flight or go buy something where we're going to have a optimised websites

where it's going to be very easy. And maybe even the point of having APIs where these interfaces that AIs can connect directly to, they don't even need to view the website,

they can just say, hey, what can you do and kind of interrogate the API?

And it'll say, hey, I can do this or this or those any of those things that you want to do today, and it'll be able to talk to us.

You know, that's the that's kind of I would say the next development past where we're at right now.

But where we're at right now, we've got systems where, you know, I can install cloud computer use on my desktop here, and it can go and it can do research for me, it can go hire a car.

And it'll do that very slowly with lots of mistakes. And sometimes I need to say, hey, you know, get back on track here because it can't close the cookie pop up, for example.

But it can do those things. And again, it's the worst it's ever going to be today. It's only going to get better from here.

So yeah, I guess, like we're talking about AI talking to AI, right?

Michael ZipurskyYeah, I mean, I think that's so here's my belief. And I've held this belief for many years. And so far, it's played out quite accurately. Although I don't know what will happen beyond.

But here's what it is. Anything that we've seen in the past. Think about, you know, when you were younger, the Jetsons. I don't know if you remember that. The kind of animation cartoon.

Back to the Future. Tron. All these different movies, series. What we see in those that look so futuristic and, like, far -fetched is the future.

And my belief and the reason that I think this happens so consistently is that, as human beings, if we can think of something,

if we can envision it, right, come up with that image and actually visualise, like put it out there for people to see, it means that it's possible.

And it may not be actually possible in the exact moment, but over time, the technology and the developments will allow it to become possible.

And so, you know, whether it's finding that you know, in politics, I remember many years ago, the idea of having a female president or prime minister or,

you know, somebody very high up, it seemed pretty far-fetched. Like, it was not common. Well, it's become a lot more common.

And you started seeing that in some different television series many years ago and now all of a sudden happens more. Or you look at, yeah, you know, the idea of autonomous cars.

Like, you would see that in something like the Jetsons where they have little things that push a button, they'd go off.

Well, now with Tesla, you know, you can hop in your Tesla and you can tell where you want to go and it'll go for you.

Like, these are crazy things that we would have never thought were possible, but today they're real.

So, I think anything that we can imagine will actually come true if there's enough kind of desire and need for it to.

Alastair McDermottYeah, for me, that is the computer in Star Trek that can talk back to the humans.

And at the time, that was so, you know, crazy, the idea of a computer being able to, like, we all do that now with Siri and, you know, Alexa and all that kind of stuff.

But also now with with ChatGPT and voice mode, it can actually have a full blown conversation with you.

And if anybody out there hasn't had a conversation like a full blown conversation with ChatGPT and advanced voice

Michael ZipurskyMode.

Alastair McDermottIt's worth subscribing just to be able to test that and see what it can do, because it'll blow your mind if you just experiment and play around with it a little bit.

And what you can do with it is just the part that I don't understand sometimes is how people are not just kind of mind blown by what this technology can do.

And I understand that when when you get a little bit reductionist about it, you can say that the technology isn

Michael Zipursky't great.

Alastair McDermottIt's it's it. There's a lot that I can't do right now. You can say things like it's just a token predictor. I heard that at the weekend at a conference I was at.

And I think that misses the point, which is that we it's still incredibly useful right now and still incredibly powerful right now.

And it's getting better and better like every day, which is one of the things you refer to earlier. Like it's it's being on the it's like it's like surfing.

It's like you're trying to stay on that wave. It's amazing how fast it's moving.

Michael ZipurskyYeah, it definitely is.

Alastair McDermottOK, so one of the things you said at the start was anybody who's got their head in the sand about AI just is out of

Michael ZipurskyTheir mind.

Alastair McDermottI mean, I agree with you, but is there anything more to say to those people who are kind of a little bit sceptical?

Michael ZipurskyWell, I'm really addressing the the business owners, you know, take my wife. She's she's the last to adopt technology. She's not on social media or social networks. This is not her thing.

She's more old school that way. And I respect that because I think that there's there's a lot of excitement and value in technology.

But there's a lot of things that technology unfortunately has, I believe, has made the world worse.

You know, the days of sitting across the table from a friend or family, you know, having a meal, just just chatting and talking and nobody pulling out their phone like it seems rare these

days. Right. So in that way, I think for the average person, I don't believe they need to necessarily dive deep into AI right now unless they're interested.

But for a business, I think you're out of your mind if you're not exploring and actively thinking about what is the potential impact of of AI.

Now, there may not be a massive impact in your specific role or your specific industry right now, but there's a very high likelihood there will be going forward if there isn't already.

And so if you're not spending time, if you're not talking to your team, if you're not talking to people in the industry,

if you're not just actively thinking about what could go wrong, as well as where are the opportunities for us to leverage and benefit from what exists now or what might exist.

I think you are missing a massive opportunity and potentially putting your business and all of your employees or team, whatever size that may be, in significant danger.

And I would go as far as saying that if you're not spending time thinking about this and exploring, it doesn't mean you have to be doing something right away,

but at least thinking and exploring, I think I would go as far as saying that you're being reckless.

And I believe that if you have a team, like, you know, speaking for myself, if we, if I'm not pushing our team, if our team isn't looking into AI,

if we're not thinking about how to leverage it and use it, I believe that I would be, you know, doing a real disservice to our team.

And I believe I have a responsibility as, you know, in my role to make sure that we're exploring what that looks like,

how can we use it, what do we need to pay attention to, what do we need to potentially look out for?

So that's really the kind of the guidance or suggestions that I'm making to internally to our team, but also to everyone that I'm speaking to about this,

because I think that we're now at a place where you can't ignore what's happening.

Alastair McDermottSo this is something I think that people find hard to deal with, that the pace of change, the new tools that are becoming available,

the fact that there are so many different providers of similar, seemingly similar tools

How do you, how do you know what to experiment with? How do you identify the right tools? How do you know what to implement on? Do you have any suggestions around that?

Michael ZipurskyYeah, I think number one, you know, don't rush this. So you don't want to just be complacent and not do anything.

But I also don't believe that this is like a sprint to the finish line, unless you're in an AI business where, you know,

you need to develop and release new features faster than the competition. I think for the average business owner, you want to, number one, think about the implications.

So does this change our business model? Does this change how we deliver services?

You know, is there some aspect of AI that could wipe out and make something that we're either producing or selling no longer, you know, necessary?

And what would the impact be on our business? So I would be, number one, looking at that. Number two, having the team, all your team members leverage AI. So how, you know, every role.

So if you're, for example, a marketing coordinator, there's going to be certain things that you can do that will make your job better and easier. If you're in research, the same thing.

If you're in operations, same thing.

If you're even in a leadership role, you can, you know, ask questions about how can I deliver or how can I improve the delivery of a message or help me to refine an email that I need to send

to investor relations or, right?

The use cases are unlimited, but you want to arm yourself and encourage your team to start thinking about how they can benefit from the different tools that exist.

And then I think the bigger kind of broader response to your question, Alastair, is I don't think people need to rush to try and master everything that's coming out.

Because the reality is, I don't know anyone that can keep up with the pace of new developments, new tools, you know,

just the amount of new features, the rapid pace of the releases of these softwares are, and new softwares popping up pretty much every single day.

Like, you can't keep up with it unless that's your actual business to keep up with it. And if that's the case, then fine.

But for most people, I think just start dipping your toes in the water, start learning about it, be open-minded, and have a culture of kind of continuous improvement and continuous education

around this so that you're learning on an ongoing basis. If you do that, number one, you'll be ahead of most of your competitors, because most people are not doing that in most industries.

But over time, what you'll find through that, like anything in life and business, is you're going to realise that some tools or some paths are not the right ones,

and others are better for you. You'll go deeper into those, and from there, you'll improve.

Alastair McDermottYeah, that's very well said. I know that one issue that people have difficulty with is sometimes identifying potential use cases, because this is such a new technology.

They know their own business very well, but they don't really know what its capabilities are, where it can help out.

Do you have any suggestions or even examples of people using AI, particularly in knowledge work and consulting, or just suggestions for people in trying to figure out the use

Michael ZipurskyCases? 100%. So the first thing I think everyone can do is use AI to answer that question, right?

So whether you're using ChatGPT, Gemini, Claude, whatever, perplexity, you name it, you can go to these sites, and you can even ask the question and say,

you know, my role is X, the problems that I typically encounter are Y, and how, you know, suggest 10 ways that AI could help me to solve these problems or to do my work.

And you'll get something back from that.

And that, I think, is a big use case for AI, which is the brainstorming component, helping you to come up with new ideas, and then you can go further down that path, right?

So it's like, every time you open up one of these, there's a little rabbit hole, right, that you can go deeper down.

And so if it gives you 10 outputs, 10 different use cases, let's say, you don't need to go with all 10, select one and say, well, tell me more about number three. What does that mean?

What does that look like? What tools might I use? Now you can go and do some research, and maybe that research is in Google, if the AI isn't up to date enough.

But that's how it's just that everybody starts. Beyond that, right, it's really about thinking through, again, what is your role?

And inside of that role, what do you typically spend your time doing? Again, what problems are you solving? Or what are the outcomes that you are in charge? Or what targets do you have?

And if you're inside of an organisation where there's some very clear target set in terms of what you need to accomplish,

you know, in terms of metrics and so forth, again, you can use AI to help with that and say, I'm tasked with achieving this target. This is a metric that I'm judged on. How might I use AI?

What kind of tools or processes or ideas might there be that I could use to reach this target or improve, right, or make, you know, strides towards it?

And you're going to get fantastic output from that. Now, as you mentioned earlier, one of the dangers of AI is that there's a lot of hallucination, right?

There's a lot of information that comes back that if you take it at its word kind of face value, it's likely there's going to be some elements of that that are incorrect or in some cases

completely off the mark. So it's critical that you pay attention to those, that you fact check, that you go deeper, that you know, ask additional questions.

Don't just take it at the first output that you get. And that's why I believe that there's still many roles and, you know, areas of work.

So whether you're in consulting or some other area of professional services or whatever it might be, like AI is not going to necessarily fully replace the expert, right, that you are.

You still have a certain level of judgment, you bring context, you bring situational awareness, you bring hearing directly from the horse's mouth,

you go to an event, you meet three CFOs, they tell you something that like AI can't give you what they just gave you that doesn't have the context, it doesn't have that relevance.

And it's not necessarily as timely as well, at least today. So that's how I would approach it and kind of how we think about it internally right now.

Alastair McDermottYeah, I love that.

Michael ZipurskyThat's great.

Alastair McDermottSo let's, let's say somebody was interested in starting today and they haven't been doing a whole lot. Where would you say, you know, here's where you start?

Michael ZipurskyI mean, you're a better person to ask that question to Al istair, because this is, this is your world. My world is helping consulting business owners to grow their businesses.

And we've helped thousands of people to do that. So if you have a question on that, I can, I can, you know, play the expert there, but certainly not in the AI space where we're learning.

I'll tell you what I typically do. I'm asked, I personally spend most of my time using Claude. That's my kind of my tool of choice. And, but I'm not, I have no affiliation.

I have no reason to say that's better than anything else. Because again, there's so many new tools out there that I'm not even aware of.

So I think, you know, just be open to it, do some research. Again, there's Gemini, there's Perplexity, there is ChatGPT, there's Claude, and again, a whole bunch of others.

Start with any of them and just explore, right? There's no pressure. But I think the, so that's one big opportunity, let's call it, is just starting to use it.

But again, I think that the bigger, or may not say bigger, the other really important action item, kind of takeaway,

hopefully for those joining, if they're not already doing this, is to spend some time actually thinking about, and if you have a team,

talking with your team about what are the potential implications of AI to our business.

Because if you're not thinking about that, you know, you might be the next blockbuster waking up, realising that Netflix has just eaten your lunch. And that's happened, right?

Or Kodak, not getting involved in digital. Like there's so many examples of this in history.

And I think right now, there's a lot of people who are not thinking about that, or considering that enough in their business.

Alastair McDermottYeah, another example is BlackBerry, who had a president-elect walking around, talking about how he was going to miss his BlackBerry. I can't believe how they missed that opportunity.

But yeah, so you mentioned, you know, that I might be a better person to answer that question.

One of the reasons why I do this podcast is because there's a certain level of knowledge that I can pick up from listening to other podcasts,

and talking to my clients, and reading every email about AI developments. But these conversations are a big part of the learning experience for me as well.

And so I really do appreciate you coming on to chat with me

Michael ZipurskyAbout this.

Alastair McDermottBut that's how I learn a lot of the time is how, you know, I find out how other businesses are using this, how they're starting with it, what, you know, different angles they have on it.

Because I think it's really important to, right now, I think that one of the biggest issues, and this is a Donald Rumsfeld quote,

he talks about how there are known unknowns and unknown unknowns. I think that in AI right now, we have a lot of unknown

Michael ZipurskyUnknowns.

Alastair McDermottAnd so that's what I'm trying to do is maybe we won't find all the answers, but we might figure out what all the questions are, or at least some of the questions.

So that's kind of what I'm doing here as well. And that's one of the reasons why I ask all these questions and bring on great guests like you on the show.

So, well, Michael, is there anything else that you want to tell the audience about how to think or how to approach AI?

Michael ZipurskyHave we said it all? Yeah, I mean, I'd only have much more to add right now, other than the two big areas, you know, kind of action items to leave people with.

One is to spend time looking at you and your team, how you can use the current AI tools to make your job, your work, your day to day more efficient and more effective.

And the second is to think about the implications of AI to your business and what that looks like now and also going forward.

Spending time on those two things, I think, are a very wise investment that people can make into their businesses.

Alastair McDermottI love it. One thing I just want to mention briefly is I do have a new book, which is called An Absolute Beginner's Guide to Using AI.

So that might also be a good place for folks to have a look

You can find that linked in the show notes if you go to AI

Michael ZipurskyPower.biz slash guide.

Alastair McDermottAnd that's basically a short book to help you get started. You can read it in about 45 minutes and it might be a good place if you're trying to figure out this stuff.

Michael Zburski, where can people find you if people want to learn more about you and consulting success?

Michael ZipurskyYeah. So home base for everything is consultingsuccess.com. I also host the Consulting Success podcast. So you can find us on Spotify, Apple and all those other places.

We have the YouTube channel where we are publishing videos on a regular basis to help people grow their consulting businesses.

And then, of course, if you want to connect with me personally on LinkedIn is the best place. Drop a little note in.

Let me know that you were listening to this podcast, what you thought of it. And I'd be happy to connect. Awesome.

MaxThanks for listening to Something About AI.

If you are new here, there is a back catalogue worth your time and a lot more on the way, so hit subscribe wherever you are listening and you will not miss it.

And if you want to go deeper, Alastair keeps a growing library of free resources over at humanspark.ai.