So What? Will AI take my job?

Well, hey everyone, happy Thursday. Happy Cinco de Mayo if you celebrate that. Welcome to So What, the Marketing Analytics and Insights live show. I'm joined by Chris and John. On today's show, we are talking about will AI take my job?

Now, this is a topic that gets covered a lot, and we also covered a lot, but there always seems to be some sort of a new spin, especially as we learn more about the capabilities of AI as we're seeing job functions uh adapt to the technology coming. And one of the things that we did last week, um, and you can see that in the newsletter if you want to subscribe to our newsletter, trust insights.ai slash newsletter, is we actually created a two by two matrix that helped explain jobs that were likely or tasks rather that were likely to be taken over by AI and tasks that were likely to stay with humans. And what we want to do on today's episode is really walk through that two by two matrix of is it more AI or is it more human? We want you, we want to help you think about how to unpack your own job role. So how to break down your job function into those individual tasks, and then give you some tips and advice on what you can do to protect your job.

Um, so John's gonna play Vanna today, but before we get into that, Chris, I want to ask you, because this is a this is a question I think you specifically get asked a lot. Um, you know, where do you stand on will AI take my job? Well, as with everything, it depends, right? Uh depends on the level of complexity of your job. And as we pointed out in the in the two by two matrix, the amount of repetition in in a given task determines how easily AI can take that task.

Now, where I think we we don't think enough about this is understanding that AI will not take your job in in total, right? But what it will do, particularly at companies where there's a lot of very similar roles, is that if you can take, say, one task uh away from a per uh a role that maybe takes an hour and you pull that one task out of eight people, essentially you freed up eight hours. Now, at more progressive companies, those companies will say, okay, now we need to help these employees do something more productive, more beneficial with that time. At more, say, you know, cost-focused companies, they'll say, Great, here's eight hours that we don't need. Let's fire one person because those eight hours we're paying for those eight hours and we don't need them, and shrink the number of emplo seats that we have, you know, the uh butts in the seats, because we've taken away that task.

And so will AI take your job as going to be dependent on the tasks that are getting automated away, the extra value that you can find to provide for your company, and your company's perspective on whether it it feels like has a growth focus where you want to take time saved and up-level your people, or cost focused, where you say take time save and reduce head count to cut costs. That's that's gonna be the determinant. Um so, John, you were thinking we were talking about this, and you were thinking about it in terms of applying the will AI take my job matrix to the traction model. So can you walk through a little bit of what traction is? Yeah, sure, sure.

So this is a it's actually now our model. I mean, this is based on the work of Justin Mayors and Gabriel Weinberg. Their book traction was the first iteration of this. But this idea that you can take the majority of marketing functions and break it down into these 21 different categories. And so their big argument is that you know, as a you start your business out, you pick three of these, you test them, and then it's just continue to repeat the cycle.

And the idea is that as an organization grows, ultimately you will be doing all 21, you know, because you'll always want to be testing where to go. But it did seem like a neat idea to take now, let's take everything on this board here and throw it over on the grid so we can get a picture of which are the most likely positions to be eliminated and which ones are considered rock solid. And it's funny, I was even thinking this morning that we can actually change the focus of this too. It doesn't have to be is AI coming to take your job. It can be which job should I be getting better at to AI proof myself?

Because that's the same thing. Here we can give you this list of okay, here's the ones where if you spend on time, you know, time on this, you'll still be doing this two years from now, as opposed to ones that you know, maybe you shouldn't be signing up for that $2,000 course on um, you know, A B copy testing for ads. That might not be the best move you could make right now. Um so yeah, we can run down and start throwing them in. I actually we put together the matrix that we've got, and I've got my big board here of the actual topics, so we can start cherry picking these and throw them in if you want me to pick one off the board.

Yeah. So can you go back to the uh two by two matrix? So I just want to walk through a little bit about where that came about. So when we were talking about it a couple of weeks ago, I was trying to find a different way to visualize will AI take my job. And so what I did in the newsletter was I took a sample of some of the tasks that I personally do and I put them to this matrix.

So a standard two by two matrix just kind of helps you organize things from high to low. And so in this example, we've taken tasks that are not repetitive to highly competitive, and tasks that are not creative to very creative. And so we're gonna map those as will AI take my job. And so tasks that are not repetitive and highly creative are the tasks that AI is gonna struggle to do the most, whereas tasks that are very repetitive and not a lot of creativity goes into it, are the tasks that AI will do the best with. So anything that falls into the top left is where AI is going to step in.

And anything that falls into the bottom right are gonna be the safest tasks. It's and so for example, you know, I had said, you know, uh interviewing people for an account manager position. That's not necessarily something that AI can do because every conversation is going to be different. There are elements of that task that I can that I can use AI for, such as screening and questionnaires and you know, running through resumes with keywords, looking for those kinds of things, but the actual conversations are not something AI will be able to take over. So that's how we were thinking about plotting these tasks to figure out what's safe and what's you know you should be concerned about.

Chris, anything to add to that? Just the caution that again, it's not the job that will go in, but it's the bundles of tasks in them. So as we go through this and we think about uh say search engine optimization, there's you know four or five subcategories of that, like technical SEO, link building, etc. And then there's tasks within each of those disciplines. So just keep in mind that wherever we net out on this chart, it's not an ironclad, this is you know for sure what's going to happen.

This is going to be more there are there's potential for more automation in certain tasks, and these roles have more of those tasks. All right. So, John, where would you like to start? Yeah, well, you know, let's uh uh we can throw SEO up on there. That'd be the first one to jump through.

So grab that. And so uh so as we're talking about SEO, so Chris, you had mentioned that SEO has a lot of different components. Can you talk through the four major pillars of SEO? So the four pillars are technical SEO, which is uh infrastructure level work, for example, making sure that your server is fast, making sure that your network connection is fast, your DNS set up properly. Um all those very, very technical infrastructure level tasks.

Then you have uh on-site uh SEO, which I would group into uh what we're called technical on-site. So use the use of schema, uh, for example, making sure that pages don't 404, uh, that your redirects are functioning uh properly. So that's that's all the optimizations you can do on a website. Your third bucket is content, right? So what content have you written?

You know, your blog posts, your videos, all that stuff that uh is going to try to appeal to an audience and be found by search. Um, and the fourth is off site, where you're looking at things like link building and brand building, which are almost synonymous these days, getting uh placed in publications or featured on someone's YouTube channel. Uh, whatever you can do to get links and reputational activities uh pointed towards your site. So those are the four big buckets, and as you heard, there's a lot of tasks within each one of them. So if we start with technical SEO, for example, so making sure your servers are quick, making sure that your site is optimized and working.

How much of that? I mean, just the word technical by itself to me implies that there is some kind of automation that is probably available, some kind of AI that can be programmed to look for issues and fix them. So, you know, within technical SEO, you know, what is your opinion of repetitive and creative? If you do things right, it should not be very repetitive at all. Should be very it should be hopefully one and done, or you know, once and then an annual checkup to make sure that things have not drifted out of compliance.

For example, your DNS entries, how your CDN works, etc. Um, maybe maybe you go to a quarterly webinar from your CDN to see uh you know the the new features being introduced to Cloudflare or Akamai or whatever. Um and this is where we get into challenges because in some aspects, some parts of uh technical SEO are uh very non-creative. For example, there are um some very specific ways to set up uh your Apache or Nginx web server, right? And there are best practices, and you really shouldn't deviate from those unless you have a really good reason and you know what you're doing.

But then there are other aspects which are highly creative, which is you know the strategic part of making decisions. Where what kind of infrastructure are you going to have, right? Um how are you gonna do your routing? How are you, you know, how are you doing your cache, you know, reverse caching and proxying and stuff. Those are decisions that you can't really automate because they're highly constrained by budget, by your own skills, um, by knowing what's possible and by what vendors and platforms you work with.

So it's not repetitive. I would uh it's not creative per se. Well, the strategy part is creative, but the implementation is not creative, but it's not something that lends itself well to automation at all. So if we start to pull that apart a little bit, so I feel like decision making, you know, strategy setting, planning, all of that is highly creative and probably not repetitive because it's something you might revisit, but as you have more information, the conversation changes. So I would put you know, technical SEO planning and strategy in the bottom right-hand corner of creative and not repetitive.

Then I would put the implementation in not creative and not repetitive, because you already have the decisions, you're already executing it. So I would put that in the bottom left. What I would put in the very repetitive and not creative is the annual check. So, like you already have what the settings should be. So you could theoretically just automate that to say, make sure it's hitting this threshold or make sure that this thing is happening.

And so while it's not repetitive in something that you do every day, it's repetitive in how you audit to look for errors. The one other factor I think is worth considering is that machine learning and AI really focus on large volumes of data. When we're talking about configuration of stuff like that, we're really talking about very basic script-driven automation, right? You don't need to train a machine learning model on you know ideal memory size for an Apache web server. Uh just implement a very you know something very basic scripting.

So in that aspect, um for a technical SEO, there's almost nothing that you would, you know, using machine learning at best would be overkill, and at worst would be a complete waste of your of your time when it should be automated for sure, but it should, but AI is the wrong uh application. It's like um you you need to stir your coffee and you're like, let's use the the biggest power blender we have. Like, no, no, you just get a spoon. Well, and I guess maybe the question is will automation take my tasks, you know, and so we can sort of think about it in that respect. So, John, you know, I feel like we have three distinct buckets of things that we can plot on the matrix.

We have uh technical SEO planning, we have technical SEO implementation, and then we have technical SEO audits. And so the sorry, I'll let Vanna catch up. I'll be it's it's one of those things. If you've never done it, try like you can be a very quick and efficient typist, but when you're trying to do it in a live setting with other people watching you, suddenly all the skills just go out the door. At least that's what happens to me.

Because it's like the pressure is on for people watching you type. What do you think? Is that uh about where we're mapping them? Yeah. Um, can you change the color so it's a little bit easier to see, maybe just make them all uh black?

Oh, I don't know. Next time we do this, we should use the Google whiteboard thing. Mm-hmm. Well, I was trying to create uh so what I learned is that you can make quadrant um charts in Excel. And so I was trying to prepare one for today, but because I'm not the technical person on the team, there was just a step that I couldn't master, so I couldn't make it work.

Okay, so this looks great. So this um right now, if you are someone in your organization who is responsible for technical SEO, then you probably don't need to worry too much about AI, machine learning or automation taking your job away from you because there's not a lot that the machine or the computer would necessarily do better than you can. So if you're part of the technical SEO planning and strategy, perfect, you're totally safe. If you're part of the technical SEO implementation, then you're probably still good there because as Chris mentioned, that's kind of a one and done, and you want to make sure that it's being done to the specifications, and it's probably more efficient to just do it yourself versus programming a machine to do it. And then with the audits, those happen less frequently, but you're also just sort of following what was implemented to make sure if this is changed, do this sort of a thing.

So there's not really a lot of room for any sort of AI or machine learning or automation in that particular role. For a brand, the exception would be if you are a relatively large SEO agency and you have a canned audit process for say, you know, that you want to run out of 200 clients, then there's some automation opportunities there for sure. What do you think, John? Yeah, and it's interesting too to me the idea that you know not only is SEO a black box, but it's also a moving target. You know, you don't nobody knows for certain what the algorithms are, so it's constantly having to be tested and prodded, and then the fact that it does change every time uh you know the search engines can continue to adjust, so that just steals so much of the repetitive nature out of this.

Like Chris said that there's definitely if you're an SEO firm, then you may have some stuff that you can stack up and automate. But for an individual organization, there's just there's just way too much testing and responding to um with anything that you can easily automate or throw to AI. It's just it seems like this is a solid career path. If you're doing something in SEO, you shouldn't be losing too much sleep right now. Um, so let's skip over to uh within SEO.

Chris, you'd mentioned content creation is the third of four pillars. Um I feel like this is a really good role to unpack down to tasks because this is also um a hot topic of conversation because there's a lot of software that will write content for you. And actually, I'll be participating in the freelance chat next Thursday on Twitter talking about you know uh AI and content creation. And it's a question that comes up a lot of should I just let the machines create the content for me? And so obviously it's a complicated answer, but we can at least start to unpack it.

Uh and John, I know that you uh found an article that basically explained Google is gonna reject any content that they think is AI created. So let's sort of get into the steps, the tasks that go into content creation. Well, content creation always comes in uh you know, there's the ideation of it, there is the uh the creation of it, and then there's the refinement, and then eventually publication, and then you have distribution uh and promotion. Where machines are being used today is on the generation portion. So being having machines be able to generate uh with generative adversarial networks things like images uh or music uh or uh with the larger language models, the ability for them to to write words that are coherent.

The challenge with a lot of those approaches is it depends on the qu level of quality that you're after. The machines today can write extremely large volumes of mediocre content, right? So if you uh for example, a press release is very structured language. There's a lot of commonalities in every press release, and machines are really good at generating them, you know, start to finish. Um, you have to have someone edit them to uh to make sure that they didn't make up something like just invent a new executive uh company, but for the most part, um they're really good at that.

Machines can write really, really high volume mediocre blog posts that don't really say anything, but you know, they're coherent, they make sense. They're they they're kind of like repeating just general platitudes in whatever the topic is. Um but if you're if your requirements um are that you you have exceptional content, machines are gonna struggle with that. And so it's an interesting quandary and one I think that not a lot of people are thinking about from an AI perspective. When you train a machine learning model on language, you have to use a lot of language.

Most language is mediocre, right? When you ingest all of Wikipedia, you ingest all of Reddit. You're not ingesting the classics here, right? I mean, they're in there, but they represent such a small portion of the corpus that you're effectively training machines on mediocre, middle of the road, middle-level education language. And that's what's going to generate.

And so here's the scale you have to balance on. If you, if part of your SEO, which is the off-site, is contingent on getting people to link to you, and people link to you naturally if your content is exceptional, but all you have behind the scenes are machines generating mediocre, you have a substantial mismatch in two parts of your SEO strategy. You can either go with a lot of mediocre content and hope that you know you pick up some traffic on the long tail, because you got a hundred million web pages that all say, you know, tripe. Um, or you scale back your automation on the generation side, you make it fully human to create things that have never been done before and that generates the the uniqueness the the pitchworthiness of your content that then the pitching team can go out and get a ton of links for and get get you on good morning america and all that stuff because you've got something so exceptional so those two things are actually at odds and it's I think it's uh kind of an important point for people who are on the generation side to remember is your machines are not going to generate exceptional content and as a result it's gonna be harder to pitch it so it really comes down to your standards and if you just need large volumes of content to sort of get start to get that awareness and to have that presence and then simultaneously creating that really high quality unique content so your stand that that standards or markets is super important Katie is super important because let's say the machines can create this level of mediocrity right if all you've got is Bob the surly intern who's creating content down here right at the I hate my job and I hate you level and I'm you know I'm gonna face roll my keyboard because I come into work every day drunk a machine is the better choice get rid of Bob right let Bob the intern go and go with go and get your you know by going with machines you'll automatically get to mediocre so for organizations we have to generate a lot of content and you have employees who are on say the left hand side of the bell curve uh in writing quality it might make sense to take away all those tasks from all those employees and say okay we're gonna have machines generate the the mediocre stuff to at least get us to mediocre. Now, if you're a company like Trust Insights, hopefully um our standards for a little higher than mediocre.

Yeah, you know what? AI is not the right choice here. Well, you know, and John, I would like your take on this, but I feel like we are sort of in that, you know, uh unique position is probably the wrong way to phrase it. But we're sort of oh, we have the luxury of being picky about our content because the business is really just three of us. We don't work at an enterprise sized company where the volume of content, you know, is directly correlated to other things and goals and KPIs and that kind of thing.

We can take our time a little bit more. Um, so I would say our standards for the content that we push out for ourselves is much higher because we have the luxury of having complete control over all of the different aspects of the content and the business. So, with all of that, John, what are your thoughts on content creation? Where does it fall on the matrix? Yeah, well, I'd say, you know, if content is part of your strategic direction as an organization, then it basically is not something you farm to AI.

But this it's interesting that you know, aligning content creation here with SEO, I could say, yes, that's an SEO function. You know, if you have 1200 McDonald's and you want a web page for each McDonald's, well then yeah, you could automate and have you know 1200 pages spun up automatically, you know, via machine for that, and that'll be fine. But basically, any org where content creation is part of your strategy, yeah, AI generated content is not going to be good enough. You need to be proving your human worth, and that's totally, you know, what you're where you're at. I mean, I would definitely put this over.

Yeah, I mean, there is some repetitive stuff, but it's definitely, you know, high creative uh iterative and generation, you know, it's it takes human touch all the way through to get it before you get it out the door. Well, and I think that that, you know, you know, Chris, as you've sort of been describing and John, you know, to your point about the multiple web pages for different locations. Um, you know, I think that there's we could break it down into those two categories. There's one is volume and one is you know, uniqueness. And so, you know, I can see scenarios where you know, a larger company or just anyone who needs to create large volumes of content, they can turn to AI to create the content, but then the time is then taken to do the editing and massaging and sort of adding your own personal spin on it.

Because I think a lot of what happens, at least this happens to me personally, is you start to get stuck in what you're writing. But if you're reacting to something, it's it can help, you know, move along the process of writing. So I can see a scenario where having AI generated content, at least to start, can be helpful to getting to that higher uh value content. Do you want to grab something else off the bingo list here? Yeah, Chris, what do you I I've picked the last couple?

What do you what do you want to tackle? Does tackle public relations, traditional media? All right. So do you want to start? So I can I can uh take a stab at sort of breaking down.

So I'll be honest, I probably of the three of us know the least about public relations. It's not a discipline that I ever had a lot of uh access or insight into. And so my understanding is that public relations involves um a lot of content generation. I think it can involve a lot of pitching the story, the headline, the brand, the person to different outlets, whether they be online or offline. Um, you know, it's it's basically that brand and public awareness of something.

But I'm I know that I've probably missed a lot of steps in there. So Chris, why don't you fill in the blanks for me? Not really public relations, at least for traditional media and even you know with social and and influencer marketing, is fundamentally a sales job. So your job is to sell your client's story to some form of uh outlet of distribution. And you know, everybody and their cousins pitching those same outlets.

You know, John and I get horrendous pitches to marketing over coffee uh a couple times an hour of uh just you know, check out the uh the you want to interview our person who did this thing that 150 other companies have done better. Um, but we've got a cooler name that has more vowels. Um we we get a lot of that. So it it is that sales job. It is working with your client to some degree to figure out what it is that what idea, uh, whether it's content, whether it's an interview, whether it's uh you know industry news, what idea you want to sell, and then you pick up that phone and you start dialing and it like the boiler room in Wolf of Wall Street, you gotta just hit the phones and and see who's gonna pick up now in that aspect, there is a lot of automation uh in the PR industry already, and it's all uniformly terrible.

Um the automation that is in the field is so bad that you're you're better off not using it. It's it's it's dangerously bad because what happens is you'll go into a media database, you will identify, you know, you choose your list of targets, unless you're like that one idiot we worked at with at the last agency who just emailed the entire database of 55,000 publications. Um I mean, everyone's entitled to a bad day. Yeah, but don't worry, it wasn't me. Um the automation just at best attempts keyword matching, at worst, just you know has you you know spraying and praying.

Um again, one of the things that we know for sure uh is is horrendously done is when we John and I get pitches for coffee. Like that's not what our show is actually about. Our show is about marketing. Um and while they're entertaining, you know, they're it's it's a clear sign that the software, the automation, hosed it. And so in that role of you know, public relations, the automation opportunities, much less the AI opportunities, are sporadic and very ad hoc.

So, for example, one of the things that we used to do a lot when we worked at the agency was use topic modeling to ingest all of the news stories about a specific topic to see what already had been written, right? To try and get a sense of okay, here's everything that's been covered, so that you know, when the PR person goes out to pitch, they know that they've got to find a different angle. If the client is saying we've got this flexible, scalable, integrated, you know, fully integrated turnkeys, uh SaaS solution. Everybody has heard that. That's not news.

So those are sort of the kind of ad hoc opportunities where automation and AI can make a difference, but on the management of relationships and the ideation of you know, is this a news wortworthy story? Uh, and even identifying who to pitch, that's stuff that right now is actually better left to humans. So it sounds like weeding out what's already been done is good for the AI, but the actual going back to that content creation, that still takes a lot of human intervention. And so that part of the role is still protected as long as you have those standards that we don't want to just generate the same turnkey, whatever news story that everybody else uh is generating. To be quite honest, I used to work in academia, and even you know, my products part that were part of clinical trials were not protected from terms like turnkey.

Like it's find a different word, just just find a different one. Open thesaurus.com and find something else. Um the pitching part too is really a part that should not be automated right now. Um crafting the pitch does I mean, even like we just did a round of pitches, uh encouraging people to partner with us on some of our reporting. And the three of us spent a lot of time thinking about how do we want to approach this?

Who do we want to approach? Um, what's the message going to be? It I would not have left any part of that process to a machine. Right. Well, and you know, it's it's funny because when I was thinking about this matrix last week and I was breaking down my like a small sample of my tasks, I had put that sure, I could let AI generate the sales pitch based on some keywords and you know some direction.

But to your point, Chris, like that's not what our standards are. If we were generating 10 sales pitches a day, that might be different. Might be like, okay, let's just get something out the door, see if we can throw a bunch of stuff against the wall and see what sticks, but that's not the kind of standards that we're trying to hold uh for the company. So, John, it looks like you're putting traditional media, PR traditional media in the highly creative, but also very repetitive. Is that your final answer?

Not super repetitive, but some repetitive. No, there's a lot that's repetitive. I mean, the project process is more than not repetitive. But there's a lot of creativity to it. So yes.

There is if you're good at your job. There's the and I think that that's an interesting thing to just sort of note for a second is the process itself might be very repetitive. So think about a writing framework. That's a repetitive process. You can structure your content the same way every time.

What's unique about it, what's creative about it, is actually the point that you're trying to make and your personal point of view into how you're making it. And the same is true of traditional media, the PR, of the process of pitching might be identical every single time. You have the thing, you pitch the thing, you close the thing, like whatever that process is. Clearly, I'm not, again, not a PR expert. But the creativity that goes into getting that pitch scene, getting that content created in such a way that it's unique, is that's where the creative piece falls in.

Exactly. So this gives us an easy hit too. So now we can I can just take uh direct sales, which as we just talked about, traditional media is just a sales job. So that just goes right side by side with that one. Or are you just trying to protect your job, John?

No, no. I I know no machine can deal with the level of insanity I see on a weekly basis. That's just there's nothing repetitive and there's nothing uh that doesn't require creativity to get out of. So I think similar to uh PR, I think there are opportunities for automation indirect sales, such as those initial cold pitches. So getting people to respond to you, to you know, become aware of you.

So you could create a sales campaign in your CRM or your marketing automation system and send that out uh in mass. And so that part you can automate and sort of you can create those nurture campaigns, you know, if they take this action, do this. You can build all of that to automate. But John, to your point, once you have someone who's interested, once they're engaged, you probably want to take the automation and the AI out of it because that's when you need that human intervention. Yeah, it's funny, I as going through this process has made me real realize that uh all of this is dependent on ability to scale.

You know, a small organization is doing a lot of work on the product front and the customers are new. So there's just so many of the things that could be automated are not in the mix yet. And it's when an organization matures and the buying cycle is solid and it's a large enough company, then suddenly more and more opportunities for automation and AI come to life. I think it kind of starts forcing everything on the chart over into the um you know more repetitive quadrant and so then you you have more opportunity to automate. The other aspect that's not on here but is implicit in some ways in which the way people think about it but it should not be is on uh analysis and uh analysis and analytics.

So for example in sales um the process of lead scoring is something that is exceptionally qualified for all for AI because not just automation but true AI because you have a so much data and you can't see the patterns in the data but a machine could say yes we're gonna surface these five leads is the these are the five leads you should call today because they're of all the indicators you know behind the scenes um these are the ones showing the sort of the green light in SEO um taking a series of headlines and you know and and measuring them and and scoring them would be one example. On the other end uh any kind of attribution analysis all that is a hundred percent stuff that AI should be doing because again people are really bad at it so you know is your SEO working uh is your uh your content uh marketing working I'm working on uh something based on last week's show about exploratory data analysis in content marketing that is all AI that that should all be AI because you don't want to try and figure this stuff out by hand it's just not going to go well as someone who had to QA uh logarithms by hand, I can wholeheartedly attest to you should be leaving that to the machines. Yeah, jobs humans don't want to have to do. No. Um and you know, I think that the analysis is true of any of these roles.

I think that that's a really good point, Chris. And I think that that's where we always start to break down what can AI do, what can AI not do? And so AI can do all of the analysis, prepare the data, and hand you the bundle and say, here's what I found. It's then incumbent upon you, the human, to draw those insights to understand context and nuance and timing and the audience and all of those different factors that sure you could spend a lot of time programming that into the AI, but it's forever changing, especially as you know, conversations change and opinions change and people change. All of those factors will change the kinds of insights uh that you're gonna draw from the data that you're looking at, and that is uniquely human.

The thing that we usually tell people to do, particularly when they're just trying to get their their brains around AI is saying substitute the word AI for spreadsheets, right? So uh what what things in this job could use spreadsheets, right? Where could spreadsheets make a difference? How can we uh make you know how can we use spreadsheets to increase our revenue? Uh when you think about that aspect, because that's really what AI all is, it's just math.

It's just a lot of math. Lead scoring on the basics here makes total sense. Yes, that is basically just spreadsheets run by a machine, right? Content creation, not a whole not a lot of that part fits into a spreadsheet. Um, some technical SEO planning does, but if it it's one of the my favorite ways to demystify AI and say just substitute the word spreadsheets, and then suddenly either a question becomes obvious or you sound like an idiot.

Like, how can I uh how can I use spreadsheets to you know re-envision my company? No, don't don't do that. You you have to write a lot of things down in a spreadsheet, and then a spreadsheet is the wrong tool. Exactly. Um, but saying, how can I use spreadsheets to improve my ROI?

Yeah, that's a place where there's a lot of numbers, and an AI will eventually be part of that. Yeah, how can I use spreadsheets to do my lead scoring? Absolutely. Uh, how can I use spreadsheets to do my technical SEO planning? It's a tougher one because that, you know, and I think that that's where, you know, again, that human intervention of sure, you can use the spreadsheet to collect the information, but there's still so much human intervention that goes into actually putting the information into the spreadsheet.

Exactly. And your easiest implementations of machine learning are all with rectangular data, and rectangular data is fancy for spreadsheet. So when you think about is AI going to take my job, look at any individual task and say, how much how many times do I use a spreadsheet in this particular task? You know, or something like that, or there's something that's so repetitive. And if you're just like at our old PR firm, there's this one job at the the bottom of the totem pole.

Um the the account coordinator copying and pasting results from Google into a spreadsheet. Right? That was their job eight hours a day. How they didn't claw their own eyeballs out, I don't know. Um, but that you look at that and go, wow, that is 100% a job.

You don't even need AI to do that. That is just straight write a 10-line program in PHP and then call it a day, because that's that that that's not even a job. Um, and there was a spreadsheet at the heart of that. So that was one where, yeah, machine learning should take that job because that's a miserable job. Well, and you just said something, Chris, that you know, strikes me as the people who can introduce AI and the people who can't introduce AI.

And so if I was the person who was responsible for copying and pasting the numbers into a spreadsheet all day long, and you, you know, came along and seagold and said, just write a 10-line, you know, PHP piece of code, I would look at you like you had six heads and be like, I don't know how to do that. Does anyone here know how to do that? And the answer is probably no. And so the learning curve for being able to write and create and implement AI is still pretty steep. It's not, you know, there's not a lot of great, like, here's the out-of-the-box solution.

We're getting there in terms of the technology, but that's also a factor of do you even have the skill sets to implement, execute, and maintain the AI? So while it may be so lead scoring, for example, while it may be a task that AI should do, it doesn't mean you have the means to do it. We're working on it, but yeah. No, I know, yeah, I mean, that's the thing. I know we're working on it, but like in that example, the solution is to write some PHP.

I don't know how to do that. And so I would be like, uh, I guess I'm gonna keep doing it the same way because I don't know how to implement a different solution. And it's interesting because when you think about the matrix, then, right? The not creative very repetitive tasks are going to be typically tasks lowered down on the org chart where theoretically, you know, reasonably, the creative non-repetitive tasks like strategy and stuff are going to be higher up in the org chart in an organization. So there may be a lot of value and uh that can be unlocked by artificial intelligence and machine learning or even just plain old automation at the lower levels in the organization.

But the stakeholders to your point, the people who have the authority to authorize it may not even understand what's happening in the lower levels of the organization and therefore they don't know that there's massive cost savings to be had or massive productivity gains to be had because they don't they have no visibility into the actual work being done. And as we talked about um in a recent podcast when you have organizational silos that also include very strict hierarchies, the junior person whose job it is to copy paste eight hours a day can't talk to somebody and say hey I think this is a waste of my time. Yeah that's a whole other issue. That's a new show. Yeah that's I you're trying to get me up on that soapbox Chris and I'm just not taking the bait not today.

So well we should probably start wrapping up anyway. Yeah so John is there any other things you want to note before we uh close down the show uh on this particular matrix what are your thoughts the big one that this has opened up for me is that AI is not the boogeyman it's automation is still your problem you know I mean AI is there but it's really you need to be more worried about stuff getting automated out of your job it's AI is um is on the horizon as a very specific application, but don't worry, there's other ways you can lose your uh paycheck. Plenty of other opportunities for that. So on that note. On that note, Chris, any final thoughts?

No, I think John said it all. So we'll see you all next week. Bye, everybody. Thanks for watching today. Be sure to subscribe to our show wherever you're watching it.

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