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What Marketers Really Need to Know About Putting AI to Work (Thinks Out Loud Episode 426)

AI image generated using MidJourney showing group of young marketers working alongside robots to illustrate the idea of putting AI to work in marketing

The AI hype cycle is running its course, with more people starting to ask, “What’s the point of artificial intelligence for our marketing and our business anyway?” That’s good. That’s a super healthy development. Why is that a healthy development? Because it means more people are looking past the hype of AI and instead asking “how can we put this to work?”

The key point to note is that you can put AI to work in marketing for your business. And what’s most important is looking at how you do that most effectively, where you place your focus.

So, what do marketers like you really need to know about putting AI to work for your business? How can you make sure you’re asking the right questions and learning the right lessons about making AI work for your marketing? That’s what this episode of the Thinks Out Loud podcast is all about.

Want to learn more? Here are the show notes for you.

What Marketers Really Need to Know About Putting AI to Work (Thinks Out Loud Episode 426) — Headlines and Show Notes

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You might also enjoy this webinar I recently participated in with Miles Partnership that looked at "The Power of Generative AI and ChatGPT: What It Means for Tourism & Hospitality" here:

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Running time: 21m 54s

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Transcript: What Marketers Really Need to Know About Putting AI to Work

Well hello again everybody and welcome back to Thinks Out Loud. Your source for all the digital expertise your business needs. My name is Tim Peter, this is episode 426 of The Big Show, and thank you so much for tuning in, I very much appreciate it. I think we’ve got a really cool show for you today. I am getting asked more and more these days about Why artificial intelligence is important in marketing, and more specifically, what’s important for marketers to know about artificial intelligence if they want to do a good job, if they want to keep their job, if they want to be able to stay competitive.

And those are really important questions, really big questions. And they’re driven from a number of reasons, a number of places. Obviously, folks are concerned about what do they need to know to stay successful? Now, I have said for some time that I don’t think AI is coming for your job. I’ve modulated that a little bit and I will talk about it A little bit later in the episode, but generally, AI isn’t going to replace you, mostly.

It’s going to replace some tasks. It’s going to change the way you do what you do. But if you think about artificial intelligence the right way, and if you think about its role properly, then you really don’t have a lot to worry about as a marketer, more or less. And I, I fully acknowledge that I’m doing a lot of hand waving on the more or less.

Again, I promise I will explain why that is as we go forward. What I would say is, That people are starting to recognize what AI is good at and what AI is not good at. And if you want to understand how AI might change marketing or how it might matter in your marketing career, then we should really start by talking about what artificial intelligence is and isn’t for a moment.

Then talk about how it’s used in marketing. And then we can get to why it might, or might not, come for your job. When most people talk about artificial intelligence at the moment, They’re often talking about general purpose generative AI applications like ChatGPT or Google Gemini or Anthropic Claude or specific features that tools like Adobe Photoshop have added such as image generated generation, something they call generative expand or generative fill that actually can do exactly what they say, expand an image using generative AI, or fill in an image, put something else in the image using generative AI.

And you’ll see tools like AI social content generators in things like SEMrush or HubSpot or Salesforce. It’s important to note, that’s not the only type of artificial intelligence that exists out there. Generative AI is just one part of it. Other types of artificial intelligence, like machine learning, also exist that help marketers and consumers be more effective and more efficient.

For instance, Google’s Performance Max and Smart Bidding tools, at least in theory, are designed to improve ad performance and make it easier for marketers to get campaigns up and running quickly. Salesforce, HubSpot, and loads of other tools offer predictive analytics to improve campaign performance or improve your ability to do things like lead scoring quickly and easily if you’re on the sales side or sales enablement side of marketing.

One of the reasons I don’t think you hear people talk about those as much is because they’ve sort of vanished under the hood. They’ve sort of just kind of faded into the background. You’ve heard me say many times on this show that technology, over time, becomes invisible. Steven Sinofsky, who used to run the Windows division at Microsoft, recently wrote in his Hardcore Software newsletter about a list of applications that rely on various forms of AI, and he gave things like maps, directions, and routing handwriting recognition, spelling and grammar recognition, image recognition, “matching that happens,” this is his quote, “matching that happens everywhere from Airbnb to Bumble, or even more recent photo enhancements” as AI, as much as just, “new features that work.” Keep “new features that work” in mind. We’re going to come back to that.

But one of the things he said was, quote, “as soon as it works, it is no longer AI.” Period. The magic wears off. It just sort of becomes a feature. It becomes this thing that disappears into the background. And that leads to the first, most important thing you should be thinking about or be aware of when you think about AI’s use in marketing.

And that is, what are the tools that you’re using today to do your job? There are over 14,000 martech tools on the market today, according to Chief Martech, and their outstanding martech map site. As they note, quote, “Generative AI has only accelerated the growth in that landscape.”

When you think about the tools you’re using, your next question should be, How are the vendors that offer those tools thinking about improving your productivity or your results?

And finally, how are they using artificial intelligence to do that? The important part is not that they use artificial intelligence, though. It’s about understanding the bigger picture of how they’re making AI work for you. Why does this matter? Because no matter how you use AI, you have to make sure that you’re looking out for your customers data, your company’s data, And your business results.

Think about it. The fact is that most of you, as marketers, aren’t going to build or deploy your own artificial intelligence. You’re not. I don’t. Most people won’t. We’re consumers of these tools. Most of your companies, for that matter, aren’t going to do that either. Some of you will. I’ve talked to companies who have very good reasons and the resources to apply to go ahead and build some of their own AI models. That’s great. That’s not going to be true for most people though, for most companies though.

Instead, as I mentioned, you’re going to be consumers of a set of tools. Sometimes those tools are going to be obviously AI. They’re going to market and promote their AI bona fides at every opportunity. And I would point to some of the things we see people doing right now, where they’re really highlighting the artificial intelligence, specifically. In most cases, though, those AI tools are going to be under the hood. Again, to use Steven Sinofsky’s words, they’ll just be new features that work. They’ll just sort of exist under the hood.

And frankly, you don’t care. You shouldn’t have to care whether it’s AI or not. You should care that it works, with one big exception. And the big exception is, if it’s artificial intelligence, it opens up one danger. Because if you don’t know what the artificial intelligence or what the product is doing with your company’s data and your customers data, you may be putting your business at some risk.

It doesn’t matter if the tool comes from big players like Google, Microsoft, Adobe, Salesforce, and HubSpot, or if it’s from small players and startups. You need to know what they’re doing under the hood with the data that matters to your customers and to your company.

It also doesn’t mean you shouldn’t necessarily use the tool. It just means you need to know what it’s doing and where you And, or your customers have the ability to opt out when you’re not comfortable with the choices those vendors make.

My good friend Mark Schaefer wrote a great article recently, and I’ll link to it in the show notes, just as I do with the Steven Sinofsky piece and others, where Mark asked whether we’re creating AI, Or if AI is creating us.

Obviously, as we use these tools, they can be doing all kinds of things under the hood that we may choose not to pay attention to. And his point is that we have some control over the process of how we choose to adopt these tools.

I’m going to go a step further. I’m going to say that your career depends on you making good choices about how you use these tools.

You’re the person who’s actually deciding to put your hands on the keyboard if you’re at that stage of your career, or to make a decision about, is this something that we want to use for our customers, if you’re the person who’s making those decisions. You get to contribute to building a better experience for your customers and, I would argue, a better society overall by using these tools wisely.

By thinking through if these tools are creating a better experience for our customers or are creating a worse experience in the long run and a worse environment in which our businesses are going to operate.

You’ve heard me say, I said it at the top of the show, that AI won’t steal your job, but smart people who use AI will. More recently, I’ve questioned whether it’s more likely that dumb people using AI will take your job. Increasingly, though, I’m coming to believe that people who use AI wisely will always be okay, will be okay in the long run for sure, and that people who use AI unwisely are the ones who are going to find themselves in big trouble, not just in terms of losing their job, but in terms of losing trust from their employers and ultimately from their customers.

Those are the folks who have to change, the folks who are going to put themselves in the worst position. And it becomes incumbent on you as a marketer to ask smart questions about how is this tool using data? How is this using our customers’ data? How is this affecting our customers’ lives? That’s really important, and you get to choose, but only if you actively make those choices.

We’ve been working on a framework here at TPA for a little while for making AI functional for our clients, it consists of three pillars built on a governance foundation.

You know, the first pillar is, is it reliable? When we think about reliability, we think about things like validity, accuracy, timeliness, and explainability. Are the answers the tool that we need? Supplies, logical. Do they make sense? Are the answers or its recommendations true? Do we understand how the tool made its recommendations or produced its results? Because if we can’t depend on it being reliable, It’s not a good tool for us.

The second pillar is responsible. That’s things like ethics, legal compliance, security, privacy, accountability. Do we have a way to go back and ensure we’ve done the right thing? With our customers data, with their customers experience, and frankly, with our customers lives, not just from a legal perspective, but from a privacy perspective, from an ethics perspective, from an accountability perspective. Do we feel good that this is something that’s working? For our customers benefit.

The third pillar is relevant. And this, this gets to more of a business results thing. Is it useful? Is it practical? Is it thorough? Is it meaningful? Does it produce results that matter for your business? Does it, is it useful to the customer?

And the foundation of all of this is governance. Do we have the right stakeholder engagement? Now that could be the business owner. If that’s you, have you really thought that through? It could be executive leadership at a larger company. And as part of governance, what is the monitoring, monitoring and evaluation process? What do we learn as we go forward so that we can actually improve over time in terms of reliability, responsibility, and relevance. Because we want to feed that back into the tool appropriately to get it to do a better job for creating great experiences and creating great messages for our customers.

You’ll note in all of this, we’re not talking about the technology. The technology is not the most important part. We’re talking about something we can plant a stake in, that we can feel comfortable about, that is doing the right thing for our customers. We’re talking about something we’ve talked about on this show plenty of times, a core principle of thinking about what won’t change.

You all know the story, I’ve told the story many times about Jeff Bezos being asked, you know, what things will look like five years down the road or 10 years down the road. And he said he prefers to think about what won’t change during that period. What can we rely upon? I believe that some of those are focused on customers and customer experience, understanding customer behaviors. Because those aren’t likely to change. The behaviors might change, but the importance of understanding customer behaviors won’t. Making sure we’re providing great customer experience won’t change.

We want to keep making sure we’re measuring both quantitatively and qualitatively so that we can learn more about what’s working for our customers and not.

And of course, there’s the need to keep learning as a marketer, right? The whole basis for this question, the whole basis for this discussion we’re having today is all about marketing changes, marketing changes all the time.

You need to keep learning. We did an episode a couple of weeks ago about why AI is the bear and how you can learn to be a better marketer in the age of AI. I’ll link to it in the show notes. I’d encourage you to check it out.

I would suggest, though, that what we’re talking about here is way more important than individual tools. When I started working in digital marketing a long, long time ago, we were building websites by hand in text editors. Things like a layer HomeSite and notepad.

Then people started using tools like Macromedia Dreamweaver and Microsoft FrontPage. Those tools are mostly gone. But the deep understanding of how the web works, and more importantly, why it matters to customers that things work a specific way, remain true. We’re still focused on the customer experience. And if you keep focused on that, then the actual tools don’t matter that much.

Think about the core principles of what won’t change. Yeah, learn the tools, learn the tools you need to know to be effective at your job. But, remember that those tools are going to change. That’s, the things that matter don’t change that much.

So, focus on what won’t change. Focus on creating great, rich, personalized experiences for your customers. Use the tools that help you create rich, personalized, great experiences for your customers. But don’t worry about whether those tools use artificial intelligence or not.

Focus on, and I quote, “new features that work,” with particular emphasis on the “that work” point. Keep learning how you can apply those tools to the areas that won’t change, like making your customer’s lives better.

And most importantly, make sure the tools you choose make it clear on how they use your company’s and your customers data, and that they let you opt out when you’re not comfortable with what they’re doing. I know I said this before, you get to choose. But only if you actively do the work to make good choices.

And for me, that’s the most important thing you need to know about how you use artificial intelligence marketing. The rest is just details.

Show Wrap-Up and Credits

Now, looking at the clock on the wall, we are out of time for this week. I want to remind you that you can find the show notes for this episode, as well as an archive of all past episodes, by going to Again, that’s Just look for episode 426.

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Show Outro

Finally, and I know I say this a lot, but I want you to know just how thrilled I am that you keep listening to what we do here. It means so, so very, very much to me. You are the reason we do this show.

You’re the reason that Thinks Out Loud happens every week. You’re the reason we take the time to put this together. So please keep your messages coming on LinkedIn, keep hitting me up on Twitter, sending things via email. I love getting a chance to talk with you, to hear what’s going on in your world, to learn how we can do a better job building the types of information and insights and content and community that work for you and work for your business.

And with all that said, I just want to say that I hope you have a fantastic rest of your day. I hope you have a wonderful week, and I will look forward to speaking with you here on Thinks Out Loud next time. Until then, please be well, be safe, and as always, take care, everybody.

Tim Peter is the founder and president of Tim Peter & Associates. You can learn more about our company's strategy and digital marketing consulting services here or about Tim here.

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