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When Will AI Get Good at Marketing? (Thinks Out Loud Episode 446)

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Artificial intelligence is part of marketing today. But, to hear most people tell it, it’s a frustrating part. AI is either the thing that will put all marketers out of work or it’s a useless collection of vaporware, continually overpromising and underdelivering.

While it’s impossible for both of these to be true at the same moment, it’s clear that we’re facing a question: When will AI get good at marketing? When will it live up to the hype — or its potential — and deliver meaningful results for our businesses?

The reason why AI isn’t ready yet probably isn’t what you think it is. So what is? What is preventing AI from producing the results we want to see? And, ultimately, when will AI get good at 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.

When Will AI Get Good at Marketing? (Thinks Out Loud Episode 446) — 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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Transcript: When Will AI Get Good at Marketing

Well, hi everyone. And welcome back to Thinks Out Loud. I had a conversation with some folks over on LinkedIn the other day about whether AI is genuinely useful in marketing at the moment. And the consensus was… not really. Which leads to the question, when will AI get good at marketing? The answer to that, as I see it, is that AI will get good at marketing when we require it to do so.

I mean, if you think about it, the problem isn’t necessarily AI. The problem is, how are we using AI to make marketing meaningful in the lives of our customers? What are we doing to make marketing meaningful in the lives of our customers with or without AI? You could almost ask, when will people get good at marketing? And then it becomes a question of, how do we use AI to improve our marketing?

What’s it going to take to make AI work for our brands and our businesses? So when will AI get good at marketing? This is episode 446 of the Think Out Loud podcast. Let’s dive in and find out.

So what we’re talking about today is when will AI get good at marketing? AI will get good at marketing when we require it to. Part of the reason that AI isn’t good at marketing is because too many folks either reject its output as “not good,” quote unquote, or worse, accept it as it is. They just take the image or the copy or what have you and release that into the wild without exercising any judgment or any sense of value around it.

Both of these approaches are wrong, of course.

Let’s start with those second set of folks. Because a better question to ask is, “when will people get good at marketing?” If you think about it, AI isn’t “good at marketing” or “bad at marketing.” Marketers who use AI &mdash or better yet, misuse AI — are the reason that we see bad AI marketing.

And I think there are a few reasons for this. First, there’s the very real case where marketers are increasingly asked to do more with less. This is hardly a new problem, but I genuinely believe it gets worse every year.

It’s no secret that your company’s C-suite regularly challenges their team — that is you — to be more efficient. They reduce headcount or drag their feet on open roles. They cap budgets, or worse, reduce them for training and tools. And they insist on driving more results despite these other challenges.

I’m actually totally okay with the last of those. We should hold ourselves accountable to produce better results all the time. What’s also true is that it’s usually important to invest in people, training, processes, and tools to help folks deliver those results.

Second, I think we lack for appropriate standards of what “good at marketing” means. Your marketing should be designed to help you deliver against a clear set of objectives. For too many marketers, especially those that are hands on with these kinds of tools, one of those objectives often is “MORE,” right? More content, more awareness, more engagement.

I’m not saying that those items are bad by themselves. I’m saying that they’re not always clearly tied to what your business actually wants, which should be more customers, more profitable revenue. When we think about content, or awareness, or engagement, how is MORE helping us drive more customers and more profitable revenue?

Is MORE what we want, or should it be BETTER? If it’s not clear, I believe BETTER should be the answer. When you’re focused on what BETTER means, you’re then in a, well, better position to assess if AI is helping you get there.

The next reason — and I can’t decide if this is 2B or 3 in my list — but I also think the lack of those appropriate standards are tied to unreasonable expectations. And those expectations can cut in both directions.

On the one hand, we’re starting to hear from folks who say that “AI can’t deliver.” And on the other, we’re hearing from folks who believe “AI will replace all marketers.”

I believe that both of these narratives are false. There are plenty of examples of AI doing all kinds of amazing things outside of marketing. Just last year, researchers were awarded the Nobel Prize in Chemistry for their use of AI to predict how proteins form, and the Nobel Prize in Physics for their development of artificial neural networks. The chemistry one has had a more practical application recently, where one of the researchers used AI to design proteins that block snake venom toxins, which apparently is a really hard thing to do in the wild.

This is from the article:

“The University of Washington’s David Baker, who picked up his Nobel in Stockholm last month, used software tools to design completely new proteins that are able to inhibit some of the toxins in snake venom. While not entirely successful, the work shows how the new software tools can let researchers tackle challenges that would otherwise be difficult or impossible.”

At the risk of sounding naive, you can’t tell me that AI can handle chemistry, and you know, physics, at a Nobel Prize winning level, but not help marketers connect with customers more effectively. That just sounds absurd to me. And that’s especially true when a ChatGPT or Google Gemini subscription is in the tens of dollars per month per seat. These aren’t expensive tools.

Clearly, science doesn’t rely on immediate economic results, where business definitely does. I suspect the problem is more around what’s economically viable at this immediate moment, coupled with the last big reason, which is…

Reason three or four, depending on how we’re counting these, is that I think too many marketers have dived into AI without learning how to use these tools well.

Part of this absolutely comes back to training and marketers being given the time necessary to learn how to master whatever platform they prefer. There’s also some degree of companies who’ve taken the head in the sand approach and barred their people from using these tools — an approach which, in my experience, pretty much never works.

And, of course, there’s some small number of folks who aren’t putting in the time whether they’re supported by their companies or not. I’ll come back to that in just a moment.

Now, for the final reason, and for reasons that will soon be obvious, one that I’m not going to spend too much time on, too many vendors have over promised and under delivered on what their AI can do to make you more efficient, more effective, or both.

Why won’t I spend too much time on this one? Well, since I’m talking to an audience of marketers, I mean, are we surprised that A.) marketers are selling the idea of ”faster, better, prettier”, and B.) that vendors maybe got a little ahead of themselves? Yeah, me neither. So let’s move on.

What’s funny about this to me is that there’s an entirely separate set of people still arguing that marketing is doomed and AI will put all marketers out of work. Clearly, the “AI sucks at marketing” and “AI will put every marketer out of work” arguments can’t both be right at the moment. You know, in theory, the “AI will put every marketer out of work “argument could be right in the long term.

I doubt it though, and the reason is — for those who aren’t aware — I started my career in the music industry. I was an amateur musician beginning more or less when I was 15 or so in the 1980s, and started working in the industry while I was still in college later in the ‘80s. The burning argument of the day was whether synthesizers and computers were going to replace quote-unquote “real musicians.”

This debate was endless. Many musicians hated synths and hated computers. I remember one of my professors coming into our college’s brand new computer music lab where I was working part time, ostensibly so he could learn about these new tools. And in one of the most childish displays I’d ever seen from an adult, randomly slammed his hands around on a MIDI keyboard, making a total garbage collection of sounds, and then said, “That’s all I need to hear.” When we asked him whether he wouldn’t rather try and play something more artistic, he replied, haughtily, “Why would I bother? I’m not going to sit here and pretend these toys will ever produce art.” Mind you, Wendy Carlos’s legendary Switched on Bach album was already 20 years old at the time.

The professor was old though, right? I mean, you’d expect that older folks would hate something new that challenges the way they see the world. (Ironically, by the way, he was roughly the same age then that I am today.) What might surprise you is that his reaction to those tools was far from uncommon even among my college classmates, folks aged 18 to 23 or so who also thought synthesizers and computers were sent directly from the devil and would spin on the end of music for all time. Fast forward nearly 35 years and near as I can tell there’s plenty of music being made.

In fact, I’d argue that synthesizers and computers more generally have democratized the creation and distribution of music. Yes, there’s a lot of crap out there. And yes, it’s hard for musicians to make a living making music.

But A.) there’s always been a lot of crap. We just tend to remember the very best stuff and forget all the crap stuff. B.) it’s always been hard for musicians to make a living. Spotify may be today’s example of the music industry taking advantage of artists. If you ask folks who signed a bad record deal 25, 30, or 50 years ago about their experiences, though, and you’ll find that the music industry has always taken advantage of artists.

Dig up a copy of the book Hit Men: Power Brokers and Fast Money Inside the Music Business, published in 1990, and you’ll read stories dating from the publication date back to the 1940s and 1950s of musicians getting screwed by the industry. This falls into the category of, don’t hate the player, hate the game. It has always worked this way. And sure, we can absolutely debate whether it’s possible for musicians to make a living, but it’s also absolutely easier for more musicians to make at least some money making music. Many of my favorite bands these days are independent folks, who would have had a tough time breaking out of a regional following in the past and almost certainly not getting any kind of major label distribution. Today, they can put their music up on Spotify and YouTube and grow a following on social more broadly to promote their performances and at least make a little bit of money. 25 or 30 years ago (or more), if you weren’t on an established label, getting your music on the radio or into television, films, commercials, what have you, the nascent video game industry, was effectively impossible.

The point is that technology hasn’t made musicians or writers or painters go away. Art is still mostly made by humans for humans, using technology or not as it suits them during the creation process, and only requiring technology when it comes to the distribution side of the equation.

As a friend of mine noted recently on LinkedIn:

“I want AI to take care of my dishes and laundry so I can create art and music. I don’t want AI to take care of art and music so I can take care of my dishes and laundry.”

To bring this back to marketing, that’s a good rule of thumb to keep in mind overall. We want to automate the boring stuff. We want to automate the simple stuff, the stuff that gets in the way and free up our time to create, to think, to think big.

Obviously, AI is already changing how marketers work. Otherwise, we wouldn’t be having this discussion, would we? It’s those changes that I want you to think about.

And what that means for marketing and practice, again, goes back to standards. AI will get good at marketing when we require it to get good at marketing. AI will get good at marketing when we exercise our creativity, and our knowledge, and our judgment to make it good. If we’re okay with crappy text and images and video, AI’s contribution to our marketing will be, well, crappy text and images and video.

We need to focus on AI making our marketing truly better. And better in the sense means creating more customers, not just creating more content. We need to use AI to help us put together more effective plans. And then we need to exercise judgment about whether those plans will help us reach our goals.

Yes, we will undoubtedly use AI to help us automate actions that can and should be automated. We will absolutely use AI to help us analyze the performance of how our marketing works.

We need to focus, though, on learning how to use these tools to improve our skills and our judgment. For me, it’s not a question of when will AI get good at marketing. It’s when will we require AI to get good at marketing?

And I think the answer to that should be today.

Show Wrap-Up and Credits

Now, looking at the clock on the wall, we are out of time for this week.

And I want to remind you again that you can find the show notes for this episode, as well as an archive of all past episodes, by going to timpeter.com/podcast. Again, that’s timpeter.com/podcast. Just look for episode 446.

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Show Outro

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

So please, keep your messages coming on LinkedIn. Keep sending me things via email. I love getting a chance to talk with you, to hear what’s going on in your world, and to learn how we can do a better job building on the types of information and insights and content and community that work for you and work for your business.

So with all that said, I hope you have a fantastic rest of your day. I hope you have a wonderful week ahead. 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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