Creative People Aren’t Problems to Solve: The Role of AI in Content and Marketing

We’re headed down the wrong road with generative AI.

Over the last few months, I’ve been struck by the messages from major gen AI solution providers. Unfortunately, those messages feed the frenzy for implementing generative AI in creative and marketing operations.

Take, for example, this recent quote from OpenAI CTO Mira Murati in response to a question about AI replacing humans: “Some creative jobs maybe will go away, but maybe they shouldn’t have been there in the first place.”

Really?

But she’s not the only one making statements along these lines. OpenAI CEO Sam Altman has claimed that AI would handle “95% of what marketers use agencies, strategists, and creative professionals for today.”

And, of course, there’s this famous quote from economist Richard Baldwin at the 2023 World Economic Forum Growth Summit: “AI won’t take your job. It’s somebody using AI that will take your job.”

Now, it’s not that these statements are entirely true or false. If you peel any of these statements apart, you’ll hear some people say, “Well, what they meant by that was….”

And that’s the problem. It’s not the accuracy of the statement — it’s the interpretation.

Tech companies make technology the hero of the story. They’re telling people to feel lucky to be worthy of such amazing tools. And they’re frothing up the argument that human creativity is a problem to be solved. 

That’s ironic when you consider how every one of these technologies used the products of human creativity to evolve.  

That way lies sophisticated mediocrity

During this gen AI gold rush, business leaders are rushing to tell investors, analysts, customers, and audiences how many roles they can replace with the technology in the name of efficiency.

But will some early adopters regret these decisions? Two researchers think so. They published an article in Harvard Business Review last year arguing that although the initial numbers might “look good, especially in cutting costs, the company will miss the opportunity for big gains by creating substantial value — or a defensible future niche.”   

I see this happening in some companies that have replaced content creators with generative AI. Yes, they are producing more content than ever — they’ve succeeded in creating efficiency in producing content at scale.

And the content they create? It’s average. It’s neither bad enough nor good enough to be remarkable. It’s just average.

And it’s leading us into an age of sophisticated mediocrity.

Wicked problems in content and marketing

A wicked problem is hard to solve because of “incomplete, contradictory, or changing requirements that can be difficult to recognize.” Information researcher Jeff Conklin described wicked problems as those “not understood until after the formulation of a solution.”

Think of the way you organize your kitchen. It might work well enough for you, so you can’t see how much better it could be until someone suggests changes that make it work much better. Only then do you realize that you did have a problem worth solving. 

Wicked problems are rampant in marketing. Your content or marketing approach might be working OK. You know it isn’t quite humming on all cylinders, but there’s nothing so dysfunctional that fixing it becomes a priority. 

But then you try to fix something minor and realize many other operational areas need improvement, too. Are the problems significant enough to warrant the disruption? Unfortunately, you won’t know until you try.    

Why gen AI isn’t a wicked problem (probably)

Unfortunately, those hyperbolic statements about gen AI replacing people or teams have created what appears to be a wicked problem in creative and marketing.

Business leaders hear about gen AI developments and think, “This is such a cool innovation. We must have a problem it can solve — we just don’t know what it is.” 

Then, because of the hyperbolic promises about gen AI replacing agencies and creatives, the sentiment shifts to, “Some of our creative jobs probably are redundant and outdated. Maybe that’s the problem generative AI can solve for us.”

I’m not saying there aren’t some organizations that employ more people than needed or that could improve efficiency or productivity. And those are wicked problems.

But implementing gen AI as a (theoretically) cost-effective replacement for humans who interact with customers or create content usually isn’t a way to solve a wicked problem.

It’s solutionism.

Resisting the solutionism message

Solutionism, a term popularized by tech critic Evgeny Morozov, describes the belief that every problem can be solved with a technological solution.

And solutionism is at the heart of all these statements made by generative AI solution providers.

When Mira Murati says that some creative roles “shouldn’t have been there in the first place,” she’s feeding into the notion that the need for creative roles is a problem that can be solved with technology. 

When Sam Altman says “95% of what marketers use agencies, strategists, and creative professionals for today” will be handled by AI, he’s suggesting that inefficiency in the art of creative marketing needs to be corrected. 

And the bumper sticker warning “AI won’t take your job, but someone using AI will” suggests that generative AI is the hero we should demonstrate our worthiness to.

Buying into these statements pushes us into the era of sophisticated mediocrity. It means we accept the trade of diversity of human thought for a sophisticated solution to a nonexistent problem.

No CEO wakes up and says, “We have too many people with too many creative ideas. Let’s save some money and get rid of them.” But when CEOs tell their teams to figure out how many (or which) resources they could jettison by implementing gen AI, they’re forcing that calculus.   

There are things we can do to avoid this trap. The biggest is to take one all-important first step: Understand and document the opportunity to which you plan to apply AI. That may sound like a no-brainer, but I see more and more companies fail to do it with generative AI.

Just last week, it was reported that 20,000 energy giant Chevron employees are testing Microsoft’s Copilot, a suite of AI-powered chatbots and other tools in Microsoft’s Office 365 apps that can answer questions and generate email drafts. The problem? According to Bill Braun, the company’s CIO: “We’re a little dissatisfied with our ability to know how [well] it’s working.”

My take is they will continue to be. You can’t give 20,000 people a solution to a problem that doesn’t exist and expect them to report back accurate value.

With any productive rollout of an enterprise-wide innovation, you have to first understand what value you want to assess. And to do that, you must understand the existing process that merits assessment. It will be impossible for Chevron to truly get an overall value until it understands what it’s trying to solve.    

I’m not arguing against using generative AI. I’m warning against using specific arguments to advance the technology. There are plenty of wicked problems to uncover in content and marketing. And many activities we do every day might be improved with technology like generative AI.

The key is understanding the difference between solving a real problem and forcing technology solutions to problems that don’t exist.

And that’s how you avoid sophisticated mediocrity.