‘Playing Around’ With Generative AI Won’t Lead To Innovation

AI doesn’t solve anything but is an opportunity to solve many things.

A weird tension builds as marketing teams across all manners of business experiment with generative AI tools. It boils down to this: Generative AI solves problems you don’t know if you even have.

Last week, a CMO at a large tech company told me they felt woefully behind and struggled to understand where and how to integrate generative AI at the marketing team level. “We just don’t get it,” they said. “Corporate is still afraid of losing our secrets to the public-learning models, but nobody wants to invest the effort into building our own. So, meanwhile, we’re just playing around.” 

That hurry-up-and-wait pressure is common. In some cases, immense pressure develops to create what might be called an “AI strategy.” I’ve seen many business leaders in startups, mid-sized businesses, and enterprise companies scramble to explain their plans to their major stakeholders.

One large nonprofit threw a customer service chatbot on the website so they could brag to the board that they’re “doing AI” while they quietly debated what AI really means to their strategy. Another technology company seeks a “chief of AI” to signal investors they take integration seriously.

Organizations generally think they should have some miraculous new capability. The promise (or warning as the case may be) is that AI will take jobs, expand creativity, and inspire companies to realize they don’t need those pesky humans running around doing things. And so, marketing leaders hear, “Tell us which one of those things it will be. Quickly! Before we’re left behind.”

Gen AI is the new car you didn’t ask for

Now, it’s not that you can’t do interesting things with the technology. Yes, generative AI helps you express ideas more quickly or thoroughly. You can “talk” to documents, automate communication workflows, translate, summarize, and structure data. In other words, generative AI takes your ideas and expresses them exponentially faster and at scale.

You’ve all been under increasing pressure to do more and more over the last decade. Since the first Content Marketing World in 2011, I’ve heard marketers clamor for the proverbial “faster-horse” technologies. But you got a new car, and it’s a rental.

Is it any wonder businesses aren’t sure how to feel about this car? Sure, it improves with every driver who takes a turn at the wheel. But you also have real concerns about the implications of driving this public vehicle. Does sharing your information run afoul of legal, regulatory, or competitive concerns? Also, a communal car prevents you from differentiating and building trust with your audience.

OK, so you’ll build your own car. But wait a minute. If (and it’s a big if) you have enough training data to build a custom AI learning model, it may take months and possibly millions of dollars to do it right. And if you just use your “small” data set, the answers aren’t nearly as cool and powerful as something like ChatGPT.

All those considerations leave most businesses simply pawing at generative AI like a cat poking a ball to see if anything interesting comes out the other end.

What should you do?

Innovation vs. invention

While the innovation of generative AI is a breakthrough, the true functional and valuable AI-powered inventions are a work in progress.

Generative AI is a true innovation. It improves an existing idea or product, making it more efficient, effective, or accessible. Invention, on the other hand, manifests an idea or object to create something that has never existed.

In the last 25 years of the digital era, inventions that emerged from original, innovative approaches filled the world. However, many of these inventions had no link to value.

Motorola’s Iridium phone from 1998 is a great example. At that time, around 300 million people used cell phones. Motorola launched the first satellite phone to let people call from any global location. It worked fine as long as you were on a boat or in the middle of a desert. But step into a boardroom in the middle of Manhattan, and you had a $3,000 brick in your hand. The Iridium was truly an amazing invention based on an awesome innovation, but there was little understanding of the actual value it might bring.

What does invention vs. innovation have to do with how you get to a better plan for generative AI? Well, to apply the innovation of generative AI, you must fully understand the opportunities — or possibilities — of all the approaches it can innovate.

Thus, you cannot make generative AI a strategy. The practice of innovation is about opportunity and possibility, not direction. AI is an opportunity looking for a strategy.

Which approach should AI innovate?

It doesn’t matter if you hire a chief AI officer or have individuals play with the opportunities the rest of the year. If you don’t apply AI through an innovation lens, making any decisions about moving forward with an integrated approach will be hard.

I recently heard from a client who wondered if they should rely on Microsoft Copilot’s suite-like platform embedded into their team’s tools or deploy a more purposely siloed best-of-breed solution for brand consistency, translation, content creation, workflow automation, etc.

My answer required two more questions. What process did they want to innovate and make better? And, more importantly, did they understand the current approach well enough to know where innovation might be valuable?

When asking the latter question about content creation, channel management, personalization, A/B testing, persona research, or myriad other approaches where generative AI could be a game changer, the answer was (as it often is) “We don’t know.”

Generative AI innovation seeks content strategy

As a content and marketing team, you would never think about creating a telephone or computing strategy. Look at AI similarly. When you understand and optimize content creation, management, and measurement approaches, you can identify the opportunities to innovate them. Put simply: You don’t need a generative AI strategy. You need a content strategy that may or may not be optimized by generative AI.   

You can then understand the prioritized uses beyond how an individual benefits from using a generative AI tool. You can know what creates the most value for the team, the division, the region, and, ultimately, the entire business.

Show me a business that understands that and has a shared content strategy, and I’ll show you a company primed or already enjoying the innovation that generative AI can bring.

It’s your story. Tell it well.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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