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AI doesn't solve anything, but it offers the possibility of solving many things.
As marketing teams across industries experiment with generative AI tools, a strange tension is emerging. What it's all about: Generative AI solves problems you don't know if you even have.
Last week, a CMO at a large tech company told me that he felt completely behind and was struggling to understand where and how to integrate generative AI at the marketing team level. “We just don’t understand,” they said. “Companies are still afraid of losing our secrets to public learning models, but no one wants to invest the effort into building our own models. In the meantime, we're just playing around.”
This pressure to hurry up and wait is widespread. In some cases there is enormous pressure to develop a so-called “AI strategy”. I've seen many leaders in startups, mid-sized companies, and large corporations struggle to explain their plans to their key stakeholders.
A large nonprofit organization set up a customer service chatbot on its website so it could brag to its board about “doing AI” while quietly debating what AI really means for its strategy. Another tech company is looking for a “head of AI” to signal to investors that they are taking integration seriously.
Organizations generally think they should have miraculous new capabilities. The promise (or warning) is that AI will take away jobs, increase creativity, and inspire companies to realize that they don't need these annoying people running around doing things. And so marketing managers hear, “Tell us which of these things it will be.” Quick! Before we get 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 technology. Yes, generative AI helps you express ideas faster and more thoroughly. You can “talk” to documents, automate communication processes, translate, summarize and structure data. In other words, generative AI takes your ideas and expresses them exponentially faster and at scale.
They have all been under increasing pressure to do more over the last decade. Since the first Content Marketing World in 2011, I've heard marketers clamoring for the proverbial “faster” technologies. But you have a new car, and it's a rental car.
Is it any wonder companies aren't sure what to make of this car? Sure, it improves with every driver who takes a turn behind the wheel. But you also have real concerns about the impact of driving this public vehicle. Does sharing your data conflict with legal, regulatory or competition concerns? Additionally, a shared car prevents you from standing out and building trust with your audience.
Okay, then you build your own car. But wait a minute. If (and this is a big problem) you have enough training data to build a custom AI learning model, it can take months and potentially millions of dollars to get it right. And if you only use your “small” data set, the answers won’t be nearly as cool and meaningful as with something like ChatGPT.
All of these considerations lead most companies to simply touch generative AI like a cat poking a ball to see if something interesting comes out the other end.
What should you do?
Innovation vs. invention
While the innovation of generative AI is a breakthrough, the truly functional and valuable AI-powered inventions are still a work in progress.
Generative AI is a real innovation. It improves an existing idea or product and makes it more efficient, effective or accessible. Invention, on the other hand, manifests an idea or goal to create something that never existed.
In the last 25 years of the digital age, inventions arising from original, innovative approaches filled the world. However, many of these inventions had no connection to value.
Motorola's 1998 Iridium phone is a good example. At that time, around 300 million people used cell phones. Motorola launched the first satellite phone that allowed people to make phone calls from anywhere in the world. It worked well as long as you were on a boat or in the middle of the desert. But when you walk into a boardroom in the middle of Manhattan, you're holding a $3,000 brick. Iridium was truly an amazing invention based on great innovation, but there was little understanding of the actual value it could bring.
What does invention vs. innovation have to do with how you arrive at a better plan for generative AI? Well, to apply the innovation of generative AI, you need to fully understand the opportunities – or possibilities – of all the approaches it can innovate.
Therefore, you cannot make generative AI a strategy. Innovation practice is about opportunities and possibilities, not direction. AI is an opportunity in search of a strategy.
What approach should AI innovate?
It doesn't matter if you hire a Chief AI Officer or let individuals play with the possibilities the rest of the year. If you do not apply AI through an innovation perspective, it will be difficult to make decisions about advancing an integrated approach.
I recently heard from a customer who was wondering whether they should rely on Microsoft Copilot's suite-like platform integrated with their team's tools or a more targeted, isolated, best-of-breed solution for brand consistency , translation, content creation, workflow automation, etc.
My answer required two more questions. What process did you want to innovate and improve? More importantly, do they understand the current approach well enough to know where innovation might be valuable?
To the latter question about content creation, channel management, personalization, A/B testing, persona research, or countless other approaches where generative AI could be a game-changer, the answer was (as is often the case): “We don’t know.” “
Generative AI innovation seeks content strategy
As a content and marketing team, you would never think about developing a phone or computer strategy. Think about AI similarly. By understanding and optimizing approaches to content creation, management, and measurement, you can see the opportunities for their innovation. To put it 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 will benefit from using a generative AI tool. You can know what creates the most value for the team, department, region and ultimately the entire company.
Show me a company that understands this and has a shared content strategy, and I'll show you a company that is prepared for or is already enjoying the innovations that generative AI can bring.
It's your story. Say it well.
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Cover image by Joseph Kalinowski/Content Marketing Institute
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