There’s an old joke about two guys walking through the woods. All of a sudden they see a bear, and the bear starts moving towards them. The first guy sits down, pulls a pair of running shoes out of his backpack and slides them on. The second guy says, “What are you doing? You’re not going to outrun that bear.” And the first guy says, “I don’t have to outrun that bear. I just have to outrun you.”
Outrunning your competitors is the real goal. For many people who were dreaming of solving all their business problems with heaps of AI, they feel let down. AI has been entering the “trough of disillusionment” portion of the hype curve lately, as our CEO Steve Zakur discussed recently on the SearchChat podcast. First it was going to solve “all the problems.” But increasingly people greet it with skepticism because they feel like it won’t.
Here’s the thing. AI probably won’t solve all of your problems, but it is a pair of high-quality running shoes. Heck, it might even represent a scooter that gives you an even greater boost of speed. Remember… you’re not trying to outrun the bear.
So, maybe you’re feeling disillusioned because you’ve tried adding AI-based software to your Martech stack but haven’t seen the dramatic improvement you want. I agree; that would suck. After all, a 10x improvement would be amazing! But if your competition is improving by 9% year-on-year and AI helps you drive 11% growth, guess what? You’re gaining market share. You’re doing better. You’re outrunning the other guy.
Don’t worry about 10x. Worry about solving your customer’s problems – and your business problems. Stay grounded while adding AI to your practices. Do you know what business problem you want to solve? Do you know if the tech you’re looking at can address that problem? And, do you have some objective to measure it by? Without these, you’re just throwing AI at problems to see what sticks. Let’s put it more simply. You’re the head of marketing or sales in your company. Do you really care whether people are utilizing AI, or do you care that they’re driving results?
10x improvement would be great. But remember what an extra point or two of growth means to your bottom line. For most of our B2B clients, that’s a lot of money. I’m betting it is for you, too. Look for the tools that help you outrun the competition. And let them worry about the bear.
For AI that proves its value — check out our technology solutions.
Recently on our podcast we talked about a conversation Tim Peter had with a colleague. The discussion revolved around AI. Tim was asked an intriguing question.
“Come on. All this AI stuff, when we talk about marketing and all that, that’s all just hype, right?”
In high stakes competitive chess, there’s a gaming style called “Freestyle” which is just as “ditch-the-rulebook” as it sounds. The best players are called “centaurs” and although these particular centaurs aren’t half-human/half-horse, their makeup runs along the same logic.
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“Come on. All this AI stuff, around marketing and sales, that’s all just hype, right? That’s not a real thing that matters. Maybe it’ll matter someday. But it doesn’t yet matter today.”
That’s a question I got recently, and it got Steve Zakur and I wondering where we are on the hype curve. Is it really just all hype? Maybe not — platform companies are snapping up data scientists the way early internet companies snapped up web developers.
Why is it that with all the marketing technology vendors claiming their products are fortified with AI pixie dust, business results aren’t better? The same goes for internal IT projects. Everyone wants their process to be better–and artificial intelligence, machine learning, and text analytics can provide that something special. And yet, it doesn’t feel like something special is occurring. At least not in the way that lots of consumer products are getting smarter and better.
Many people have only recently become acquainted with the concept of Artificial Intelligence (AI), but the term was first coined 55 years ago this month at the Dartmouth conference. The name AI has never sat well with me, partly because calling computers “artificial” seems strange. (I haven’t heard Google referred to as “artificial search” to contrast it with the good old-fashioned searching that human beings do when poring over books in the library.)
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