Why Most AI Tech Investments Fail (Private Coaching Session)
As part of the AI Academy for Marketers membership, we offer monthly Ask Me Anything (AMA) coaching sessions with leading industry experts. We chat about everything from technology trends, use cases, lessons learned, to much more.
- The major causes of AI implementation dissatisfaction and failure.
- The need for defined processes and goals prior to AI implementation.
The relationship between technology and humans.
Below is a quick video from our chat, followed by top takeaways from the conversation.
How do you define Rev Ops?
I get scared that sometimes people think they can just rename their sales operations and marketing operations teams, and call it revenue operations, and then they will be aligned. But revenue operations is a structural and systems approach to engineering outcomes.
So if you think about what sales, marketing and customer success teams do by and large, their focus is on doing more, doing better. If you think of the flywheel, it's the increase force side of things.
So I think one delineation is that there's a tactical level of revenue operations, which is important. That's the administrative side of things. That's getting things in order, and making sure things are set up. But then there's the strategic level of revenue operations, which is where the payoff really occurs. And that's really taking that systems approach to look at solving for the whole, rather than solving for the individual parts, and seeing where the constraints and bottlenecks are.
We talk about alignment as the focus. Like people say you need to be aligned, and what I've discovered is alignment is the byproduct. And the byproduct is there when the structure of the organization is is in place.
When we're pulling in the right places, there's clarity, our incentives are set up correctly, our tools and systems are set up to support, and we have continuous improvement. So revenue operations is kind of always working on creating that space that allows for lift.
What are some common reasons that AI tech investments—or really any tech investments—fail?
AI is a subset of technology, and I think that's how you should think about it. It may be a massively interesting application of technology, but what is the prime directive? That is, what is the business process driving the technology? The technology must not be the driver of the business process. If there was no technology, how would it work if it worked the way you want it to work, and that's where we start.
I can say with confidence 90% of the time or more, when someone has been dissatisfied with a technology implementation, the cause has been ambiguity or conflicts in the business process. Not very often is it that they bought a technology they don't need or that the technology didn't do what it was capable of doing. It was the structure that the technology was put into. The lack of a clear business process is often the underlying cause of dissatisfaction, and then the technology magnified that.
In your course, you talk about positive and negative friction. Can you explain that a bit more?
Marketing AI is different than other AI because marketing is different. Sales and marketing are an open-loop system, and just about every other system in business is a closed-loop system. In manufacturing, you are seeking to eliminate variance, and you control the inputs and the outputs. In sales and marketing, you're actually looking to take advantage of variances. That's where the value is created along the way.
That's one of the dangers of friction. If you will eliminate all friction, you also eliminate all value, by definition.
An example of good friction is the treads on our tires on our cars. They're there to create friction. If they weren't there, we wouldn't be able to drive a car. If there was a drop of rain on the road, we'd fly off the road. The biggest thing I can do anything when coaching is to cause you to ask the question that you wouldn't have asked. Well, that's friction. It slows you down.
We're in this obsession with speed — faster, faster, faster. And I'll steal this from Stephen Covey who wrote Seven Habits: If you invented a way to go from Boston to Miami in 30 minutes, it would be an amazing invention, but it wouldn't do a lot of good if your destination was San Francisco. Right?
And we're so obsessed with speed that we forget where we're going. And then when we add in the element of our people, multiple technologies, our processes and a changing market — that's when I see some AI implementations go wrong.
You talk about how companies can go wrong with best practices. If we're all using the same AI to write our email subject lines or our sales emails, aren't we all just going to sound the same? Is that a fundamental risk we take?
I definitely see that happening. I think where we are in sales and marketing with most AI applications is very akin to professional athletics and moneyball. If you're not using advanced analytics, you're not going to be competitive, but if you're only using advanced analytics, then there's definitely a ceiling too. It's about the balance between the two. When you become too reliant on the technology pieces and you're not thinking about all the other things that go into it, that's where danger occurs.
One thing I think is most fascinating is when a tool will give you a blog headline or an outline. As Brene Brown calls it, a "shitty first draft." It gives you a head start, but then you apply YOU to it. You look at it as an inspiration, instead of something that removes the core element of thinking.
I see this with bots right now. We have really powerful bots, and what we're doing is training our team to behave more like bots. And what I'm going to say is: If it can be handled by a bot, then it should be handled by a bot. But if you're to have a salesperson handle it, then don't turn your salespeople into bots. Where's the human element to that? And if we're going to have humans involved, then we need to make sure there's a human element.
We're auto-tuning our businesses and messages. AI helps prevent you from being the worst. It saves us from being really, really bad, but if that's all your doing, then you lose the ability to be special too.
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About Mike Kaput
Mike Kaput is Chief Content Officer at Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.