Adjusting your mindset to get the most out of AI

As I talk to marketers, I find that many are unsure about how to go about getting the most out of the rapidly evolving AI world.

I don’t blame them. With things moving so quickly, it’s not easy to know where to focus your efforts. The last thing anybody wants is to invest in something that leads to a dead-end (think eight-track cassette players or the BlackBerry) or to buy a promising AI product that (whoops!) does not work well with your existing system.

Here are three things I believe customers and prospects need to know if they are to get the most out of AI.

1. You should adapt AI tools to your specific needs

We have an ongoing dialogue with our customers, and we built KnakAI to respond to what they told us they need.

But every customer is different, with different circumstances and different requirements.

So I encourage everyone using KnakAI (or any other AI product) to get creative and adapt it to their needs.

How do you do that?

There are two ways.

One is by experimentation.

Some of the marketers I meet with are in full on experimentation mode. They’re ready to take new things on and try new stuff to see what it can do for their business. So they’re taking KnakAI and playing with it and figuring out what it can do for them.

Not everyone has the time or the inclination to experiment, so another way to adapt AI to your needs is to learn from what others are doing.

That means asking questions.

I saw a post on LinkedIn recently from someone who was unsure about how to use KnakAI. That person put out a query asking whether anyone had figured out how to integrate it into their workflow.

By sheer coincidence, I had happened to see another post the day before from a Knak customer who was operationalizing KnakAI. It was an amazing piece offering an early take on how KnakAI was performing for that customer and what it was doing for their business.

Naturally, I put the two people into contact with each other so that the person who wanted to know how to integrate KnakAI into their workflow could learn from the person who was already doing it successfully.

It was a perfect example of how one person can learn from another about how to adapt AI tools and platforms to their needs.

The lesson here: You will need to figure out how to make AI work for you. And that might take a bit of work.

The reality is that we can’t tell our customers actually how to use what we create. We built KnakAI based on what our customers were telling us, but once they start using it, they will make it their own and probably start doing things with it that neither we nor they had thought of before.

That’s why the customer voice is important for us. Sometimes what a customer says they want is one thing, and what a customer is able to do in real terms is something totally different. We want to see how people actually use KnakAI in real life, how they adapt it to their needs.

It helps us make it better.

2. Think of AI as driving outcomes, not efficiencies

Knak has always helped marketers create better-performing campaigns, but it was never something we led with when we tried to sell people on Knak.

What always seemed more important – what seemed to resonate more with people – was how much more efficient our customers could be when they used Knak. So we really focused on telling people how much faster campaign creation could be with us.

With KnakAI, we’ve completely flipped our script.

We’re now touting outcomes – better-performing campaigns – instead of efficiencies.

Why?

When you think about it for a minute, it stands to reason that something created using AI is going to be quick. Speed is one of AI’s defining characteristics. With anything AI, efficiencies are inherent.

So it makes sense for anyone looking at AI tools and products to consider outcomes more than efficiencies.

In other words, consider what AI can do for you rather than how fast it can do it.

That Knak customer who had blogged about how to operationalize KnakAI made us realize this.

Her blog told the story of how she decided to see whether KnakAI could help her build better-performing campaigns. She focused on outcomes, not speed. She wanted to know whether KnakAI was going to help her business, and whether it was going to generate more revenue.

Her answer was yes.

Our sales team has taken note.

We used to talk up efficiencies Knak could give, and then point out how customers would get better performance as a by-product.

Now we’re talking up performance, and adding that efficiencies are the by-product.

For us at Knak, that’s pretty empowering. It means we can focus on driving a company’s performance, on boosting its earnings. Which in today’s work world is pretty important.

(For some insight on how to use AI to drive outcomes in marketing campaigns, here’s a link to my chat with Jeff Canada, the B2B Marketing Operations Lead at OpenAI, during the launch of KnakAI.)

3. You don’t have to be technical to embrace AI

A lot of prospects tell me they’re under pressure right now to build AI agents into their workflow.

That makes them feel like they’ve got to become tech wizards, that they’ve got to understand the workings of AI.

That’s simply not true. You need to know how to use AI, not the technical details of how it works!

A couple of years ago I would have pointed out that marketers didn’t have to know how to code to get great results. That’s because Knak offered a no-code solution.

Today, I’m adding that they shouldn’t have to become experts in the technical aspects of AI.

That’s because anyone under pressure to build AI agents into their workflow needs to realize that those agents already exist inside AI products.

KnakAI, for example, has 10 working AI agents. They are purpose-built, and they learn from our hundreds of customers and the hundreds of thousands of email campaigns that they create.

From my perspective, marketers should never be tasked with technical things.That is not why you hire them. Marketers are there to be creative, to do marketing, to drive results.

Instead of telling marketers what to do and how to do it, they should be told what outcomes the leadership team wants.

They will find AI tools – tools that come equipped with built-in AI agents – that will allow them to reach the desired outcomes.

And because of what’s available now, marketers should be reminding their leadership team that they can be driving outcomes instead of building AI agents.

So stop asking marketers to be technical. With AI, they don’t have to be.

A final word…

I’ll be in close contact with our customers in the coming months to see how they are using KnakAI to drive outcomes. And I’ll be posting here about the latest developments, so if you’re looking to learn, stay tuned.

We’re seeing wild adoption of KnakAI right now; there should be plenty to report!