Key Tips for Success in B2B


The Gist

  • AI strategy. Evaluate AI solutions for real problem-solving, not just buzz, in your AI strategy.
  • AI strategy framework. Collaborative synergy and accessibility enhance AI’s role in your strategy framework.
  • Machine learning strategies. Trust in AI requires quality data, transparency, and adaptability in machine learning strategies.

Recent research shows that 79% of B2B companies anticipate incorporating more AI strategy this year — and that’s a conservative estimate. While most organizations see the possibilities with AI and want to make the most of it, many don’t know where to start. And, an even bigger question: Can we trust it?

To navigate the complex landscape of AI, you need a robust AI strategy framework to evaluate its usefulness. Here’s what to look for when trying to figure out if there’s a place for AI in your go-to-market (GTM) tech stack.

Let’s take a look at AI strategy

Black game pieces ame pieces set on a black board with a gold line illustrating the shortest rout from point A to point B, illustrating the importance of AI strategy in business.
AI strategy needs to solve a real problem and be aligned with the business’s goals.Olivier Le Moal on Adobe Stock Photos

AI Strategy: Are the AI Solutions Real?

Any time there’s tech as buzzy as AI, vendors everywhere start boasting about their solutions that provide it. But, as with all technology, not everything is equal. Just because a company says its software uses AI doesn’t mean that it does or that it’s more of a light layer on top of a non-AI stack. And even if a vendor is truly using AI, there’s also the issue of innovation versus imitation.

For example, consider the sales space right now. Pretty much every sales engagement vendor you can think of is touting the fact that AI can write emails for users now. Well, OK. Technically that might be true. But does it really matter? Does it truly move the needle for that sales department’s goals or the goals of the greater business — especially when each email still needs to be reviewed and edited by a human? Oftentimes, this sort of thing is nothing more than shiny pixie dust. When you choose a solution that claims to use AI, it should be solving a real problem that was formerly manual.

Here’s an example on the B2C side. My kid went to sleepaway camp this summer, and the camp shares photos every evening with the parents. But, there are endless faces in every image and in the past it would take hours to sift through them all to find pictures of your child. This year? The camp’s picture sharing platform was using AI tech (facial recognition), so it only sent the photos with my daughter. This is a great example of using AI strategy in a seamless way to take a previously hard problem and make it a delight. 

This instance might not seem revolutionary, but it did solve a problem. In your business, make sure the AI tech you’re evaluating does the same thing for your team. It needs to solve a real problem and be strategically aligned with your goals and the business’s goals. If you’re unsure about whether it can check these boxes, seek a proof of concept.

Related Article: Generative AI in Marketing and Sales: 8 High-Impact B2B Use Cases

Does AI Empower Humans?

Whenever we talk about AI strategy, we can’t avoid the sticky narrative about its potential to replace humans. Let’s get this out of the way. In my opinion (and that of others), AI in the workplace won’t take your job on its own, but other people who know how to use AI might, if you don’t learn to use it, too. That aside, many leaders believe that AI should be employed to empower humans and make their lives easier and better. (I also think schools should be teaching students to use it responsibly as a tool and not banning it from classrooms.)

As an example, think about using an AI strategy framework to score accounts. This puts the technology to work uncovering the best opportunities, and then enables the human to spend their valuable time on those opportunities that have the most potential. It’s an ideal machine/human collaboration.

As you evaluate AI solutions, look for collaborative synergy. If your marketing team stands to benefit most from a given tool, are sales and customer success also able to tap into some of those benefits? The other side of the collaboration coin is accessibility. Can everyone get access who may need to? How hard is it to use? How difficult is it to incorporate into your strategies and everything you’re doing?



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