How to Strategically Integrate and Use Artificial Intelligence in Marketing

Artificial intelligence (AI) is everywhere today.

When you wake up in the morning, you may ask Alexa to give you a run-down of your daily schedule. That’s AI at work.

When you drive to work using Waze, the app uses a machine-learning algorithm to provide the best route for you. Hello, AI, again.

When you watch a movie or a show on Netflix or make a purchase on Amazon, the platforms use AI to make content or product recommendations for you. That’s definitely AI working hard for you.

With the launch of ChatGPT, many enterprises and companies can access large language models (LLM) to leverage AI for various uses.

So, how do you get started with AI marketing?

Quick Step-by-Step Guide to Integrating AI in B2B Marketing

Going all-in with AI in B2B marketing is a complex process. It involves evaluating and changing your established workflows and processes, which may take months and years—especially in an enterprise environment.

Because teams, businesses, and industries are all different, the particulars about how you approach AI will vary from others. That’s okay!

In general, these are the five key steps to integrating AI into your marketing efforts.

Step 1: Go in with the Right Mindset

When approaching AI marketing, you need to have the right mindset, separate from traditional marketing or digital mindsets.

You need to have a solid understanding of what AI can and can’t do, how different AI tools work, the new skills you’ll need to develop to work with AI, how much time and effort you and your team will need to acclimate to AI—the list could go on. Often, we also don’t know what we don’t know.

You need to be nimble and patient when working with AI integration.

Having the right mindset for working with AI will help on your AI journey.

Step 2: See Where AI Can Fit Into Your Processes

Next, you can figure out where AI can fit into your processes and workflows. While AI can do more and more things every day, it still can’t take on everything on its own.

AI also still needs human oversight. Only you know your business, customers, industry, and competitors like you do! You need to determine where to inject human approval steps.

But, you need to clearly define what you want AI to do. The secret is to make your plan as specific as possible with a clear scope. By doing so, it’s easier to scale and establish your processes with AI.

Step 3: Learn How to Use AI

This is where prompt writing comes in. You might have heard about prompting AI from commercials like this one for Gemini. You’ve probably already tried out AI for yourself by now!

The ads make prompting look easy, and it certainly can be easy when asking simple questions or giving simple directions to a gen AI platform. However, prompting AI for marketing is a more involved process.

To make effective use out of most AI tools, you’ll need to perfect the science of prompt engineering. Developing this skill takes time, patience, and a lot of trial and error. Every AI app responds to prompts differently, and you have to provide plenty of information up front in order for the AI to give you more tailored and useful answers.

If you want to learn more about prompt writing, check out my book, The Modern AI Marketer: Guide to Gen AI Prompts, where I break down the essentials of prompt engineering and give you 75+ plug-and–play prompt examples for a wide variety of sales and marketing applications.

Step 4: Understand Your Data

Data is at the center of AI. And as much as marketers don’t always love dealing with data, it’s important to understand your data and how it will affect your AI usage and results.

You need to know where your data is located, how it’s structured, how to access it, whether it is dated or current, what other data sources need to be pulled to enrich it, and more.

Wilson Peng, CTO of Appen, had this to say on the importance of data quality:

“If you train a computer vision system for autonomous vehicles with images of sidewalks mislabeled as streets, the results could be disastrous. In order to develop accurate algorithms or predictions, you will need high-quality training data.”

This perspective applies to using AI in marketing as well. If you train your AI on inaccurate data about your business, customers, or competitors, then you won’t have accurate results to base your sales and marketing decisions on—which could lead to disastrous business outcomes.

But when you have a good enough understanding of your data, then the analysis and results AI provides can help improve things like team productivity, campaign results, and ROI.

Step 5: Scale Up AI

Once you find ways to start implementing AI in one or two places in your marketing, you can then consider scaling up. This process involves:

• Understanding your current marketing channels
• Detailed documentation of all your processes and workflows
• Determining where else AI can easily fit in
• Testing, training, and modifying AI usage
• Comparing AI results to human results
• Remodifying and re-scaling

Using AI as an individual is different from using it across a team or organization; It involves support from management and coordination across many teams.

Only scale up once you’ve got the hang of using AI for smaller tasks first!

AI Marketing Is the Future… Are You Ready?

Actually, it’s more like the present! B2B marketing teams are already starting to add AI into their workflows to great success.

Want to keep up and take your AI marketing to the next level, both as an individual and within your organization? My book The Modern AI Marketer in the GPT Era is perfect for you. I go further in-depth with entire chapters on each of these steps in the book—and so much more.

Interested in learning more about Pam’s AI Training, including her exclusive AI Copilot Training for enterprises? Feel free to schedule a complimentary call.