5 AI Mistakes Marketing Leaders Should Avoid

Every marketing leader we meet has started to use AI tools to enhance productivity. While most are experimenting with using ChatGPT, Claude or similar tools to produce content and graphics, some have gone further and are using AI platforms to develop segmentation strategies, content personalization, and predictive lead scoring.

While AI promises advancements in both marketing strategy and execution, the technology also brings notable risks that marketing leaders should consider.

Below are five common AI mistakes that every marketing executive should avoid to ensure responsible AI adoption.

1. Not setting up a corporate AI account.

The number one mistake that AI experts cite is the failure by organizations to invest in a paid corporate subscription like ChatGPT Enterprise, Claude Enterprise or Grammarly Pro. Employees who are using free AI tools – and they are, even if your organization has officially banned the use of these tools – are putting your company’s proprietary data into the AI universe, which means AI is training on your data.

Business subscriptions, which often ensure that the underlying AI model is not continuing to learn from your company’s data, can start with as few as two licenses. However, you should always verify whatever tool and subscription type you are buying is not training the AI on the data being inputted by your team, even if it is a business or enterprise subscription.

2. Failing to fact check.

One of the biggest risks of using AI tools to generate content is assuming that their output is 100% accurate, even if you give them excellent prompts. There’s also the risk of plagiarism. Just look at the PR nightmare that CNET, a respected news outlet, created by using AI to generate financial articles.

Fact checking – and source checking⁽¹⁾ – by a human, what the industry commonly calls the human in the loop, is a critical step before publishing any AI-generated content.

“Stop thinking about it as ‘AI’ and start thinking about it as ‘assistive technology’, with assistive being the operative word,” says Geoff Livingston, Founder and Chief Strategy Officer of CognitivePath, a Washington, D.C.-based AI consultancy.

3. Thinking AI is psychic.

This advice comes from Nicole Leffer of A. Catalyst, a respected AI advisor to CMOs. Generating quality AI content is a two-sided equation. If you don’t provide good input (aka prompts) into the tool, then you’re likely going to be unhappy with the output.

As Nicole says, “Context is critical. Provide to the AI tool the same information a human would need to do a good job on the project.”

4. Not proactively partnering with your Finance, Legal and Technology teams.

Marketing teams have begun to use AI-supported software to perform more sophisticated functions such as segmentation strategy and personalization. As with the implementation of any martech platform, a company’s Finance, Legal, and Technology teams should be involved in sourcing, approval, and implementation – especially in cases where the new technology will tap into company data (see mistake #1).

It’s critical for marketing leaders to initiate proactive conversations with their functional counterparts to prepare, and secure buy-in, for the implementation of new AI tools. Leading with the value AI delivers will help internal stakeholders understand how AI technology, such as chatbots on your website, will improve the customer experience.

5. Chasing shiny objects.

Most marketers remember the overwhelming Martech Landscape graphic that was first published a few years ago. Today, the proliferation of new AI tools has a similar feel. So how does a marketing leader select the AI tool(s) that best supports the company’s marketing needs?

One of the biggest mistakes, says Nicole Leffer, is implementing too many AI tools. Instead, she says, “focus on one core tool and teach your teams to use it effectively and to its full capacity.”

Geoff Livingston adds, it’s critical to “sync with your technology teams to ensure the new tool will work with your company’s existing data and systems.”

AI tools offer tremendous potential for enhancing marketing strategy and accelerating tactical execution. However, the use of these tools can create serious risks for an organization. It’s critical that marketing leaders approach the implementation of AI tools thoughtfully and be aware of the potential pitfalls that can expose the company to data privacy and reputational risks.

⁽¹⁾ Case in point: We asked Claude to generate suggestions for an opening sentence to start this article. Claude’s results included this statistic: “In an era where 83% of businesses now consider AI a strategic priority….” We then asked Claude where the 83% stat came from. The answer: “I apologize for the confusion. The 83% statistic I mentioned is not from a specific, verifiable source. I generated that number as part of an example opening, but I should not have presented it as a factual statistic without a proper citation.”