Artificial intelligence has left an undeniable impact on the marketing landscape today. From personalized campaigns to predictive analytics, AI influences our approach to almost every aspect of online marketing.

However, just like any other tool, AI used incorrectly does more harm than good. Are you making any of these AI marketing mistakes?

1. Overestimating What AI Can Do

While AI is powerful, it’s neither a magic bullet nor a replacement for human insight and creativity. AI excels at analyzing vast amounts of data, identifying patterns, and making predictions. However, it cannot process nuance the way people can. It also can’t create something entirely original.

What to Do Instead: Use AI to supplement your marketing efforts, not replace them. Combine AI’s data-driven insights with your team’s creativity and intuition to craft campaigns that resonate with your audience.

For instance, your AI tools can identify which content performs best at different stages of the customer journey. However, human employees are better at crafting a compelling narrative that engages and converts. Your AI’s insights can guide your actions, but cannot and should not perform them all for you.

2. Jumping on the AI Bandwagon Without a Plan

AI may be the hottest new thing, but if your company rushes to implement your own AI approach without a concrete plan, you’ll likely struggle. AI needs to align with your overall marketing strategy—and you need to know how it aligns. Without a plan, you can end up wasting resources, creating inconsistent messaging, and creating marketing campaigns with abysmal conversion rates.

What to Do Instead: Clearly define your marketing goals and determine how AI can help achieve them. Are you trying to increase engagement, boost conversions, or improve customer retention? Once you have a clear objective, identify the specific AI tools and techniques that can support your goals. In other words, fit AI into the marketing strategy that you know works, rather than rebuilding your entire strategy just to include AI.

3. Ignoring Data Quality & Quantity

AI thrives on data—that’s no surprise by now. But it can’t work with just any data. Poor-quality or irrelevant data can lead to inaccurate insights and misguided marketing strategies. You also need to consider where your data is coming from. Is it your own? If it originates from outside your company, are you even allowed to use it?

What to Do Instead: Invest time in collecting, cleaning, and organizing your data before feeding it into your AI tools. Ensure your data is relevant, up-to-date, and representative of your target audience. This means removing duplicate entries, correcting inaccuracies, and filling in missing information. You also need to be absolutely sure that any data you don’t create yourself comes from willing sources.

4. Getting Way Too Personal

Personalization is one of AI’s most celebrated capabilities, but there’s a fine line between providing personalized experiences and coming off as intrusive. It’s tempting to give AI every bit of data you can. But as experts have pointed out, AI lacks the emotional intelligence of a human, so it doesn’t know when it’s being insensitive or invasive.

What to Do Instead: Use personalization thoughtfully and avoid being overly familiar with your audience. Aim to add value by providing relevant content, offers, or recommendations rather than trying to showcase how much you know about your customers. For example, instead of using hyper-specific details like mentioning a customer’s recent purchase in an email subject line, focus on recommending products or content based on their broader preferences.

Above all, do not give your AI marketing tools confidential or sensitive data. Not only is this a serious violation of privacy principles, but it will only harm your reputation in the public eye. Collect and use only the data you’re legally permitted to have.

5. Making Customer Interactions Robotic

AI-powered chatbots and automated responses can handle many customer inquiries, but relying solely on AI for customer interactions can backfire. AI tools don’t always understand what a customer is asking for. Other times, when dealing with complex or sensitive issues, an AI’s lack of emotion can lead to upsetting responses. It’s no secret that when many customers call a helpline or use an online chatbot, many try to get the robot to send them to a human representative as fast as possible.

What to Do Instead: Implement a hybrid approach that combines AI with human support. Use AI to handle routine inquiries, tasks, or FAQs. Meanwhile, your actual employees should handle more complex or sensitive issues. This improves efficiency and ensures that customers feel valued and understood.

If your system defaults to an AI at the beginning of a conversation, state that upfront.  Also, make it easy to get to a human representative. Your customers shouldn’t have to navigate a complex menu to talk to a real person.

6. Not Supervising Your AI

AI needs near-constant supervision and performance review. Algorithms can save your team a lot of work—but your company’s needs will change. Your customers’ preferences will change. And if you don’t ensure that your algorithms change with them, you’ll continue to churn out campaigns that fail to deliver the desired results.

What to Do Instead: Regularly review your AI-driven campaigns and strategies to identify areas for improvement. Use metrics such as engagement rates, conversion rates, and customer feedback to gauge performance. AI learns over time, so the more you monitor and refine it, the more effective it becomes.

7. Ignoring Ethical Considerations & Privacy Concerns

In the age of data breaches and privacy scandals, ethical considerations are more important than ever. Too many marketers make the mistake of using AI to collect and analyze data without fully considering the ethical implications, which can lead to a loss of trust and damage to your brand’s reputation.

This invasive type of data collection is painfully obvious in cases like that of Eli Stein. He and his wife discovered they were expecting a child, but chose to hold back on making the announcement online. That didn’t stop a presumably AI-powered algorithm from flooding his social media feeds with ads for new baby supplies. And personal life events aren’t the only thing to consider. AI is trained on human-created data—and unfortunately, that data can reflect biases that the AI then perpetuates.

What to Do Instead: Be transparent about how you’re using AI and data. Ensure you have the proper consent from your customers before collecting their information, and respect their privacy by using data responsibly. Additionally, be aware of potential biases in your AI algorithms and take steps to address them to avoid perpetuating stereotypes or excluding certain groups from your marketing efforts.

8. Assuming AI is Good to Go Right Away

Many marketers expect immediate results once they implement AI solutions. It’s hard to blame them—AI’s capabilities are praised to high heaven. The reality is that AI requires time to learn and adapt, and it often takes weeks or even months to see significant improvements in performance.

What to Do Instead: Set realistic expectations and timelines for your AI projects. Understand that AI is a long-term investment, and be prepared to invest the necessary time and resources to see tangible results. Start with small pilot projects, gather insights, and gradually scale your AI initiatives as you gain confidence in their effectiveness.

Using AI Wisely in Marketing

AI is a tool that can enhance your marketing efforts when used correctly. It is not a one-size-fits-all solution. It is also no substitute for human intervention. But neither is it inherently a net negative. Using AI with human creativity and insight can help you create marketing strategies that produce worthwhile returns.

Ready to improve your AI marketing strategy? Contact us today.