AI in your marketing – Yes or No?

Artificial intelligence is revolutionizing the marketing landscape, offering businesses new ways to automate tasks, analyze data, and take over tasks such as copywriting, design, data entry, etc. But is it really safe to use AI for your marketing? Let’s explore the pros and cons!

Why is AI in marketing helpful?

1. Efficiency & Automation

   AI-powered tools can automate repetitive marketing tasks, such as email campaigns, social media scheduling, and customer service chatbots. This saves time and allows marketers and business owners to focus on strategy and creativity.

   
   

2. Data-driven insights

   AI can process vast amounts of data, saving time when it comes to numbers and clustering.

   
   

3. Fast access to relevant information

   If you need information, you might read the first page of articles from a Google search. AI goes far beyond that.

   
   

4. Higher engagement

   Surprisingly, studies on engagement have shown that AI-generated texts are more engaging for customers than those written by real people.

   
   

5. Chatbots & Customer Support

   AI-powered chatbots can provide instant responses to customer inquiries, improving customer satisfaction while reducing the need for human intervention.

   
   

The downsides of AI in marketing

Unfortunately, AI does not provide only benefits. As a marketer, I see a big downside to this technology:

1. Lack of human touch

   Yes, AI writes texts in a more engaging way. However, if you’ve seen some AI-generated texts, you can recognize them easily due to their specific structure patterns, word choices, and a certain kind of weirdness that only a human would notice. Moreover, since AI is not a marketing specialist, it has access to industry information but doesn’t truly know or understand your brand. It lacks emotions and human creativity. The content it generates is often too basic, suitable for everyone in your niche, which makes your content less unique. The more AI-generated content there is, the less engaging it becomes to read anything—since everything starts to look like an AI copycat.

   
   

2. Data privacy

   With AI relying on user data, privacy regulations like GDPR require businesses to be cautious about how they collect and use information. Given recent lawsuits related to this topic, it is tricky to feed someone else’s algorithm with your own sensitive data.

   
   

3. Implementation Costs

   When talking about improved versions of existing AI tools or about more specific AI tools, such as healthcare solutions, internal algorithms, etc., implementation can be costly for users.

   
   

4. Low Data Quality

   AI is only as good as the data it’s trained on. Inaccurate or biased data can lead to misleading insights, resulting in poor decision-making. At the moment, AI can’t differentiate high-quality scientific reports or valuable articles from fakes and low-quality information. The problem is that you usually can’t check every single source of the data insights provided by AI, so you have to believe that the results you get are reliable. And what if not?

   
   

   Recently, I read an interesting thread about incorrect data provided by AI on Instagram. The most liked comments were actually making fun of how often you get completely wrong answers even to the simplest questions, and you only notice it if you already know the topic and double-check. But how many people are searching for legitimate advice without actually knowing the topic?

   
   

5. Possibility of low-quality results

   Even if the data were qualitative, sometimes AI gets creative in a bad way - making up its own facts and numbers, mixing up irrelevant information, and providing tier results that take much longer to fix.

   
   

   Recent story from my life: When I was creating this website, the platform I used had an AI tool for faster website development. I clicked on it, and without my input and against my directions, it started creating a structure I didn’t need/want - one that would have been extremely bad for user experience in the future. It seemed to have predefined settings, but it couldn’t really do anything beyond that. I spent around 40 minutes trying to fix it, but it didn’t correct anything that was already there. In the end, I gave up and started creating from scratch by myself, which took a lot of extra time.

   
   
   
   

So, AI in marketing: yes or no?

I would say that a balanced approach is ideal for saving time and focusing on strategic directions. However, it is always a bad idea to rely 100% on AI for a specific task without reviewing it or adding your own input.