7 Potential AI Issues You Should Keep an Eye On

Updated on May 10, 2023
7 Potential AI Issues You Should Keep an Eye On

It’s estimated that a whopping 77% of all companies are either actively using AI or exploring what its implementation may bring. 

So far, this technology has been touted as revolutionary, so it makes sense to adopt it in your business as quickly as possible. 

Yet, like every new resource, you also need to understand its current limitations and avoid using artificial intelligence (AI) for applications it’s simply not ready for. 

Let’s go over the potential applications of AI in business and the mistakes you should avoid when adopting this technology. 

The Applications of AI in Business

From marketing to logistics, manufacturing, and telecommunications, the potential applications of AI technology are endless. 

Take digital advertising platforms that use AI to evaluate hundreds of variables in a matter of seconds in order to deliver the best ad to digital users. Or shipping and logistics firms that power their real-time warehouse stock management systems with powerful artificial intelligence.

AI has also had measurable results in most of these scenarios. Some call centers reported an increase of 69% in customer satisfaction rates, which was accomplished by furnishing agents with AI tools. 

But, even though AI can already help you successfully automate necessary tasks, this technology still has a long way to go. 

7 Mistakes You Should Look Out for When Using AI

One major mistake that affects not only your AI implementation, but your whole business, is not having a clear plan. 

If you don’t know how you plan to achieve the objectives you set for yourself, there’s a strong chance your AI implementation will be turbulent at best. 

In addition to the above, some of the errors you should avoid at all costs include:

1. Over-Reliance On AI Tools

AI tools can analyze data, condense information, and harvest details from different sources. However, you should have a verification system in place to avoid relying entirely on your AI resources. 

Let’s say you have an AI tool to help with your competitor’s marketing research in the US. Even after seeing the results, you should use a VPN server US connection to verify the local competitors and their features. 

2. Lack of Expertise or Knowledge

One major characteristic of AI tools is that they’re not as easy to use. These actually have a learning curve because of the way that artificial intelligence models work. 

Therefore, implementing AI tools without having someone on your team that has the right expertise or knowledge may be tricky. This doesn’t necessarily mean hiring an in-house developer. 

That said, having someone that can write prompts and is familiar with the mechanisms powering AI resources is a great idea. 

3. Rigid Processes That Don’t Change

AI has the potential to accelerate or otherwise affect your internal processes. However, a lot of companies fail to reshape their processes, which can create inherent bottlenecks that were previously nonexistent. 

This can become an issue, so review your processes, make sure they’re flexible, and avoid implementing AI in areas that can’t change. 

4. Not Focusing on Data Security

GDPR, HIPAA, and other regulations dictate how data must be handled in different situations. These protocols have to be abided by whether you use AI or not. 

The problem is that AI is not designed around data security. So, you need to think about the information you want to protect and how it will be kept safe when combined with your artificial intelligence tool. 

5. Limited Testing or Validation

AI technology is similar to a supply chain because this type of tool can complete repetitive processes with minimal errors. With that in mind, it’s still possible for AI tools to make mistakes, so it’s also essential to have a testing or data validation system in place. 

This can consist of either spot-checks, manual reviews, or even another AI tool designed to test or validate. That said, if you use another AI tool, remember to create a testing system for this solution. 

6. Only Implementing AI in Part of Your Business

AI is not a resource that can only be used by one department. There are many areas of AI, including its technical area and business strategy application, among others. 

Thus, you need to create a company-wide adoption plan, think about how different stakeholders will use this resource, and make sure that the AI is introduced in a safe, effective way. 

7. Disregarding Ethical and Legal Elements

Finally, it’s crucial to keep the ethical and legal elements that may impact your AI application in mind. 

You need to keep in mind questions like:

  • Will the AI be provided by a third party?
  • Does your industry require adherence to certain regulations?
  • And does the technology provider abide by the same regulations as you do?


There is no doubt that artificial intelligence will change the way we manage our businesses and complete necessary tasks. 

With that in mind, it’s also important to understand where the technology currently is and its limitations, as well as the future advancements that developers have in store.  

We hope that the 7 mishaps listed above help remind you of scenarios you want to avoid and aid you while you implement AI tools into your business. 

Article by:
Kenny Trinh
While he’s not editing articles on the latest tech trends, he likes to discuss business and entrepreneur. His writing has been featured in national publications such as Forbes, RD, Yahoo Finance, HackerNoon among others.

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