Top 5 Disadvantages of Using AI in Digital Marketing

Digital marketers can attest to the critical contribution of technology to their industry. Artificial intelligence, machine learning, and natural language processing allow for better customer experiences.

AI chatbots, for example, learn human behavior. They can then respond to customer queries on time. Marketers also use them to make product recommendations based on past purchasing behavior.

The same technology also helps in conversational marketing. Customers are more likely to buy when they feel like they’re talking to humans and not machines. 

Digital Marketers can also use AI for talent acquisition platforms. Let’s say the department is looking for a content writer. By posting the position, they get tons of responses. 

The AI can go through the resumes and articles from prospects. Recruiters then get recommendations on the top candidates. It saves on time that would go into checking each application by a human.

Yet with all the benefits, digital marketers face some challenges with artificial intelligence. We will explore some of them in our article below.

Top 5 Disadvantages of Using AI in Digital Marketing

1. The Ever-Evolving Nature of Artificial Intelligence

The one constant with technology is that it keeps evolving. Digital marketers must keep up with the changes and emerging trends.

But, having the correct information is not enough. The company must also have the capacity to upgrade software. Only then can they be sure of adapting to the existing environment? 

The teams must also be careful about the process of upgrading. Any breakdowns may result in the loss of data or codes. Without backups in place, restoring such would be time-consuming and costly.

2. Lack of Trust in AI Technologies

A Gartner report has some interesting statistics. 84% of digital marketers believe AI can enhance customer experiences. Yet, the report goes on to show that there is a level of mistrust in the technologies. 

Mistrust levels are as high as 75% for those in the pilot stage of adoption. A further 53% who have already adopted the technology still have some doubt levels. 

Some of the misgivings could be because AI is still a new concept. It may also be quite complex to anyone who does not have the proper training. Some customers are also not comfortable with some of the methods. Recommendation tools, for example, learn behavior based on past activities. 

It then recommends a product or service from the insights. The customer may be wary of technology that seems to know them too well. But, acceptance levels are rising. This portends good news for mainstreaming AI in digital marketing. Digital marketers must be more transparent when using AI applications. 

They can, for instance, explain to customers how they will use the data. It removes the mysteriousness and complexity of the applications. In the end, customers will be more trusting of the processes.

3. Lack of IT Infrastructure 

The initial cost of setting up IT infrastructure can be pretty high. Hardware such as computer systems requires capital investment. There are also attendant maintenance costs. The company will also need an IT team to oversee operations.

The reality is that some may lack the financial might. The good news is that cloud-based solutions are available. The vendors provide infrastructure and support at monthly or annual fees. It becomes a viable solution for businesses that cannot afford in-house systems. 

4. High-Quality Data Shortage

You cannot talk about digitalization without mentioning data. Digital marketers depend on data for all marketing activities. They use it for things like competitor analysis, lead generation, and market research. 

AI tools also depend on such for all their functionalities. Take the case of the AI chatbots above. A marketer must have data that forms the basis of the AI database. 

The pre-defined scripts provide reference material for the chatbots to learn human behavior. Yet, there is a shortage of high-quality data. The situation is direr when looking at those specific to AI applications. It becomes a hindrance for the technology to perform at the highest level.  

Organizations must find a way to overcome the data quality challenge. True, companies collect and generate tons of data every day. But, the struggle still exists to find the correct data for AI marketing needs. 

5. Moral and Ethical Issues

With any automation comes some moral and ethical issues. One of the most significant is job losses due to automation. Statistics show that up to 37% of employees fear job loss due to automation. By the end of 2022, there could be a 13% drop in human work hours. By 2030, 20 million manufacturing jobs could end up with robots. 

But, optimists feel that automation will create new job opportunities. It is also a chance for those in redundant jobs to look for new career paths. Companies must also invest in proper security measures to guard customer data. Privacy concerns are becoming an issue. 

Companies use sensitive information to create algorithms or scripts for AI apps. Yet, all this happens without customer awareness. It takes away the consent aspect for the use of personal data.

A survey sampled more than 5,000 respondents. They were from the US, UK, and Australia. 71% of customers are not agreeable to using personal data for AI applications. For them, the promise of a better customer experience is not a good enough reason. 

A further 63% are uncomfortable about AI making decisions without their knowledge.  Countries are implementing regulations that guide the use of personal data. An example is the General Data Protection Regulation (GDPR) by the European Union. 

Companies must also address such concerns with the clients in a transparent manner. Perhaps this quote summarizes this point well. 

“What all of us have to do is to make sure we are using AI in a way that is for the benefit of humanity, not to the detriment of humanity.” -Tim Cook, CEO of Apple.

Final Thoughts

Technological Innovations like artificial intelligence have transformed the digital marketing landscape. Yet, there are some challenges to overcome, as we have highlighted above. But, the outlook is positive, and there is much to look forward to.

What are your thoughts on the AI challenges facing marketers? We would love to hear from you. 

Tirtharaj Raman

A Backpacker with keen interest in Digital marketing. Responsible and passionate for building a digital culture at SoftwareSuggest. Grabber to implement new competitive ideas to analyze and boost online presence. Could be found in mountains and solo traveler by birth.