The 3 Biggest Problems You’ll Face With Content Automation


One of the most exciting things about new technologies is the various ways we can use them. Of course, the technology itself can be fascinating, but this is often overshadowed by periods of exploration. We can use these innovative tools and see how they can make our way of life and our business practices smarter.

This is really where we are with artificial intelligence (AI) and automation in business right now. We apply machine learning techniques to various fields: curation, production and distribution of content between them.

As part of a larger content strategy, AI has the potential to improve personalization, reduce retention time, and make delivery more efficient. That said, as with any technological tool, automated content is not without limits.

So what should businesses be aware of when implementing automated tools? How can we use AI to make a dent in content marketing, while avoiding complications? Let’s take a look at the issues to be aware of, as well as the broader implications of its continued use.


Content is one of the most powerful tools for building brands. Automation can ensure that the widest possible audience is reached with minimal human interaction. AI website builders can help determine the design and layout of content that may be most appealing for specific demographics. It can be helpful to have more of an eye on the marketing copy, when it is most appropriate for your target audience.

These automated ingredients don’t replace the human element in building a brand, but they can support it by doing some fieldwork.

However, it’s when we take a closer look at current digital marketing trends and what consumers are looking for in their brands that we start to see some issues with content automation. The place of today’s consumers a high premium on authenticity as a component of their brand experiences. The content should demonstrate what the company does really well and how it is continually developing in those areas. It must communicate to consumers that the company is trustworthy in its area of ​​expertise.

AI content execution finds blog and social media posts produced to match what the algorithm determines consumers want to see, rather than accurately reflecting the interests and areas of growth of the company. business. As such, this approach can appear inconsistent and inauthentic.

Marketers understand that writing with a brand voice is much more complicated than using key phrases. It must reflect the underlying values ​​of the company and explore in depth topics that demonstrate expertise.

Today, automated content production tends to be superficial – proficient at relaying facts, not very effective at providing the context and relativity that help make content valuable. This means marketers tend to ‘oversee’ AI, editing and rewriting to meet business and audience needs.

Curation through automation

One of the ways that automation can be useful is through content curation and delivery. Small business owners or marketers can leverage their time and resources to produce only a small amount of original content, then automatically organize summaries in email newsletters or repost them on networks. social.

However, one of the concerns surrounding automated content curation is quality control. Businesses are fundamentally convinced that AI can deliver content that reinforces business messages. For the most part, AI is simply not able to understand the contextual nuances required for effective curation. This can not only lead to errors in the type of automation of the content, but also in what it censors.

Last year, YouTube has reinstated human moderators after finding that he was overzealous in removing content. Without the capacity for cultural sensitivity, AI tends to have a hard time understanding the context and overcensing as a result. This can lead to the removal of vital information from news summaries; whether the intention is to serve the public interest or to achieve marketing objectives.

Misinformation is another major concern when it comes to automated content curation. Items that seem relevant to an algorithm based on the topic do not necessarily amount to trustworthy information.

supposedly ‘Fake news’ has become a widespread problem through traditional and digital channels, whether through sloppy reporting or by design to move an agenda forward. By including such articles in organized summaries, businesses are contributing to the damage that disinformation does to public discourse. Worse yet perhaps, they could inadvertently contribute to further public manipulation.

Quality connections

Automation is increasingly used to improve our ability to connect with consumers. This is usually seen from a customer service perspective through chatbots, but is also starting to be used through content delivery platforms – social media, email delivery. This can be an effective approach to simple initial interactions with customers, before handing over to human staff for more in-depth conversations.

The problems really arise when businesses rely too much on AI content tools to engage with customers. These systems evaluate the most appropriate response to customer contact and respond automatically. Unfortunately, no amount of Natural Language Processing (NLP) coding can make AI capable of human behavior such as the empathy that consumers often seek in their engagement with businesses.

Bank of America automatic responses to the #Occupy movement on Twitter are prime examples. Rather than genuinely engaging with an audience concerned about the bank’s ostensibly unethical practices, one bot simply responded to “help” them with their checking account issues.

The result of overuse to connect with customers is that those consumers tend to shy away from aggrieved interactions. While to business owners this may seem like an effective tool, consumers who take the time to try and make quality engagements with businesses feel, and rightly so, that they deserve the same. in return.

Automation in itself is not a problematic technology – it can be an innovative tool to improve efficiency. The problems arise in the way we use it. Rather than relying on AI to take care of the tasks, we need to treat it as a collaborator. Not only does this provide the human element customers need and deserve, it can also prevent some of content marketing’s worst mistakes.


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