One of the most exciting aspects of new technology is the varied ways we can use it. Sure, the tech itself can be fascinating, but that is often overshadowed by the periods of exploration. We get to take these innovative tools and see how they can make our lifestyle and business practices smarter.
This is very much where we are with artificial intelligence (AI) and automation in business at the moment. We’re applying machine learning techniques to diverse areas — content curation, production, and distribution among them.
As part of a wider content strategy, AI has the potential to improve personalization, reduce time in curating, and make dissemination more efficient. That said, as with any tech tool, automated content is not without its limitations.
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 what issues to be aware of, alongside some wider implications of its continued use.
Branding
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 to determine the design and content layout that can be most appealing to specific demographics. It can help to get more eyes on marketing copy, at the most appropriate time for your intended audience.
These automated ingredients don’t replace the human element in brand building, but they can support it by performing some legwork.
However, it’s as we look closer at the current trends in digital marketing, and what consumers are looking for in their brands, that we start to see some problems with content automation. Today’s consumers place a high premium on authenticity as a component of their brand experiences. Content has to demonstrate what the company genuinely does well and how it is continually growing in these areas. It must communicate to consumers that the business can be trusted in its area of expertise.
Running content by AI finds blog and social media posts being produced to fit what the algorithm determines consumers want to see, rather than accurately reflecting the business’ interests and areas of growth. As such this approach can come across as inconsistent and inauthentic.
Marketing professionals understand that writing in the brand voice is much more complicated than using some key phrases. It has to reflect the underlying values of the company and explore subjects in depth that displays expertise.
At present, automated content production tends to be shallow — competent at relaying facts, not so great at providing the context and relatability that helps give content value. This means that marketers tend to have to “supervise” the AI, editing and rewriting to serve the needs of the business and the audience.
Curation via Automation
One of the ways automation can be useful is in the curation and dissemination of content. Busy small business owners or marketers can leverage their time and resources into producing only a small amount of original content and then automatically curating digests in email newsletters or reposting across social media.
However, one of the concerns surrounding automated content curation is quality control. Businesses are essentially trusting that the AI can provide content that reinforces company messaging. For the most part, AI just isn’t capable of understanding the contextual nuances that effective curation requires. This can not only lead to mistakes in the type of content automation, but also in what it censors.
Last year, YouTube reinstated human moderators after finding that it was overzealous in removing content. Without the ability for cultural sensitivity, AI tends to have trouble understanding context, and over-censors as a result. This can result in vital information being negated from news digests; whether the intention is to serve the public interest or achieve marketing goals.
Misinformation is another key concern when it comes to automated content curation. Items that appear to an algorithm to be relevant based on subject matter do not necessarily equate to trustworthy news.
So-called “Fake news” has become a prevalent problem across traditional and digital channels, either through sloppy reporting or by design to push an agenda. By including such posts in curated digests, companies contribute to the damage misinformation causes to the public discourse. Perhaps worse, they could be inadvertently instrumental in the continued manipulation of the public.
Quality Connections
Automation is increasingly being used to improve our abilities to make connections with consumers. This is commonly seen from a customer service perspective through chatbots, but it is also beginning to see use through content providing platforms — social media, email outreach. This can be an efficient approach to simple initial interactions with customers, before handing over to human staff for more in-depth conversations.
The problems really arise when companies rely too much on AI content tools to interact with customers. These systems assess what the most appropriate response is to customer contact, and automatically reply. Unfortunately, no amount of natural language processing (NLP) coding can make AI capable of human behavior such as the empathy that consumers are often seeking from their engagement with businesses.
Bank of America’s automatic responses to the #Occupy movement on Twitter are prime examples of this. Rather than engage genuinely with a public that was concerned about the bank’s ostensibly unethical practices, a bot simply responded to “help” them with their checking account issues.
The result of overuse to make connections with customers is that those consumers tend to come away from the interactions short-changed. While to business owners it might seem like an efficient tool, consumers that take the time to try to make quality engagements with businesses feel — rightly so — that they deserve the same in return.
Automation in itself isn’t 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 tasks, we need to treat it as a collaborator. Not only does this provide the human element that customers need and deserve, but it can also prevent some of the worst mistakes of content marketing.
