Exploring the Benefits and Challenges of AI Generated Content in Marketing Strategies

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Why is AI generated content important for content marketing?

Content marketing has emerged as a crucial component for brands in attracting leads and building relationships. With 90% of consumers in the United States preferring personalized content, content marketing efforts are more effective when the brand is able to ensure that the content being delivered is dynamic and tailored to the needs of specific visitors.

As more industries consider whether to embrace AI tools and debate the benefits and drawbacks of doing so, it’s become clearer that AI will continue to play an increasingly important role in the years to come. 

Benefits of AI generated content

As with any automation tool focused on streamlining operations, leveraging AI content generators will allow businesses to create content faster and spend more time on customer engagement.

In scaling up on the volume of content that can be created and posted, a wider range of customers can be targeted in a shorter amount of time, allowing the brand to boost conversions and revenue.

Paying the costs of licensing for full use of AI content generation tools allows a smaller staff of content writers to produce just as much content as a larger team, but at lower cost.

Similarly, you can create powerful SEO content by asking the tool to focus on optimization so as to boost your position on search engine ranking pages (SERPs) quickly using these tools, which will make your content more impactful and draw more traffic. 

Risks of AI generated content

There are massive concerns in how quickly businesses are adopting AI tools into their businesses, and concerns about how the tools themselves function that are driving much of the debate and dialogue around AI content generation.

One of the major concerns is that Google has already adapted its algorithms to protect against the anticipated onslaught of AI-generated content in the coming years. The principle of E-A-T (Expertise, Authoritativeness, and Trustworthiness) as a measure of the value of content considers the expertise, authoritativeness, and trustworthiness content instills to determine if it should be prioritized in search.

Google has since added Experience into the algorithm, so as to ensure that content is written in such a way as to show that the writer actually understands the subject and has presented information that can be trusted. Thus far, content created by AI platforms has not shown the ability to adhere to the new E-E-A-T criteria.

AI generated content has also proven to be highly inconsistent in quality, depending what the machine has been tasked to address. Whether from a lack of current data or having to address topics that require a more subjective approach than factual approach, AI tools tend to struggle to create consistently high-quality material. This requires that human writers review, revise, and enhance the content, which–while faster–still requires time and manpower.

There are also significant copyright and plagiarism concerns with AI-generated content, as developers are using material they don’t have the rights or permissions to use as training data for their tools. The resulting content, whether in text or visual form, doesn’t include citations, and most tools in fact don’t keep track of sources used to generate the final output.

Again, this can be mitigated by having staff who go behind the tools and edit and revise the content in order to make sure that it’s not only factually correct but that it’s also not blatantly copying from other sources or that those sources are referenced before publishing.

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