AI-Generated Content: Why Caution Beats Blind Adoption

After nearly 30 years of commercial availability, AI content generation is having its moment. Thanks to technological advancements like better output production and user-friendly interfaces, content creators jumped on the AI content bandwagon with the goal of churning out content quickly and cheaply.

There’s no questioning that AI content generators have value, but it’s important to exercise caution when using these tools. Their ability to consistently produce high-quality content remains largely unproven, which could lead to serious issues for content creators down the road.

In this article, we’ll discuss why digital marketers may want to avoid blindly going all-in on AI for content production.

Current landscape of AI content generation

As AI-generated content’s popularity skyrocketed over the past several months, OpenAI’s ChatGPT led the way with some seriously impressive numbers. The platform’s free research preview received an estimated 13 million unique visitors per day since launching in November.

Here’s part of what happened next.

Publishers try their hand at AI content

It’s not just small bloggers and content creators trying to harness this technology. Some of the biggest players in the SERPs, including Men’s Journal, CNET, Bankrate, and Buzzfeed, jumped on the bandwagon. However, it hasn’t gone well.

Men’s Journal faced backlash after publishing its first AI-generated article. It apparently had at least 18 inaccuracies — not great for E-E-A-T. CNET and Bankrate faced similar negative press after publishing factually inaccurate explainer articles, and they have since paused their AI-generated content.

Google joins the AI race

On the heels of OpenAI’s ChatGPT, Google hastily announced its own AI chatbot, Bard. Parent company Alphabet’s stock immediately plummeted following an advertisement for the chatbot that showed an incorrect answer when asked about the James Webb Space Telescope.

According to NASA records, the James Webb Space Telescope was not the first to take photos of these “exoplanets.”

So, what happened exactly?

The above examples highlight the risks of blindly trusting AI-generated content, especially when it comes to sensitive or complex topics.

One of the key limitations of AI content generators is their tendency to confidently output incorrect information. These tools rely on limited data and are trained only on specific sources, so they may produce biased, outdated, or simply incorrect information. Additionally, AI struggles to understand and convey elements like context, irony, and sarcasm, which are inherent to human communication.

Lessons from early and late adopters

Even big corporations can fall victim to the temptation of jumping on a new trend or keeping up with competitors. However, being an early adopter of a new technology or hot trend isn’t always a recipe for success.

When jumping on a trend goes wrong

For example, in the early ‘90s, Pepsi jumped on the health-conscious trend by launching a clear, caffeine version of their signature cola, Crystal Pepsi. Pepsi marketed the drink as a better-for-you alternative, as clear items were often perceived as healthier at the time. However, the product failed to catch on and was pulled from shelves just two years later.

Similarly, in an attempt to keep up with Netflix, Blockbuster tried to pivot to a subscription-based model. The plan was poorly executed, though, and the company failed to adequately adapt to the changing market. This lack of strategic foresight ultimately led to Blockbuster’s bankruptcy in 2010.

While Pepsi recovered from their misstep by pulling Crystal Pepsi and moving on, Blockbuster’s misjudgment ultimately led to their downfall.

A cautious approach may be the best option

When it comes to dramatic shifts in strategy, a cautious approach may be the way to go, as digital streaming kingpin Netflix can attest. Although Netflix is widely recognized for popularizing online streaming, it actually wasn’t the first streaming platform.

Early pioneers in the online streaming space include the now mostly forgotten iTV and RealNetworks, and even YouTube, which launched two years before Netflix offered digital streaming. Netflix took a sit-back-and-wait approach until the technology was more refined. Once the company was confident, it entered the market and became a dominant player.

While AI can be a powerful tool for content creation, the cautionary tales of companies like Blockbuster and Pepsi demonstrate the potential risks of early adoption of a new trend or technology. As content creators explore the potential of AI for content production, it is important to approach with a critical eye and a measured strategy. This ensures that they’re using the tools in a way that supports the writer’s creative goals and adds value to the content, rather than simply jumping on a trend.

AI falls short in meeting Google’s content criteria

Despite Google rolling out algorithm after algorithm to update and change its search engine, its core purpose remains the same: presenting users with helpful, reliable, and people-first content.

Google’s ideal content is insightful, interesting, and provides substantial value compared to other content in the SERPs. This presents a major challenge for AI-generated content, because it often lacks a unique perspective or expertise angle.

Google explicitly warns against creating search engine-first content, which is content that essentially summarizes what others have said without adding much value. Since AI-generated content is trained on pre-existing information, it is incapable of providing a fresh or unique viewpoint. This adds weight to the argument that content creators should be cautious about relying solely on AI-generated content when trying to meet Google’s value requirements.

Using AI where it makes sense

AI tools like ChatGPT may have limitations, but they’re still valuable for processes like content creation when used properly. We’re not advocating for a boycott of these tools, but rather a cautious approach that incorporates the best of both worlds. Think of them as an assistant (instead of the new lead copywriter).

By combining the efficiency of AI content generation with the creativity and expertise of human writers, you can create high-quality content that provides the value and unique perspective that Google wants. Ultimately, it’s about striking the right balance and using these tools in a way that enhances your content rather than produces it entirely.

Effective ways to use AI tools in your content creation process

Brainstorming – Use the tool to generate ideas and subtopics that can inspire content creation.
Content Structure – AI-generated outlines can help kick off your piece of content by providing a framework.
Summary and Introduction – Feed the tool your content and have it provide a summary or introduction. The tool derives the output from the details you provide, so you can avoid potential issues with inaccurate information.
Title – AI can generate options for content titles that align with your content’s theme.
Meta Description – Feed the tool your content so it can produce the page’s meta description.

Conclusion

In the realm of content creation, where Google rules the roost in terms of what’s served to potential viewers, it’s crucial to find the sweet spot between using AI-generated and human-written content. But how much of each should you use? As with most things in digital marketing, the answer is not black and white.

While some may rush to adopt the latest and greatest tech, taking a more measured approach can help you stand out from the crowd. After all, blind adoption has resulted in the noteworthy missteps by Bankrate, Men’s Journal, and other online publishers. By being mindful and strategic in how you use AI, you can provide better user experiences, gain a competitive edge, and avoid both ranking and reputation mishaps.