AI Slop Is Marketing's Latest Victim

Marketers ruin everything we touch.

I've been saying this for years. First, I noticed billboards north of Atlanta destroying the countryside. Then came spam email corrupting phenomenal technology. Don't get me started about text message marketing.

Any opportunity we have as marketers to push, we use. And eventually cause it to be ruined.

You can almost pinpoint exact dates when marketing tactics destroyed new technologies.

That history is repeating itself with AI content generation becoming the next technology we're collectively ruining.

The Rise of AI Slop

There's now a term for this phenomenon: "AI slop" (Reuters Institute, 2025). It's appearing everywhere – generic content where large language models are given a topic to spin up a page or article with minimal human oversight.

Many people are using AI effectively as a tool to augment their capabilities, correct grammar, or generate ideas. This represents the right balance.

But the urge to create more and more low-value content is growing stronger.

This problem is complicated by two contradictory trends: AI systems are getting significantly better while platforms designed to identify AI-generated content remain unreliable.

Ethan Mollick, one of my favorite voices of reason (LinkedIn, 2025) in this space, frequently points out that tools meant to identify AI-generated content produce far too many false positives to be useful.

A recent Guardian article describes this "AI slop" problem. The proliferation of low-quality AI content is actively distorting online information ecosystems (The Week, 2025).

This mass-produced content, often created purely for profit, misleads users and disrupts algorithms, degrading our entire information environment.

The Production Framework Driving AI Slop

The mechanics behind AI slop follow a simple formula:

1. Find trending topics or high-search-volume keywords

2. Use AI to generate content at a massive scale

3. Optimize for algorithm visibility, not reader value

4. Publish without substantive human review

5. Repeat thousands of times

The economics make this approach irresistible for certain businesses. When you can produce 500 articles for less than the cost of one quality piece, the quality threshold drops dramatically.

This production model represents everything wrong with how marketers approach new technologies – maximum output with minimum value.

Building An Ethical AI Content Strategy

So what's the solution? Start by not being part of the problem.

Develop an AI content generation strategy that aligns with your values as a brand, business, or individual creator.

Understand that premium-level AI tools aren't there so you can pump out 5,000-word articles. They exist to make your 3,000-word article far better.

Explore research capabilities from advanced AI systems to help you investigate topics more thoroughly. These tools can help you find connections and insights you might miss on your own.

Citations matter more than ever. I don't care how you implement them, but citations are the trust metric for the AI-generated world (Futurism, 2025). People should be able to check your references and make their own decisions about your content.

Find ways to inject your authentic self into everything you create.

Authenticity in a world of AI-generated images, videos, personalities, and Max Headroom-style solutions will be one of your most valuable assets going forward.

In my case, I spend considerable time on my drawings every week because I'm trying to grasp concepts and find ways to visually simplify them. This process cannot be replicated by an AI system yet (although I do use AI to clean up the diagrams and font).

I also ensure that I cite or link to articles, academic theories, or books as often as possible, as I want to share the content that is shaping my thinking about where all of this is headed.

The Resistance To Better Practices

Many marketers will resist these suggestions for understandable reasons.

First, the economics of scale are compelling. Why spend hours crafting thoughtful content when you can generate hundreds of pieces in the same timeframe?

Second, many believe Google can't effectively distinguish between AI slop and quality content. While this may be temporarily true, search engines continuously improve their ability to identify value.

Third, in the short term, flooding the market with AI-generated content might actually work as a strategy. But these gains will be temporary as both algorithms and humans get better at identifying and filtering low-value content.

Finally, creating authentic, value-driven content is hard work. It requires thought, research, and personal investment – all things that run counter to the automation mindset.

The Stakes Are Higher Than We Think

If we continue down this path, we risk several significant outcomes.

Trust in online content will continue to erode. Users will become even more skeptical of everything they read, making it harder for legitimate creators to connect with audiences.

Search engines and social platforms will implement increasingly aggressive filters, potentially harming even quality creators caught in the crossfire.

The signal-to-noise ratio online will worsen dramatically. Finding valuable information will become harder as AI slop drowns out thoughtful content (Searchstax, 2025).

Most importantly, we'll waste another transformative technology. Rather than using AI to enhance human creativity and productivity, we risk reducing it to a tool for digital pollution.

This matters because content remains how we share ideas, build businesses, and advance knowledge. Corrupting this ecosystem hurts everyone.

The choice is simple but challenging.

Will you use AI to amplify your unique human perspective, or will you contribute to the growing sea of undifferentiated digital noise?

Your answer will determine whether you're part of marketing's solution or its next cautionary tale.