In last month’s column, I talked about an upcoming presentation my boss and I were preparing to deliver. We’d been asked to lead a conference session on newsroom training and the lessons we learned after a year-long effort to retrain a newsroom. 

He was busy. I was busy. Our combined busy schedules meant we didn’t have a lot of time to devote to drafting the perfect presentation. If we weren’t careful, we ran the risk of pulling together the PowerPoint version of AI slop. 

We could have Googled what a bunch of other newsrooms had done, asked our favorite AI chatbots to throw in a few suggestions, and — in a short amount of time — voilà, we would have had ourselves a presentation. 

Except that's not what the audience wanted. It's not what they needed. 

They could have easily Googled the same questions and found the same answers. They wanted lived experience. They wanted lessons learned. They wanted to hear what worked, what failed, and what we'd do differently if we had to do it all over again. 

They didn't want slop.  

I introduced commodity and non-commodity content in my last column, and I want to continue the discussion because marketers, communicators and content creators need to understand how these content types affect visibility in an AI-driven world. 

For years, organizations were rewarded for publishing the best summary of information available online. Today, AI engines can generate those summaries in seconds. The value of aggregating content is declining while the value of original insight is rapidly increasing. 

That's where the distinction between commodity and non-commodity content becomes important. 

What is commodity content?  

Just like corn, oil and livestock, commodity content is something you can get almost anywhere. 

It's interchangeable. Frankly, if you removed the author's name or company logo and replaced it with another organization's branding, most readers wouldn't notice. 

Commodity content is old-school SEO. It's listicles and explainers. It's content designed to answer broad questions like: 

• What is predictive maintenance? 
• What are the benefits of cloud manufacturing? 
• What is a digital twin? 
• How does supply chain visibility work? 

There was nothing wrong with this approach. In fact, it worked remarkably well for years. 

The problem is that AI engines are now very good at gathering, synthesizing and rephrasing information that already exists online. If your content simply summarizes what's already been written elsewhere, large language models can often replicate it and deliver it directly to users without anyone ever visiting your website. 

Commodity content doesn't pull from experience. It pulls from other sources' work. 

And here's the unpopular comment nobody wants to hear: Commodity content is often just AI slop in disguise. 

What is non-commodity content?

The alternative is non-commodity content. 

Non-commodity content is unique because it can only be created by the people, organization or company that lived the experience. It's built on insights that don't exist elsewhere. It's the story behind the lesson learned. It's the expertise developed after helping hundreds of customers solve the same problem. It's the analysis of proprietary data. It's the firsthand account of what worked, what failed and what happened next. 

Non-commodity content might include: 

• Original research 
• Customer interviews 
• Case studies 
• Expert analysis 
• Product-development insights 
• Industry observations 
• Lessons learned from successes and failures 

This is the type of content AI engines cannot independently generate because the information doesn't already exist across thousands of websites. 

That lived experience is difficult to replicate, which makes your content more likely to be discovered, referenced and cited. 

To put it another way: Commodity content gets absorbed. Non-commodity content gets cited. 

How can you tell whether your content is commodity or non-commodity?  

You may be looking at your own company's blog or newsroom content and wondering how much falls into which bucket. Perhaps you’re putting together a content marketing plan and trying to create more unique ‘non-commodity’ content. I’ve assembled this decision tree to help make the designations easier. 

Decision Tree: Is Your Content a Commodity?

Could another company publish a very similar piece of content with minimal edits? 
Yes: That's commodity content. 
No: Move on to the next question. 

Does your content primarily summarize information already available online? 
Yes: That's commodity content. 
No: Move on to the next question. 

Does your content include original customer insights, expert interviews, case studies, proprietary data or firsthand experience? 
Yes: Move on to the next question. 
No: You're at risk of creating commodity content. 

Does your content answer questions that your audience can't easily find answered elsewhere? 
Yes: Move on to the next question. 
No: You're at risk of creating commodity content. 

Does your content demonstrate your organization's expertise or unique point of view? 
Yes: Congratulations — you're producing non-commodity content. 
No: You're likely creating commodity content that will struggle to differentiate itself in answer engines.