The First Domino: How AI Is Commoditizing Software Faster Than Companies Can Build Moats

When people tell the story of how AI changed business, they usually begin with the launch of ChatGPT. But launches don't change industries by themselves. What changes people's minds is the first visible casualty. That first casualty wasn't a startup that quietly disappeared. It was Chegg.

The Real Lesson from Chegg

Most people view Chegg as an education company that simply got unlucky. That's the wrong conclusion. Chegg became the first public demonstration of a rule that is likely to define the next two decades of software:

AI commoditizes features faster than companies can build competitive moats. For decades, software companies operated under a simple assumption. If building a feature required three years of engineering effort, competitors would also need years to replicate it. Those years became your competitive advantage and your profits. AI fundamentally changed that equation. Capabilities that once demanded entire engineering teams can now be recreated or surpassed by general-purpose AI models within months. Once copying becomes essentially free, the feature itself stops being valuable. What remains valuable are the things AI cannot easily copy:

• Your proprietary data
• Customer relationships
• Distribution
• Trust
• Deep integration into customer workflows

When the Product Becomes a Commodity

Chegg's business was built around providing answers to homework questions. The moment conversational AI could instantly answer nearly any question, students no longer needed a subscription to a platform that answered only some of them. A product refined over fifteen years became commoditized in roughly six months. The market reflected that reality with remarkable speed.

• Peak (February 2021): $113 per share
• Today: Approximately $0.82 per share The market wasn't simply discounting Chegg. It was declaring that the company's core source of value had effectively disappeared.

Chegg Wasn't the Exception

Initially, many observers assumed education was uniquely vulnerable. It wasn't. Chegg simply happened to fall first. Since then, the same pattern has emerged in three distinct forms.

1. AI Replaces Products

This is the most obvious form. Products whose primary function is generating, retrieving, or explaining information are increasingly competing with general-purpose AI models that perform the same tasks at near-zero marginal cost. Another powerful example is Stack Overflow. For more than fifteen years, it served as the internet's primary destination for software developers seeking technical answers. At its peak:

• More than 200,000 questions were asked each month. Today:
• Roughly 3,000 questions are submitted monthly. Question volume has fallen back to levels last seen in 2008. Importantly, developers didn't abandon Stack Overflow because they disliked it. They simply stopped needing it. There is also a striking irony. The AI models replacing Stack Overflow largely learned their programming knowledge by training on Stack Overflow's own content. In many ways, it trained its own replacement—one accepted answer at a time.

2. AI Replaces Workflows

The second form is more subtle. The software product survives. The workflow around it doesn't. Industries including:

• Software development
• Customer support
• Legal research
• Marketing
• Recruiting are becoming dramatically more productive through AI. Greater productivity is good for customers. But if your business depends on customers needing more people, more billable hours, or more specialized software, increased efficiency becomes an existential threat. Customers don't necessarily leave. They simply require less of what you're selling.

3. AI Reallocates Capital

This is perhaps the least visible and potentially the most dangerous form. Companies don't need to lose customers to be affected. They only need to lose budget priority. Today, nearly every executive team is asking the same question:

"What's our AI strategy?" Answering that question requires investment. Those investments rarely come from new budgets. Instead, they come from existing ones. That means:

• Software upgrades are delayed.
• Consulting engagements are postponed.
• Infrastructure projects are pushed back.
• Existing contracts become harder to renew. The impact may not appear immediately in customer churn. But it appears in spending decisions.

IBM: A Recent Example

A striking illustration occurred with IBM. In early June, IBM reached an all-time stock high of approximately $329, fueled by optimism surrounding AI. Just weeks later, the company experienced the largest single-day decline in its 115-year history. Approximately $67 billion in market value disappeared in a single trading session. The reason wasn't that AI replaced IBM's products. According to company leadership, enterprise customers shifted spending away from traditional software and infrastructure toward AI-related servers, storage, and chips. IBM didn't lose customers. It lost priority.

Three Different Symptoms. One Underlying Cause.

At first glance, these appear to be unrelated stories.

• Chegg lost its product.
• Stack Overflow lost user activity.
• Service firms are losing billable hours.
• IBM lost budget allocation. But they're all manifestations of the same underlying force. In every case, something companies previously charged for became commoditized faster than they could create a sustainable defense around it. Sometimes that "something" is:
• A feature
• A workflow
• A budget allocation
• A category itself

The Question Every Executive Should Be Asking

Many leaders continue asking:

"Will AI disrupt my industry?" That is no longer the useful question. The answer is increasingly yes for nearly every industry. A far more valuable question is: Which assumption is my business built upon that AI is about to commoditize? Every company has one. For Chegg, it was the assumption that answering questions was difficult. Tomorrow, it may be another industry's defining advantage.

Final Thought

Chegg wasn't simply an isolated business failure. It was the first domino. The remaining dominoes are already falling. They are simply falling at different speeds, in different industries, and often without the courtesy of a press release.