Every AI feature is the same feature

Open any SaaS product you use daily. There's a good chance it recently added an AI feature. Now open a second one, and a third. Notice anything? They all do the same thing: summarize, generate, suggest. When every product in your stack performs the same magic trick, it stops being magic. It becomes wallpaper. We're living through the great AI feature convergence, and almost nobody is talking about what it actually means.

The AI checkbox era

Somewhere around 2023, a shift happened. Investors started asking founders a single question: "Do you have AI?" And founders scrambled to answer yes. The result was predictable. According to a 2024 SaaS benchmarks report, 56% of companies launched or tested AI features within a single year. The primary driver wasn't solving user problems, it was revenue expansion. Customer demand came second. So every product got its sparkle icon. Notion AI, Slack AI, Google Workspace AI, Adobe Firefly, Canva Magic, Salesforce Einstein. The branding differs, but squint and they're remarkably similar: summarize this document, generate this draft, suggest the next step. The same OpenAI or Anthropic API underneath, the same prompt patterns, the same UX of a glowing text box that spits out something plausible. This is the AI checkbox era. Ship the feature, check the box, update the pitch deck.

The laundry detergent problem

Walk down the detergent aisle at any supermarket. You'll see dozens of bottles in different colors with different names, all promising roughly the same thing: clean clothes. The actual chemistry is nearly identical. Differentiation is branding, not ingredients. AI features in SaaS have the same problem. When every product wraps the same foundation model in a slightly different UI, the "AI-powered" label stops being a differentiator. It becomes table stakes, something users expect but don't get excited about. This matters more than most companies realize. As McKinsey has noted, AI functionalities are rapidly becoming table stakes in business software. The question is no longer whether you have AI, it's whether your AI actually changes anything about how the product works.

Feature fatigue is real

Users are noticing. Every app now has a sparkle icon, a "generate" button, or an AI assistant lurking in a sidebar. And increasingly, users are ignoring them. There's a growing sentiment that many AI features feel bolted on, solving problems that weren't really problems, or solving them in generic ways that don't fit specific workflows. When every tool summarizes, but none of them summarize in a way that actually matches how you think or work, the feature becomes noise. This is AI feature fatigue: not a rejection of AI itself, but exhaustion from shallow implementations that all feel the same.

Shallow AI vs. deep AI

The distinction that matters isn't between "has AI" and "doesn't have AI." It's between shallow integration and deep integration. Shallow AI is a feature. It's a sidebar, a button, an add-on. The underlying product architecture, workflow logic, and user experience remain unchanged. AI arrived as a bolt-on, built for a different era. Forbes recently described these as "reach extenders," tools that solve a real problem in the moment but don't fundamentally change what you're capable of doing. Deep AI is a product. The AI doesn't just assist the workflow, it reshapes it. Think about Cursor's code completion, which doesn't just suggest lines of code but fundamentally changes how developers navigate and write software. Or GitHub Copilot's pull request summaries, which are deeply woven into the development workflow rather than sitting in a generic chat window. The difference is structural. Shallow AI asks: "How can we add AI to what we already built?" Deep AI asks: "What would this product look like if AI were the foundation?" Most companies shipped the shallow version. That was the rational choice, it was faster, cheaper, and satisfied the investor checkbox. But it's not where lasting value lives.

What actually wins

The AI features that users love share a common trait: they make the core workflow faster without requiring the user to leave it. They're invisible in the best way, reducing friction rather than adding a new thing to learn. Here's a useful litmus test: does the AI feature make the thing you were already doing faster and better? Or is it a sidebar you open once, poke around in, and never return to? The products getting this right tend to have a few things in common:

The real question for builders

If you're building a SaaS product, the question isn't whether to add AI. That ship has sailed. The question is whether your AI feature is genuinely different from every other AI feature, or whether you're just adding another sparkle icon to the pile. The products that will win this era aren't the ones that shipped AI first. They're the ones that figured out where AI actually belongs in their specific workflow, and built it so deeply that users can't imagine going back. Everyone else is selling laundry detergent.

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