Commentary sections across the web are filling up with content that reads fine at first glance but feels slightly off. The arguments are coherent, the writing is smooth, but there’s something missing—personality, genuine insight, the sense that a human with actual experiences and perspectives wrote it.

Sometimes that feeling is right. More commentary than you’d think is now AI-assisted or AI-generated. Not always disclosed, not always obvious, but increasingly common. This is changing the landscape of opinion writing in ways we’re just beginning to understand.

The Use Cases

Let’s be clear about what’s actually happening. Full AI-written commentary published under human bylines is still relatively rare and usually easy to spot. More common is AI assistance: tools that help generate outlines, suggest arguments, polish drafts, or expand brief thoughts into full pieces.

Some commentators use AI to beat writer’s block, generating rough drafts they then heavily revise. Some use it to speed up production, outputting more pieces than they could write from scratch. Some use it to generate variations on a theme across multiple publications with minimal additional work.

Content mills and low-end publications increasingly use AI to generate filler commentary at scale. Generic takes on trending topics, produced for pennies, published under fake or borrowed bylines. This stuff is usually terrible, but it’s cheap and fills space while generating ad impressions.

Then there are experiments with fully AI commentators—chatbots or LLM-based systems producing opinion content. These are usually labeled as such, but not always. Some publications are testing whether readers can tell the difference or whether they care.

Across all these uses, AI is becoming part of the commentary production process in ways that weren’t possible even two years ago. Organizations working in custom AI development see the technology capabilities advancing faster than guidelines about appropriate use.

What AI Is Good At

For generating commentary, AI is surprisingly decent at certain tasks. It can produce grammatically correct prose at arbitrary length. It can synthesize common arguments on any mainstream topic. It can mimic stylistic patterns and maintain consistent tone across a piece.

It’s particularly good at producing content that sounds authoritative without saying anything particularly insightful. That’s a useful skill in low-engagement opinion writing—pieces that exist primarily to fill space and generate clicks, not to advance thinking or provide unique perspectives.

AI can also rapidly generate multiple variations on a theme, which is valuable for publications that need fresh takes on breaking news or trending topics. Instead of one human commentator taking hours to write one piece, AI can generate five different angles in minutes.

For editors, AI tools can assist with headline writing, social media promotion, and identifying which angles on a story might perform well. These behind-the-scenes uses arguably improve content delivery even when the core writing is still human.

What AI Can’t Do

The limitations are significant, though. AI-generated commentary lacks genuine perspective, lived experience, and original insight. It can only recombine and synthesize patterns from its training data. It can’t have a new thought or bring unique expertise to an analysis.

AI commentary tends to be safe, generic, and bland. It gravitates toward consensus positions and commonly argued points. It doesn’t take risks, challenge assumptions, or provide the kind of contrarian or deeply personal perspective that makes commentary valuable.

It also can’t check its own facts or assess source credibility. AI will confidently assert false claims if they appear commonly in its training data. Without human verification, AI commentary can spread misinformation packaged in confident prose.

And AI lacks cultural context, nuance, and the ability to understand when a technically correct statement will be read as offensive or tone-deaf. Human commentators with lived experience navigate these subtleties. AI just patterns-matches and hopes.

The Quality Problem

The flood of AI-assisted and AI-generated commentary is degrading the overall quality of opinion content online. Not because every AI-assisted piece is bad, but because the ease of production encourages volume over quality.

Why spend three hours crafting a thoughtful, well-argued commentary when you can spend 30 minutes revising an AI draft that’s “good enough”? Why develop a unique perspective when AI can generate a passable generic take that’ll get clicks?

The economics reward speed and volume. AI enables both. So we’re getting more commentary that’s adequate but forgettable, that restates common positions without adding insight, that exists primarily to capture search traffic or social engagement rather than to advance understanding.

This crowds out better work. When feeds and search results fill with AI-generated content, there’s less room for human commentary that’s actually worth reading. The discovery problem gets worse—finding the signal in the noise becomes harder when the noise increases exponentially.

The Authenticity Question

Commentary has always relied on an implicit contract: a human with some expertise or experience is sharing their genuine perspective. You might disagree, but you’re engaging with actual human thought.

AI-generated commentary breaks that contract. You’re not getting someone’s genuine perspective—you’re getting a statistical prediction of what text should follow given certain prompts. That’s fundamentally different, even if the output reads similarly.

Some argue this doesn’t matter. If the commentary is useful, who cares how it was produced? But I think it does matter. Part of what makes commentary valuable is the human element—knowing you’re engaging with someone’s actual thinking, shaped by their experiences and values.

When that element disappears or becomes uncertain, the whole transaction feels hollow. You’re not having a human conversation anymore, even mediated through text. You’re consuming content optimized to pattern-match your expectations.

The Disclosure Problem

Some publishers are transparent about AI use. They label AI-generated content clearly or disclose when human writers use AI assistance. This is responsible but uncommon.

Most AI-assisted commentary isn’t disclosed. Writers use AI tools as part of their process without mentioning it. Publications generate content with heavy AI involvement without labeling it. Readers have no way to know what they’re getting.

This creates trust problems. When readers discover commentary they trusted was AI-generated, they feel deceived. The lack of disclosure standards means there’s no way to verify what’s human-written and what isn’t short of algorithmic detection (which has its own problems).

We probably need disclosure standards similar to what advertising has. If your content is AI-generated or substantially AI-assisted, that should be disclosed. But there’s no enforcement mechanism and limited industry consensus on standards.

What This Means for Readers

If you consume commentary online, you’re already reading AI-assisted or AI-generated content regularly, whether you know it or not. Some of it is fine. Some of it is misleading or low-quality. You mostly can’t tell which is which.

This makes evaluating commentary harder. You can’t just assess the arguments anymore—you have to consider whether the piece represents genuine human thought or optimized content generation. That’s exhausting and probably unsustainable.

The practical advice is to focus on commentators you know and trust, where you have confidence the work is genuinely theirs. Be skeptical of generic takes from unknown writers. Look for specific details, personal experiences, and insights that suggest human authorship.

But even that isn’t foolproof. As AI gets better, the tells get subtler. Eventually we might not be able to reliably distinguish AI from human commentary without technological assistance.

The Future Is Messy

AI will become more prevalent in commentary production, not less. The tools are getting better, the economic incentives are strong, and the barriers to use are low. We’re heading toward a media environment where significant portions of opinion content are AI-generated.

This might not be entirely bad. If AI can handle generic commentary, maybe that frees humans to focus on distinctive perspective and original insight. The best commentary might become more valuable precisely because it can’t be replicated by AI.

Or maybe we end up with a two-tier system: premium human commentary for paying subscribers, AI-generated filler for everyone else. That has troubling implications for democratic access to quality analysis and informed opinion.

Most likely, we’ll muddle through with unclear boundaries, inconsistent standards, and ongoing tension between efficiency and authenticity. AI will be part of commentary production, readers will be uncertain what they’re getting, and we’ll argue about what should be allowed and disclosed.

Same as everything else with AI, basically. The technology advances faster than our ability to establish norms around its use. We’ll figure it out eventually, or at least reach some uneasy equilibrium. Until then, welcome to the future of commentary: technically impressive, ethically messy, and impossible to put back in the box.