Contently: Your content is no longer competing only with other brands

Ajith Babu’s January 2026 piece in Contently’s Content Strategist blog starts from a premise that by now many writers recognize: the traditional SEO model is no longer the right frame for understanding content competition. The new competition is not for rankings on a search results page — it is for influence inside the AI-generated summaries that now sit above those rankings, and for persistence inside the training data and retrieval systems that power those summaries.

The shift Babu describes is structural. When a user asks a question and receives an AI-generated answer, the individual sources that informed that answer are typically invisible. Success in this environment means one of two things: your content earns a direct attribution — a link or citation that the AI surfaces alongside the answer — or your framing, terminology, and examples are absorbed into the AI’s output without naming you. Both outcomes require the same underlying quality: content that is distinctive enough to persist through the compression that AI summarization applies.

Babu identifies the content most at risk: safe, consensus-driven material that covers the same ground as dozens of other sources. When an AI model summarizes a category, it is drawing on a large set of similar inputs and producing a representative average. Content that replicates the consensus adds nothing to that average. It is indistinguishable from the aggregate and therefore invisible in the output.

What survives compression, by contrast, is content with structural advantages: specific data that cannot be generated from priors, clear conceptual models that give AI systems a distinctive way to frame a topic, and terminology that is specific enough to be identifiable across sources. The piece notes that “the riskiest move is to have no distinct voice at all” in an environment where dozens of sources collapse into a single response.

The strategic recommendations that follow from this analysis are practical for individual writers as well as editorial teams:

Original research and data travel further than synthesis. If a piece contains a number, finding, or claim that does not appear elsewhere, AI systems have reason to surface it directly.

Memorable framing persists. A concept with a clear name or model — one that readers and AI systems can apply to subsequent questions — has a longer shelf life than a well-written piece that covers familiar ground without introducing anything new.

Measuring success requires different metrics. Traffic and rankings reflect the old competition. Idea persistence — whether your framing shows up in subsequent AI responses and in how audiences discuss the topic — is a more relevant signal in this environment, even if it is harder to measure.

The article is particularly useful for writers and editors trying to understand why high-quality work is losing search visibility, and what the relevant response to that change looks like.