Is Scaled Content Hurting Your Rankings? Google’s Warning Explained

Scaled content is under scrutiny in Google’s latest updates. This post breaks down what scaled content means today, how Google is evaluating it, and what content teams need to do now.

What is Scaled Content and What’s the Problem?

As SEO priorities shift again in 2025, “scaled content” is resurfacing as a critical issue for marketers and site owners. Once associated with black-hat tactics from the early 2000s, the concept has evolved, but the risks haven’t gone away.

Today’s scaled content often meets technical SEO requirements while failing to deliver actual value to users. The real concern isn’t the production process; it’s the lack of substance or usefulness for the audience.

While tools like AI and content automation can accelerate publishing, the temptation to generate dozens or hundreds of similar pages can result in a bloated content library without rigorous editorial review, minimal differentiation, and weak relevance to search intent. That’s precisely what Google is cracking down on.

Defining Scaled Content in 2025

Marketers no longer define scaled content by keyword stuffing or spun articles.

We typically define it as follows:

Bulk output using automation or AI: Pages are generated in bulk with minimal human input, often using templates and variable swapping (e.g., city names, product SKUs).
Limited originality: These pages feature nearly identical phrasing, structure, and information, often rendering them indistinguishable from one another, except for minor variations in keywords.
Superficial coverage of topics: Rather than providing helpful, comprehensive answers, scaled content often glosses over subjects with shallow explanations or filler phrases.
Inconsistent alignment with search intent: Content that fails to fully address the user’s question or need won’t perform well. Even with relevant keywords, it may still be treated as low-quality at scale.
Lack of editorial oversight: These pages often bypass QA, fact-checking, and strategic review, resulting in them rarely adding real value.

Modern scaled content can take several forms:

Location pages: Nearly identical service pages for every city or ZIP code, differing only by the name of the place.
AI-generated blog posts: Dozens of thin articles generated to rank for long-tail keywords with no added commentary, research, or insight.
Product pages: E-commerce descriptions that are copied, lightly rewritten, or cloned across multiple product listings.
Programmatic SEO: Automated page creation based on combinations of keywords, filters, or data points, with limited or no human refinement.

The issue isn’t automation itself. It’s when automation replaces human judgment, originality, and intent. As Google’s ranking systems become more sophisticated, they now evaluate signals of quality and usefulness across sets of content, rather than just individual pages.

Karen Lewis, a digital marketing strategist and agency founder, underscored this shift in a LinkedIn post discussing the January 2025 Quality Rater Guidelines update.

“If you’re using AI to support content,” she wrote, “make sure it’s human-reviewed, adds new insight, and truly benefits your audience.”

Her advice reflects Google’s evolving expectations: originality and editorial effort matter just as much, if not more, than technical correctness.

Google’s Historical Stance

Google has always taken a firm position against content created solely to manipulate search rankings. The company’s approach to scaled content has changed alongside the tools used to create it:

2000s: Keyword stuffing and spun articles

Early search engines were gamed using mass-produced pages stuffed with keywords or created using article spinning tools. Google’s early algorithm updates, like Panda, targeted these tactics directly.

2010s: Template abuse and thin affiliate pages

As content farms and low-value affiliate sites grew, Google began cracking down on pages that offered no added value or unique perspective. The bar for originality rose.

2020s: The rise of AI-generated content at scale

With the introduction of LLMs, the volume of auto-generated content exploded. While some AI-assisted content is valuable, Google explicitly warns that large volumes of unoriginal or unhelpful pages, even if grammatically correct, may be treated as spam.

When Google Search Liaison Danny Sullivan said, “It doesn’t matter how it’s created … it’s going to be an issue,” he made Google’s position clear. Intent and usefulness matter more than the production method.

Key takeaways from Google’s guidance:

Focus on usefulness: Pages must deliver value, not just match keywords.
Intent matters: Matching the user’s need is more important than covering every variation of a phrase.
Volume raises scrutiny: A few similar pages may fly under the radar, but dozens or hundreds? That’s when scaled content becomes a problem.
Automation ≠ exemption: AI and programmatic tools aren’t an excuse for skipping editorial oversight.

If your content strategy prioritizes quantity over quality, you risk compromising visibility and credibility. Scaled content, when done poorly, dilutes your site’s authority, and Google is watching.

👉 Check out this post for a strategic foundation on aligning content creation with your business goals: Why Your Company Needs a Content Strategy.

How Scaled Content is Flagged in Google’s Quality Guidelines

Google’s Search Quality Evaluator Guidelines (SQEG), last updated in 2024 and revised again in 2025, have sharpened their focus on identifying and penalizing scaled content. These updates reflect growing concerns around mass-produced pages, especially those created with minimal oversight using AI or automated tools.

The guidelines now provide more explicit signals for what constitutes low-quality content. Importantly, the judgment isn’t limited to whether a page contains factual errors. Instead, evaluators must consider whether the content shows signs of real effort, originality, or skill. Without these elements, even technically correct content may be rated poorly.

Quality is now defined as more than accuracy. It’s about whether the content reflects real human thought, customization, and relevance to the user’s intent.

New Criteria for the ‘Lowest’ Quality Rating

The latest guidelines introduce stricter instructions for assigning the “lowest” quality rating to web pages.

This rating is now applied to pages that show:

No evidence of original thinking: Content that echoes existing web pages without adding new insight, perspective, or data.
No signs of effort or editorial input: Pages that appear auto-generated or copied from templates with superficial rewrites.
No skill or subject matter expertise: Articles written without depth, nuance, or a clear command of the topic are often recognizable by their vague language and generic phrasing.
Formulaic or repetitive structure: Pages that follow the same pattern or layout across dozens or hundreds of URLs, with only minor keyword swaps or placeholders changed.

Here’s what may trigger the lowest rating even if the page seems helpful at a glance:

A city-specific service page that mirrors dozens of others except for the location name.
A product roundup post where all entries are pulled directly from manufacturer descriptions.
An AI-generated blog post that lacks citations, examples, or context.
A FAQ page with generic answers repurposed from other sites.

Nick Jordan, founder of ContentDistribution.com, put it bluntly in a LinkedIn post. He explains, “Engagement-first content wins. Not your 4,000-word AI-regurgitated keyword-stuffed turkey blog that got a Surfer score of 89.”

His advice aligns with Google’s updated stance: if you create content for machines instead of people, Google may ignore or even deindex it. Under the latest Quality Rater Guidelines, originality, effort, and usefulness are non-negotiable.

This shift means that even well-structured or grammatically correct content may fail Google’s evaluation if it lacks authenticity or depth.

What This Means for SEOs and Publishers

For SEOs, content marketers, and publishers, the message from Google is unambiguous: Publishing at scale without originality is a liability.

Relying too heavily on AI, templates, or repetitive formats, without investing in research, customization, or expert input, will likely result in declining rankings. Google trains its evaluators to look for signs of human creativity, expertise, and editorial refinement.

To meet modern expectations and maintain visibility in search, content teams should:

Shift from quantity to quality

Stop trying to rank with hundreds of near-identical pages.
Focus on fewer, high-effort pages that address search intent more deeply.

Prioritize human touch and expertise

Include real insights, quotes, or first-hand analysis wherever possible.
Bring in subject matter experts to fact-check or contribute to the content.

Make each page distinct

Avoid overusing templates without customization.
Ensure that metadata, structure, tone, and examples vary meaningfully between pages.

Demonstrate topical authority

Build content clusters with internal links that reinforce expertise.
Use supporting visuals, charts, or original research to increase depth and usefulness.

Conduct internal reviews before publishing

Create a checklist that includes originality, clarity, and usefulness.
Have editors or strategists assess whether the content would pass a manual quality review.

In essence, if your page doesn’t show evidence of care, expertise, and customization, Google may assume you built it for bots, not people.

👉 Check out this post to learn how the right writers can help you avoid the low-quality flags outlined in Google’s Quality Guidelines: What Every Content Marketer Needs to Know About Hiring Freelance Writers – nDash.com.

Does It Matter Who Creates Scaled Content?

When it comes to scaled content, Google doesn’t care if it was created by a human writer, an AI tool, or a team using both. What matters is whether the content is genuinely helpful, well-crafted, and created with the user in mind. Google’s search guidance focuses on outcomes rather than the methods used to create the content. When a page shows little effort or originality, Google labels it low quality.

This approach reflects a broader shift in Google’s search philosophy. Rather than focusing solely on authorship, the emphasis is now on the intent behind content creation and the value it delivers to the reader.

That’s why Google’s policies on spam and search manipulation apply equally to:

AI-generated pages that mimic helpful content without real substance
Human-written pages produced at high volume using formulaic or duplicated structures
Hybrid content that combines AI drafts with minimal human oversight

Whether the tool is a large language model or a manual content spinner, the issue lies in scale without quality.

Sullivan’s Throwback to 2005 Tactics

Sullivan noted that scaled content isn’t a new issue. Long before ChatGPT or generative AI, marketers were employing human-driven tactics to produce massive volumes of near-duplicate content, designed to manipulate search engine rankings.

Back in 2005, scaled content often looked like this:

Article spinning: Manually rewriting the same article dozens of times using synonyms and slight phrasing changes
Bulk production of doorway pages: Pages created for specific keyword combinations or local searches that funneled users to the same landing page
Template-based content farms: Websites filled with thin, surface-level articles covering high-volume keywords with no original reporting or analysis
Affiliate pages with duplicate copy: E-commerce or referral pages using vendor-supplied descriptions across hundreds of listings

Google addressed these tactics early on through updates like Panda and Penguin, establishing the basis for modern quality standards.

“The problem isn’t new,” Sullivan noted. “The speed and tools may have changed, but if the goal is to flood search with low-effort content, it’s still spam.”

AI Doesn’t Get a Pass

With the rise of generative AI, some content creators assumed that automation might offer a loophole. But Google makes its position clear: it holds AI-generated content to the same standard as all other content.

If the content is:

Thin or repetitive: Lacking depth, original thought, or differentiated perspective
Over-optimized or keyword-stuffed: Designed to target search terms without addressing user needs
Lacking human oversight: Published without fact-checking, editing, or customization
Duplicated across variations: Reused across different pages, regions, or topics with only minor tweaks

…it’s considered low-quality content, no matter how “smart” the AI appears.

To avoid triggering quality penalties, marketers using AI must:

Use AI as a starting point, not an endpoint: Treat AI-generated drafts as rough ideas that require human refinement.
Add editorial value: Include insights, examples, quotes, or experiences that only a human can provide.
Customize deeply: Avoid producing “copy-paste” pages. Each piece should have a clear target audience and a clear purpose.
Validate accuracy: Cross-check facts, statistics, and references to prevent hallucinations or misinformation.

Kenny Lee, an SEO strategist for brands like AWS and HubSpot, learned this firsthand. In a LinkedIn post, he shared how his affiliate site, once ranking for high-volume supplement keywords, lost visibility after Google began emphasizing E-A-T.

“An engineer recommending healthcare products isn’t exactly EEAT stuff,” he wrote, reflecting on how even well-optimized content fails when it lacks subject matter credibility.

His conclusion?

“Good SEO goes beyond creating for the machine.” Whether humans, AI, or a combination of both created the content, it must meet Google’s standards for trust, intent, and expertise to succeed.

The takeaway is simple: AI is a tool, not a shortcut. If you use it to cut corners on quality or scale low-effort pages, Google will treat the results accordingly.

👉 Check out this post to see how brands blend AI and human oversight without sacrificing quality: Human Touch in an AI-Driven World: How Content Services Help Brands Balance Automation and Personalization – nDash.com.

When Scaled Content Adds Value

Scaled content often gets a bad rap, but not all of it is problematic. Google has made it clear that how you produce content matters less than why and for whom you create it. When scaled content serves a clear purpose, improving usability, surfacing insights, or reducing cognitive load, it can enhance the user experience rather than degrade it.

The key distinction lies in intent and execution. If content is mass-produced purely to manipulate rankings or claim digital real estate, it’s likely to get flagged. But when you create it to simplify, summarize, or enrich the user’s journey, even large-scale content can meet Google’s quality standards.

Scaling value is acceptable; scaling noise isn’t.

The Amazon Review Summaries Example

One of the most compelling examples of scaled content done right comes from Amazon’s AI-generated product review summaries. Sullivan cited this use case to highlight how automation can enhance, not exploit, the search experience.

Here’s why Amazon’s approach works:

Synthesizes large volumes of data: Rather than generating new content from scratch, Amazon’s system distills insights from thousands of verified user reviews.
Improves decision-making: These summaries help shoppers quickly grasp the common pros and cons of products without having to read hundreds of individual posts.
Avoids SEO manipulation: The summaries aren’t there to inflate visibility or create duplicate pages; they live within the product listing and serve a clear UX function.
Contextual and honest: The source material (user reviews) reflects real feedback, which is aggregated transparently and without spin.

The content qualifies as scaled, but it draws from original data, delivers genuine utility, and avoids trying to outrank existing search results. It’s an example of AI applied for comprehension, not for clicks.

The Difference: Additive vs. Redundant Content

To determine whether your scaled content is a benefit or a liability, ask a simple but powerful question:

Is this adding something new, or just more of the same?

Additive content is:

Insightful: Offers expert commentary, analysis, or explanation beyond what’s already indexed.
Efficient: Distills complex or scattered data into an easier-to-understand format.
User-centric: Solves a problem, answers a question, or helps someone take action.
Data-driven: Surfaces patterns or conclusions from original research or large datasets.
Context-aware: Adapts the message to specific audiences, formats, or intents.

Examples include:

Industry trend summaries that compare five years of data across regions.
FAQ sections generated from support ticket analysis and customer input.
Dynamic dashboards or product selectors that adapt based on user goals.
Regional landing pages that reflect distinct regulations, culture, or behavior.
Long-form explainers broken into modules for different industries or job roles.

Redundant content is:

Repetitive: Rewrites or paraphrases what’s already ranking, with no added substance.
Template-heavy: Mass-produced with fill-in-the-blank copy and little human input.
Keyword-centric: Prioritizes variations of a phrase over depth of information.
Detached: Lacks understanding of audience intent or user experience.
Cluttered: Adds noise to the SERP without guiding users toward a solution.

Examples include:

Dozens of city pages with duplicate content except for the location name.
AI-generated listicles that repeat advice from top-ranking blogs.
Programmatic pages built from keyword matrices with minimal editing.

To stay on the right side of Google’s guidelines, content marketers should evaluate scale not as a goal, but as a means of delivery.

👉 Check out this post to see how brands scale content with value, not volume, by tapping flexible freelance teams: The Rise of the Fractional Content Team: Why Freelancer Writers Are a Strategic Advantage – nDash.com.

Common Misconceptions About “Quality” AI Content

As AI tools become more advanced, many marketers and SEOs have leveraged them for content generation, often with the belief that as long as the output is grammatically correct and keyword-optimized, it is of “quality” and therefore safe. But Google’s evolving stance tells a different story.

The misconception stems from a surface-level understanding of what “quality” means in the context of search. Google’s guidelines make it clear: a piece of content can look polished, contain accurate information, and still be considered low-quality or spammy if it lacks originality, genuine user value, or editorial oversight.

“Quality” is Subjective and Misused

One of the most common defenses of AI-generated content is the phrase: “It’s fine as long as it’s quality.” But as Sullivan has pointed out, that statement often reflects a misunderstanding of how Google evaluates content.

Here’s why that mindset is flawed:

Polish ≠ Purpose: AI tools can now produce content that reads smoothly and mimics natural human tone. But clarity alone doesn’t indicate value. If you create the piece solely to target keywords, it remains vulnerable to penalties.
Surface-level helpfulness isn’t enough: A blog post that restates known facts or paraphrases existing top-ranking pages may sound informative, but it lacks depth and originality. Still, if it doesn’t offer anything new or personalized, Google may classify it as redundant.
Mass production raises red flags: Even if each page appears “helpful,” the sheer volume of similar, templated posts can signal scaled manipulation.

As Ed Malinowski noted in a LinkedIn post, “AI browsers aren’t disrupting SEO; they’re exposing it.” He explains that tools like ChatGPT, Perplexity, and Claude are filtering content not by its keyword rankings, but by its relevance, credibility, and structure.

In his words, the content that stands out today is “deeply authoritative… backed by credentials and data,” and offers “original and insightful” perspectives. AI browsers and Google increasingly ignore pages that repeat top results, lack structure, or offer little value.

This shift underscores a growing consensus: surface-level quality isn’t enough. Content must be genuinely helpful, well-structured, and tied to subject-matter expertise to stand out from the noise.

Indicators that “quality” may be misapplied:

The content lacks expert input, original research, or lived experience.
It mirrors existing SERP content in structure, phrasing, and conclusions.
It’s published in bulk with minimal human review or customization.
It doesn’t fully address the nuances of the topic or search intent.

Define Tests of Legitimacy

Google has introduced simple, intent-based filters for evaluating the content, whether it’s human-written, AI-assisted, or a combination of both. These questions help reveal whether the author intended to inform users or to manipulate rankings.

Ask yourself these two key questions

Was this content primarily created to rank in search engines?
- Are keyword variations driving the structure, rather than user needs?
- Is the goal traffic generation, not solving a problem or answering a question?
- Would the content still exist if search traffic didn’t matter?
Does it genuinely help users or offer something new?
- Does it add a unique insight, perspective, or layer of context?
- Are you offering first-hand experience, original analysis, or case-specific value?
- Is there a clear reason for this content to exist beyond SEO?

If the answer leans toward search performance over usefulness, even high-effort, well-written AI content may still be penalized.

Additional litmus tests for content legitimacy

Is it written with a real audience in mind? Not just Google’s bots, but actual users with specific questions or pain points.
Would a human editor or expert endorse it? Does it meet the standards of accuracy, nuance, and completeness?
Can it earn backlinks on its own merit? Would someone link to this as a reference, even if they didn’t know it came from AI?
Does it meet EEAT expectations? Does it demonstrate Experience, Expertise, Authoritativeness, and Trustworthiness?

Chris Essey summed up this shift on LinkedIn when he wrote, “It’s no longer enough to be optimized. You need to be believable. You need to be human.”

He emphasizes that AI search engines are moving beyond keyword matching. They now synthesize content and prioritize credibility using real-world signals like author credentials, citations, transparency, and human review. As he puts it, E-E-A-T isn’t optional anymore. It’s foundational.

Legitimate content, regardless of the tools used to create it, is rooted in user-first principles. That involves answering fundamental questions, solving real problems, and offering genuine insights. AI can assist with content development, but it can’t replace the strategic thinking behind effective content.

👉 Check out this post for tips on avoiding misleading “quality” shortcuts when using AI: Content Marketing Strategies: Prioritizing Quality Over Quantity in the AI Age – nDash.com.

Google’s Two‑Pronged Testing Framework

In response to growing confusion around what qualifies as helpful, high-quality content, Google has distilled its evaluation guidance into two deceptively simple questions. This framework shifts the conversation away from how content is generated and focuses instead on the intent behind it and the value it provides.

Rather than assessing content purely by surface-level quality, like grammar, formatting, or keyword usage, Google wants creators to ask:

Why was this content created?
Does it contribute anything original to the web?

If the answers to these two questions reveal search-driven motives without user value, the content is at risk. Google may still label a technically sound, well-written page as low quality.

Traffic‑motivated content

The first part of Google’s framework asks: Was the primary intent of this content to gain search traffic?

If the goal is to rank rather than to help, that’s a red flag, especially if the content is scaled across pages, keywords, or variations. Sullivan has reiterated that content created for search engines, rather than users, even if it appears helpful, is likely to be penalized.

Melanie Fernandes pointed out in a LinkedIn post that many new websites are struggling to get indexed, not solely due to technical issues, but because they’re publishing what she calls “spammy low-quality AI-generated content.”

She explains that Google’s crawl budget is tighter than ever, and bots are prioritizing “clear semantically correlated content that makes sense topically.” Her advice is simple yet sharp: ditch the vague filler, like “in today’s world,” and instead create content that focuses entirely on the buyer’s needs and questions. It’s a direct reflection of Google’s two-pronged framework, intent and originality matter more than ever.

Warning signs your content is traffic-motivated:

You chose the structure and topic based solely on keyword volume, rather than user need.
Writers created multiple pages targeting slight keyword variations, such as “best CRM tools for law firms” and “CRM software for attorneys,” with little difference.
The page provides generic answers that echo top-ranking results without advancing the conversation.
There’s no clear call to action or next step for the user, only ads or affiliate links.
The content wouldn’t exist (or wouldn’t be as long) if it weren’t intended to rank.

What to do instead:

Begin with user intent: What is the reader trying to solve, decide, or understand?
Focus on search discovery rather than search manipulation. Aim to be helpful even if it means not targeting a high-volume keyword.
Treat SEO as a distribution channel, not the end goal. Let strategy guide structure, not the other way around.

Originality benchmark

The second question Google asks is: Does the content offer something new or insightful?

This test gets to the heart of what separates valuable content from filler. As AI-generated content becomes increasingly prevalent and many tools are trained on overlapping datasets, the risk of publishing redundant or derivative material increases. Without original thinking or unique data, content can quickly become stale, even if it’s accurate.

Nina Maisuradze, Lead SEO Project Manager at GoldenWeb, pushed back on the idea that optimizing for LLMs requires a brand-new playbook. In a LinkedIn post, she wrote, “Clarity and structure have never gone out of style.”

She points out that tips like summarizing content, answering questions directly, and demonstrating author credibility have been SEO best practices for over a decade.

Her message?

The smartest approach to standing out in AI-driven search isn’t chasing new acronyms, it’s doubling down on foundational, user-first content strategy.

Characteristics of truly original content:

First-hand experience or expertise: Drawn from your team’s knowledge, trials, or customer interactions.
New data or perspectives: Includes survey results, industry benchmarking, or analysis not available elsewhere.
Unique framing or explanations: Introduces metaphors, frameworks, or workflows that help users grasp complex topics more easily.
Tailored insights: Applies a known idea to a specific audience, niche, or context (e.g., “AI in content strategy for legal tech companies”).

Common signs your content lacks originality:

It repeats commonly available advice without citing sources or adding insight.
It uses the same examples, comparisons, or templates found across other top-ranking pages.
It was generated entirely by AI and only lightly edited, with no unique research, voice, or POV.
It includes filler content (“As we all know,” “It’s important to stay competitive”) instead of substantive value.

To meet Google’s standards, originality doesn’t mean reinventing the wheel, but it does require a meaningful contribution. Your content should do more than summarize; it should clarify, challenge, or contribute to the broader conversation.

👉 Check out this post for practical guidance on aligning your testing strategy with Google’s emphasis on quality and intent: Best Practices for Modern Marketers: Content Creation and Navigating Google’s Ranking Factors – nDash.com.

Practical Takeaways for Content Strategy

Google’s guidance isn’t just a warning; it’s a call to elevate content practices. Brands that align their creation with user value, originality, and expertise will remain competitive, even as search standards become tighter.

For marketing teams and SEO professionals, now is the time to realign with principles that prioritize depth, usefulness, and authenticity. Below are two practical steps to help future-proof your content.

Audit Content Motivations

Before planning your next batch of content, step back and examine its purpose. If the answer revolves around keyword rankings, traffic growth, or volume targets without a clear link to user value, it’s time to reassess.

Ask yourself:

What problem is this content solving?
What question is the user asking at this stage of their journey?
Would we still create this if organic search didn’t exist?

Audit your current content by looking for red flags:

Pages created solely to match keyword variations, with minimal user differentiation.
Blog posts that summarize existing information without adding new angles or examples.
Landing pages with generic copy that doesn’t map to a user’s need or decision point.

How to realign with purpose:

Map every topic to a user goal: Whether it’s learning something new, making a purchase decision, or troubleshooting an issue, content should have a clear purpose.
Match content type to intent: Instead of defaulting to blog posts, consider formats like:
- Step-by-step guides for how-to queries
- Short videos or infographics for visual learners
- Comparison tables or calculators for decision-stage content
Create fewer, better pages: Consolidate overlapping content and build deeper resources that solve entire problems, not just fragments of them.

Jackson Dunagan, founder of Bright Vessel, emphasized this shift in mindset in a LinkedIn post. He wrote, “Google wants expertise. Write to solve problems, not to hit word counts. One great post beats five forgettable ones.”

His advice reinforces the purpose of this audit, not to publish more, but to ensure every page earns its place by delivering real value.

Inject Expertise and Originality

The fastest way to stand out in an AI-saturated web is to be more human. That means showcasing experience, voice, and insight in ways that AI or templated strategies can’t replicate.

Add human touches to improve both quality and trust:

Subject Matter Expert (SME) quotes: Include firsthand commentary from product managers, engineers, support teams, or clients to provide context that no language model can generate.
Proprietary data or research: Share trends from internal surveys, customer usage reports, or industry analysis unique to your brand.
Real-world examples and use cases: Show how your audience can apply a concept, not just what the idea is.
Personalized commentary: Offer editorial perspective, experience-based recommendations, or insights gained through trial and error.

Kristy DelMuto, Head of Brand and Marketing at Mainsail Partners, echoed this approach in a LinkedIn post reflecting on how portfolio marketers are responding to the changes in AI search.

“The best content starts with your team’s insights, not a prompt,” she wrote. While generative AI supports content at scale, she stressed a key point. The strongest strategies still come from individuals with a deep understanding of the brand and its audience.

Avoid content that:

Relies entirely on AI with no additional editorial layer
Repeats common SEO advice or trends without citation or nuance
Feels interchangeable with dozens of other top-ranking results

A few originality prompts for your next content piece:

What’s our internal POV on this issue that competitors haven’t said?
What do our clients and team members frequently ask us about?
What failed experiment or lesson learned could others benefit from?
How can we make this content actionable, not just descriptive?

The brands that thrive under Google’s new scrutiny will be the ones that sound less like a search engine and more like a trusted guide.

👉 Check out this post for guidance on building scalable, quality-first content workflows: Scaling Content Strategies: Lessons for 2025 – nDash.com.

Why Scaled Content Needs a Strategy Reset

Google’s message is clear: mass-producing content without purpose or originality is no longer sustainable. To stay visible in search, brands must rethink their approach, shifting from volume-driven output to value-led strategies that are grounded in expertise, user intent, and relevance. Reassess your motivations, elevate content standards, and use AI with intention, not automation.