The Future of AI-Driven Linkbuilding: What Changes and What Stays the Same

Why This Debate Matters Now

Throughout 2024 and 2025, the adoption of generative AI tools within SEO teams shifted from experimental to routine. Platforms such as ChatGPT, Claude, Gemini, and vertical tools like Surfer, Semrush AI, and Perplexity are now embedded in workflows that were previously entirely manual. At the same time, Google rolled out several core updates and a spam detection system aimed specifically at content generated at scale, creating tension between automation and editorial quality.

In that context, the question circulating among SEO professionals in LATAM and globally is concrete: which parts of linkbuilding can AI handle without risk, and which still require human judgment? The answer is not binary. It depends on which stage of the process the automation is inserted into, and whether the final result preserves or degrades the editorial relevance of the link.

To understand what is changing, it helps to first review what the available sources have said: Google documentation, quantitative studies from industry tools, and public statements from specialists with verifiable track records. The synthesis that follows covers data and public statements from 2023 onward.

What Google Says About AI and Link Quality

Google's official position on AI-generated content is articulated primarily in two documents: the Google Search Essentials (updated in 2023) and the Google Search Central article on helpful, people-first content. The stance is consistent: what matters is not whether content was produced by a human or an AI, but whether it meets the criteria of experience, expertise, authoritativeness, and trustworthiness (E-E-A-T).

With respect to links specifically, Gary Illyes, Google Search analyst, stated at a BrightonSEO talk that the spam detection systems have incorporated signals to identify outreach and publication patterns generated at scale. He did not detail the exact mechanism, but noted that uniformity in anchor text, repetitive email structures, and publication velocity are variables factored into the evaluation models.

John Mueller, for his part, has noted in multiple Google Search Central Office Hours sessions that links that exist solely to manipulate rankings — regardless of how they were obtained — provide no value and may be ignored or penalized. That definition is technologically agnostic: it applies equally to a manually purchased link and to one acquired through AI-automated outreach.

"The signal we look for in a link is that someone editorially decided to reference that content because they considered it useful for their audience. If that editorial decision doesn't exist, the link doesn't carry the value they expect it to have."

This statement has direct implications for evaluating any AI-mediated linkbuilding practice: if automation eliminates the publisher's genuine editorial decision, the link loses its fundamental value signal.

What Quantitative Studies Show

Three studies published between 2023 and 2025 provide relevant data for this analysis.

Ahrefs: AI Content Volume Does Not Correlate With More Backlinks

In its study on backlink acquisition patterns published in 2024, Ahrefs analyzed a sample of sites that substantially increased their content production using AI. The conclusion was that the increase in indexed pages did not automatically translate into a proportional increase in organic backlinks. The sites that did successfully attract new links were those that combined AI-assisted production with human editing and active distribution. The study is available on the Ahrefs blog.

Semrush: AI Speeds Up Outreach but Does Not Improve Response Rates

Semrush published data on AI use in outreach campaigns in its State of Search. Teams that adopted AI tools to personalize emails reported production times up to 60% shorter, but average response rates showed no statistically significant improvement compared to manually run campaigns of equivalent editorial quality. The most common interpretation among surveyed teams was that the operational efficiency gains are real, but effectiveness depends on the quality of prior targeting — not on the generated text itself.

Backlinko: Links in Long-Form Editorial Content Remain the Most Durable

Backlinko's analysis of backlink durability (2023, with 18-month follow-up) showed that links placed within long-form editorial content — articles over 1,500 words with a clear argumentative structure — have a considerably higher retention rate than those appearing in brief posts or generic resource pages. This finding is relevant because high-quality long-form editorial content is precisely the type that is hardest to produce with AI alone, without significant human involvement.

What Specialists Say

The following are verifiable public statements from specialists with recognized standing in the industry, both internationally and within the Spanish-speaking market.

Lily Ray (Amsive Digital)

Lily Ray, SEO Director at Amsive Digital and one of the most cited voices in Google update analysis, noted in her presentation at SMX Advanced that the greatest risk of AI in linkbuilding lies not in the tool itself but in volume: "AI makes it very easy to produce 500 outreach emails in an afternoon. The problem is that 498 of those emails have no real editorial basis, and publishers can tell." Her central argument is that scale without precise segmentation damages the sending domain's reputation among publishers.

Kevin Indig (Growth Memo)

Kevin Indig, in his Growth Memo newsletter from January 2025, drew a useful distinction between AI as a process assistant and AI as a replacement for judgment. According to Indig, the first use — automating prospect research, classifying domains by topical relevance, generating proposal drafts that a human then reviews — is consistent with building quality links. The second use — fully delegating the decisions of who to contact, what to offer, and what to publish — produces low-signal results that Google's algorithms are increasingly well-trained to identify.

Aleyda Solis (Orainti)

Aleyda Solis, an international SEO consultant with a strong presence in the Spanish-speaking market, published several reflections on integrating AI into SEO workflows on her blog and on X (formerly Twitter) throughout 2024. Her position is pragmatic: "AI is useful for scaling research, not for replacing strategy." In the context of linkbuilding, this means using AI to identify link opportunities at scale while maintaining human judgment over which opportunities to pursue and how to present the value proposition to the publisher.

Voice from the Hispanic Market: Romuald Fons

Romuald Fons, a prominent SEO figure in the Hispanic market with an extensive presence on YouTube and industry events, has noted in several 2024 and 2025 publications that linkbuilding in LATAM retains a strong relational dimension that AI does not easily replace. In markets where personal trust between the SEO professional and the media editor is part of the negotiation process, AI-generated templates tend to generate rejection more quickly than in English-speaking markets, where cold outreach is more normalized.

Wil Reynolds (Seer Interactive)

Wil Reynolds argued at conferences throughout 2024 that the real opportunity for AI in linkbuilding lies in content gap analysis at scale: identifying what topics one site covers that another does not, and using that gap as an outreach argument. This application is less visible than email generation but has a more direct impact on prospecting conversion rates.

What Changes With AI: Real Transformation Points

Drawing on the sources reviewed above, there are specific areas where AI's impact on linkbuilding is concrete and verifiable.

Prospecting and Prospect Classification

The manual search for relevant sites for a link-building campaign has historically been one of the process's main bottlenecks. Current AI-powered tools can cross-reference domain lists with traffic data, topical relevance, domain authority, and publication patterns in timeframes that previously required several days. This type of automation carries low editorial risk because it does not affect the quality of the resulting link — only the efficiency of the prior process.

To explore how this process fits into a digital PR campaign, it is worth reviewing how to use HARO and Connectively to earn authority backlinks, where the opportunity identification component is equally central.

Linkable Content Creation

The production of content that naturally attracts backlinks — original studies, reference guides, visual resources — can be accelerated with AI during the research and structuring phases. However, content that effectively earns links requires factual originality or a differentiated editorial perspective, two dimensions where current generative AI has well-documented limitations. The risk lies in publishing generic content at volume and expecting Google to treat it as reference-quality material.

Outreach Personalization

AI can help adapt the tone and structure of an outreach email to match the recipient's profile. But surface-level personalization — mentioning the blog's name or its most recent article — is not enough to stand out in inboxes that receive dozens of similar pitches. The personalization that converts is the kind that demonstrates an understanding of the publisher's audience and proposes an editorial angle that fits their editorial line — something that requires actually reading the site.

Backlink Monitoring and Analysis

This is where AI contributes most directly: tools that detect lost backlinks, classify link profiles by risk, identify competitors' linkbuilding patterns, or project the impact of new links on the overall profile. This analytical layer is probably where AI adoption generates the most net value with the fewest editorial risks.

What Stays the Same: Signals AI Cannot Manufacture

Beyond the operational changes, there are elements of linkbuilding that the sources reviewed consistently identify as stable in the face of automation.

• Real topical relevance: A link from a site thematically related to the destination continues to be more valuable than one from a high-authority generic domain. AI can identify relevant candidates, but it cannot manufacture relevance where none exists.
• Genuine editorial decision: As Mueller noted, Google looks for evidence that the publisher chose to link based on their own editorial judgment. Spam detection systems evaluate publication patterns, velocity, anchor structure, and the behavior of the linking site.
• Publisher domain authority: The accumulated editorial reputation of a site cannot be replicated artificially. A backlink from a publication with a history of rigorous coverage carries different weight than one from a site built to publish sponsored content at scale.
• Natural link profile diversity: A backlink profile with varied anchors, diverse topical sources, and organic acquisition velocity remains the benchmark against which Google calibrates artificially constructed profiles.
• Relationships with publishers: Especially in LATAM, where the digital editorial market operates at a more contained scale, direct relationships with editors