In this week’s digital news, the Google August spam update took 2.5 days to roll out and is now complete. Google announced it is rolling out new experimentation and planning capabilities in Google Ads and AI Max
Meta is implementing an AI-first approach to ad buying, which is transforming the way paid social teams operate. Unveil the truth about AI search with interesting findings from 15 million data points. Learn what really influences rankings.
Google has officially confirmed the completion of its August 2026 spam update, which finished rolling out globally on the 21st August after launching on the 18th. The algorithm update targeted systemic search manipulation and scaled content abuse, triggering substantial volatility and dramatic traffic swings for publishers relying on heavily automated publishing or scraped content. Industry monitoring highlights that sites churning out hundreds of low-value pages daily faced severe ranking collapses, while legitimate programmatic and human-authored sites successfully navigated the turbulence.
This update reinforces Google’s zero-tolerance stance on low-effort, mass-produced content and poorly executed automation. Sites caught in the crosshairs experienced steep drops in organic reach, proving that technical evasion tactics or rapid scaling strategies no longer protect sites from algorithmic evaluation. SEO professionals must prioritise rigorous quality audits, ensuring that all published material offers distinct human value rather than generic aggregation to safeguard their rankings against future spam updates.
Google is rolling out new testing and planning tools for Search campaigns and AI Max. From September, advertisers will be able to run a single A/B test across multiple Search campaigns to measure the impact of budget and ROI target changes. AI Max experiments can now be run with brand and location parameters active, letting advertisers test the feature without removing existing targeting guardrails. Performance Planner has also been updated to predict the impact of bidding or budget changes and allow immediate application of its recommendations directly within the tool.
Meta is continuing to shift campaign decision-making away from manual buyers and toward its automated systems, with audience selection, placement and optimisation increasingly handled by AI. For enterprise advertisers, the practical implication is that the edge no longer lies in granular ad set management but in the quality of conversion signals, creative volume and governance. Poor or inconsistent event tracking via Pixel and Conversions API will train Meta’s optimisers toward the wrong outcomes. A particular risk for large organisations with fragmented web properties. Creative production also becomes a persistent operational discipline rather than a project-based one. With AI systems rewarding consistent asset throughput over occasional campaign bursts.
A comprehensive study by Ahrefs, analysing 15 million data points across major AI search engines like ChatGPT, Gemini, Perplexity, and Copilot. Has debunked several prominent AI search myths. Led by researcher Mateusz Makosiewicz and incorporating insights from SEO experts like Lily Ray. The research revealed counterintuitive truths about GEO. Notably, controlled experiments showed that self-promotional “best-of” listicles often backfire. AI models use the content for data grounding but recommend competitors in 43% of answers. Additionally, the study found that 97% of published llms.txt files are never read by AI bots, and schema markup provides no immediate shortcut for gaining citations.
The implications of these findings force a fundamental course correction for anybody chasing quick AI “hacks.” Rather than investing resources into unread text files or superficial schema tweaks, brands must focus on traditional organic authority. Given that 88.46% of AI citations still trace back to the standard search index. SEO teams are advised to abandon speculative tactics and build robust. Authoritative brand content across independent platforms to secure reliable visibility in generative search.
Reddit’s citations in ChatGPT have fallen from as high as 4.5% of responses to about 0.5% after OpenAI changed how it searches the web. Reddit says it still gets most of its traffic from direct visits and traditional search. Meanwhile, Reddit is using AI to turn posts and comments into videos and podcasts. With the company aiming to make its content easier to consume in the background.
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ChatGPT 5.6 is changing how it searches, with fewer fan-out queries using terms like “best”, “top”, “vs”, and “comparison”. Peec AI data shows listicles made up 7.8% of citations after the update. Down 50.5%, while comparison pages fell 32.1% to 6.17%. The shift could reduce visibility for the listicles and comparison pages that brands have been creating at scale to win AI citations and mentions.
Read more here.
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