The world of search is undergoing seismic shifts—and this week’s news updates confirm that the future of SEO will be shaped not just by rankings, but by how AI reshapes the very structure of search itself. Google is doubling down on AI-generated results with major enhancements to AI Mode, now open to all U.S. Labs users and showing signs of full integration into core search. At the same time, fluctuations in search rankings continue to stir speculation around silent updates.
Meanwhile, Google Search Console rolls out smarter insights and hourly data tracking, Google Ads brings transparency to Performance Max campaigns, and the unexpected collaboration between Apple and Google signals that generative AI is no longer a competitive edge—it’s becoming infrastructure.
From changes in local and product SERP visibility to evolving SEO best practices, this week’s roundup breaks down everything you need to know to stay ahead. Let’s dive in.
The SEO community was abuzz this week with reports of major ranking fluctuations—despite no confirmation from Google about a core algorithm update. Several tracking tools, including Semrush Sensor, Rank Ranger, and Accuranker, showed increased volatility between April 22–23 and again on April 25.
Webmasters across industries reported mixed signals—some saw significant drops in traffic, while others enjoyed unexpected spikes. Many speculate that these could be tests of AI Overviews (formerly SGE) or updates to how Google interprets site authority and topical depth.
Even though these aren’t confirmed updates, the movements are similar in impact to previous broad core updates, indicating that Google is continuing to refine its understanding of search intent and quality content. If you saw any ranking shifts, now’s a good time to review recent content, update outdated pages, and double down on E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness).
Google’s vision for the future of search took another leap forward this week with major updates to its experimental AI Mode—a feature being developed under Google Labs that could redefine how users interact with the world’s most widely used search engine.
Announced on May 1, 2025, the latest updates to AI Mode reflect Google’s commitment to building a more dynamic, conversational, and visual search experience—one that goes beyond blue links and aims to deliver direct, intuitive answers while maintaining context across sessions.
Previously limited to users on a waitlist, AI Mode is now immediately available to all users in the U.S. who opt into Google Labs. This change dramatically expands access and allows a broader group of users to experience and shape the future of search.
For SEOs, this means that real-world usage and feedback from a larger sample size will likely influence how AI responses evolve—potentially accelerating shifts in user behavior and how we optimize for visibility.
One of the most noticeable upgrades is the inclusion of rich visual cards in AI-generated results. These cards can highlight:
This moves the experience closer to a true “answers engine” where users get everything they need at a glance—often without clicking through to a website.
This visual shift puts pressure on SEOs to optimize for featured inclusion, especially in verticals like local SEO, e-commerce, and news.
Another major change is the introduction of a left-side session panel, which displays a history of your interactions and follow-up questions. This effectively turns Google Search into a threaded conversation, where context from previous queries is retained.
Users can click back into any part of the conversation, revisit earlier results, or build on them—similar to how AI chat platforms like ChatGPT maintain thread memory. This marks a departure from the one-and-done query model and introduces opportunities for long-tail visibility across multiple query layers.
For marketers, it’s essential to ensure content answers related sub-questions and can be parsed effectively by Google’s AI models in extended dialogue.
In the coming weeks, Google will begin testing the AI Mode tab directly within the main Google Search interface for a small percentage of users in the U.S. This is significant because it suggests AI Mode may move from an opt-in Labs experiment to a standard feature accessible by default.
If widely adopted, this could fundamentally shift how users access and interpret search results—particularly for informational queries, research-heavy tasks, and product discovery.
Google’s updates to AI Mode are not just cosmetic—they represent a deeper shift in how the company envisions the role of search in people’s lives: not just finding, but understanding, guiding, and helping users make decisions faster.
Search Console got two welcome upgrades this week:
This week, Google’s Search Relations team addressed several long-standing questions from the SEO community, offering clarity on internal link repetition, sitemap behavior, and domain extension (TLD) impact. These subtle yet important confirmations help refine our understanding of technical SEO and site structure, especially for those focused on optimization at scale.
One of the questions many webmasters face when designing site architecture is whether placing multiple identical internal links on a single page affects SEO.
Google confirmed that having multiple links pointing to the same destination URL on the same page is perfectly fine. This is common on most websites—think of a navigation menu linking to a product page, plus a CTA in the body text pointing to the same place, and another link in the footer. Google sees this as standard behavior.
From an SEO perspective, Google typically considers the first anchor text for ranking signals, but the existence of duplicate links does not cause dilution or confusion. The key takeaway? Don’t worry about repeating important internal links—just ensure they are useful, relevant, and contribute to user experience.
Another point of clarification focused on the lastmod attribute in XML sitemaps—the tag used to indicate the last time a particular page was modified.
Some SEOs have attempted to manipulate the lastmod date to suggest that content is fresher than it really is, hoping to trigger a re-crawl or rank boost. Google strongly advised against this practice.
While it’s not seen as a spam tactic per se, artificially updating the lastmod tag without actual content changes offers no SEO benefit and may reduce Google’s trust in your sitemap over time. If Google notices inconsistencies—like unchanged content paired with frequently updated lastmod dates—it may simply begin ignoring the tag altogether.
The best practice? Update lastmod only when meaningful changes are made to the page—such as content updates, layout changes, or added features. This helps Google prioritize which pages to recrawl and keeps your sitemap accurate and useful.
Lastly, Google addressed a popular question regarding whether certain top-level domains (TLDs)—like .ai, .store, .design, or even more niche ones like .esports—carry any SEO advantage or disadvantage.
The short answer: They don’t.
Google treats all TLDs equally from a ranking standpoint. Choosing a specific TLD will not inherently improve your visibility, trustworthiness, or authority in the eyes of the search engine. What matters more is:
So, while using a relevant TLD like .photography or .finance might help with brand positioning or user clarity, it won’t boost your Google rankings on its own.
These confirmations from Google don’t represent new policies, but they reinforce the importance of clarity, honesty, and user-centric structure in technical SEO. Clean internal linking, accurate sitemap metadata, and pragmatic domain naming all play a role in site health—even if they aren’t ranking factors by themselves.
For SEOs and webmasters, it’s a reminder to focus on what matters most: serving users well, organizing information cleanly, and ensuring technical accuracy across your site.
Google Ads has rolled out a highly anticipated update to Performance Max campaigns, bringing channel-level transparency, enhanced asset insights, and more comprehensive reporting tools—offering advertisers far greater control over campaign optimization.
One of the biggest pain points for advertisers using Performance Max has been the lack of visibility into where and how ads were being delivered. That’s now changing.
With the new “Channel performance” view, advertisers can see how their campaigns perform across individual Google channels—including Search, YouTube, Display, Discover, Gmail, and Maps. This granular reporting includes key metrics such as impressions, clicks, conversions, and spend per channel, making it much easier to evaluate where performance is strongest and where improvements are needed.
Visual dashboards and exportable tables allow teams to quickly identify trends. For instance, if YouTube is generating a large volume of high-converting traffic, an advertiser can respond by developing more video-focused creative assets.
In addition to channel data, Google is also expanding the metrics available for creative assets. Advertisers can now view impressions, clicks, cost, conversion value, and average CPC for each asset (like headlines, images, videos, and calls-to-action).
This gives marketers clear insight into what’s working, what’s underperforming, and where to allocate creative resources. It also helps improve ad strength scores, which are critical for maximizing reach and performance within Performance Max campaigns.
Performance Max will now offer full access to search term data—the same level of transparency previously limited to standard Search and Shopping campaigns.
Advertisers can see exactly which user queries are triggering their ads, which is a game-changer for optimization. With this insight, they can fine-tune messaging, create custom segments, and exclude irrelevant traffic with negative keywords, helping improve targeting precision and reduce wasted spend.
Google is also introducing diagnostic insights that flag potential performance blockers within specific channels. For example, if an ad isn’t performing well on Google Maps because a location extension is missing, the system will alert the advertiser to fix it.
These cues help advertisers quickly resolve issues that may otherwise go unnoticed—ensuring all available inventory is being used effectively.
This update is a significant shift in how Performance Max operates. The black box is slowly being opened. Marketers now have actionable data on both the where (channel performance) and the how (asset effectiveness and search queries), making it easier to optimize campaigns for ROI rather than guesswork.
The rollout is expected to continue in the coming weeks, with more in-depth previews slated for Google Marketing Live later this month.
In a bold step toward monetizing emerging digital interactions, Google has begun integrating AdSense ads directly into third-party AI chatbot conversations. This marks a significant evolution in how and where Google ads can appear, reflecting a strategic pivot to stay competitive as user behavior shifts toward AI-driven platforms.
Google is extending its AdSense for Search program to cover chatbot interfaces. This means that when a user interacts with an AI assistant—particularly those built by third-party developers—ads may now appear contextually based on the conversation.
Early implementations have involved AI chatbots created by startups, where users receive conversational answers with sponsored links or promoted suggestions seamlessly inserted into the dialogue. The ads are designed to align closely with the content and intent of the conversation, mimicking the approach already used in Search and Discover placements.
This move comes as more users seek fast, dialogue-based interactions over traditional search results. Tools like ChatGPT, Claude, and Perplexity have gained traction for offering natural, fluid answers—often replacing the need to sift through web pages. Google’s strategy ensures its ad ecosystem remains present wherever people search or engage with information—even if that environment isn’t Google Search itself.
The integration helps Google retain advertisers who are exploring alternative platforms for visibility and reach. It also ensures publishers and developers entering the AI space can monetize their tools via the familiar AdSense infrastructure.
One challenge will be balancing monetization with user trust. Ads must be subtle and relevant to avoid breaking the conversational flow or appearing spammy. If implemented well, it could enhance the chatbot’s utility—helping users discover products or services they were already looking for.
However, overly aggressive or irrelevant ad placement could backfire, damaging both user experience and the credibility of the AI platform hosting the ads.
For advertisers, this presents an opportunity to appear in a new type of intent-driven context—where users are actively seeking solutions or answers. These interactions may prove more conversion-friendly than traditional display ads, given their relevance and immediacy.
For AI developers and chatbot publishers, it unlocks a new revenue stream at a time when monetizing AI tools is a growing challenge. Integrating with AdSense may offer an easy plug-and-play solution while retaining focus on content and product development.
This shift signals that conversational AI isn’t just reshaping how users search—it’s transforming the entire digital advertising ecosystem. Brands, developers, and marketers alike will need to adapt quickly to make the most of this rapidly evolving frontier.
In a major development shaking up the tech landscape, Apple has confirmed that it will integrate Google’s Gemini AI into its upcoming Apple Intelligence platform. This move marks a rare but strategic collaboration between two of the largest competitors in the mobile and AI space.
Unveiled earlier this year, Apple Intelligence is Apple’s suite of AI-powered tools designed to enhance user experience across its ecosystem—including iPhone, iPad, and Mac. It focuses on summarization, smart replies, personalized recommendations, and on-device understanding of user intent. Think: a smarter Siri, proactive reminders, and context-aware responses in apps like Mail, Safari, and Notes.
Apple has traditionally prioritized on-device processing and user privacy, often limiting access to large cloud-based models. However, certain tasks—like generating complex text, interpreting context-rich queries, or processing images—require the power of large language models (LLMs) that go beyond Apple’s native capabilities.
By partnering with Google, Apple gains access to Gemini Ultra, the most powerful version of Google’s multimodal AI model, which can process text, images, and audio in tandem. This allows Apple to offer more advanced features without building an LLM from scratch or compromising on user experience.
Apple emphasized that users will have full control over when Gemini is used. Requests that need cloud processing will prompt user approval. Additionally, privacy safeguards will be maintained in line with Apple’s standards—meaning no user data will be used for training Gemini.
This partnership underscores how even the most privacy-conscious companies recognize the need for powerful generative AI—and are willing to work with former rivals to get there. For marketers and SEOs, this is yet another signal that AI-driven search and user interaction models are no longer on the horizon—they’re here.
As AI continues to reshape how information is retrieved and displayed, SEO professionals must adapt—not only in terms of strategy but also in tooling, content structure, and user intent analysis. Stay agile, test frequently, and keep your finger on the pulse.
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