This week in search has been anything but quiet. Google rolled out major enhancements across Search and Search Console — from Gemini 3’s debut inside AI Mode to new travel-planning features that push agentic workflows even further.
Site owners also get two valuable reporting upgrades in Search Console: a Branded Queries filter and Custom Chart Annotations, both aimed at giving SEOs clearer visibility into user intent and performance patterns.
And in industry news, Adobe shocked the search world with its $1.9B acquisition of Semrush, signaling a major shift in how AI, analytics, and content workflows may soon converge.
Here’s everything you need to stay ahead.
Google has introduced Gemini 3, calling it its most intelligent model to date, built for state-of-the-art reasoning, deep multimodal understanding, and powerful “agentic” behavior.
Gemini 3 isn’t a single model, but a family, with Gemini 3 Pro as the first release:
Google positions Gemini 3 as a step toward turning its products—from Search to productivity tools and developer platforms—into “thought partners” that can help users plan, reason, and complete multi-step tasks, not just answer one-off questions.
At the same time as the Gemini 3 launch, Google rolled out the model directly into Google Search’s AI Mode, marking the first time a new Gemini flagship model ships into Search on day one.
Smarter Query Fan-Out and Deeper Reasoning
Search already uses a “query fan-out” technique—where AI issues multiple related queries behind the scenes and then synthesizes results. With Gemini 3, Google says this system gets a major upgrade:
In practice, this means that for multi-step, messy, or highly specific questions, AI Mode can tap into a wider and more finely curated set of web pages before composing an answer.
Generative UI: Dynamic Layouts, Tools and Simulations
One of the biggest changes comes from what Google calls “Generative UI”—interactive layouts that Gemini 3 builds on the fly:
These interfaces are powered by Gemini 3 Pro’s reasoning and tool-use abilities plus a dedicated generative-UI system described in Google’s research.
For users, Search becomes less like “10 blue links + a paragraph” and more like a custom mini-app built around their question.
Smarter Model Routing in AI Mode and AI Overviews
Google also plans to upgrade automatic model selection inside Search:
This type of routing matters because it effectively creates two tiers of search behavior:
Knowing which kind of intent your content serves can influence how often it’s pulled into Gemini 3-powered responses.
Availability and Access
According to Google, the first rollout looks like this:
Beyond Search, Gemini 3 Pro is also available via the Gemini app, Gemini API, Vertex AI, Gemini Enterprise, and developer tools like Gemini CLI, Jules, Code Assist and Antigravity.
Visibility Is Now About Being Used, Not Just Ranked
With Gemini 3 driving AI Mode, search visibility isn’t only about traditional rankings anymore:
Think of it this way:
Your content now needs to be something an AI system trusts enough to quote, not just something a ranking algorithm thinks deserves position #1.
Multimodal and Interactive Content Gains Importance
Because Gemini 3 and the Generative UI can handle images, video, and tools: \
Visual assets, demos, diagrams, and videos that clearly explain a concept may have more value as ingredients for AI responses.
This doesn’t mean every page needs a custom app—but it does suggest that richer, well-structured experiences have more routes into AI-driven answers.
Intent Complexity and “Thinking” Queries
Because Gemini 3 is reserved for more complex questions in AI Mode and AI Overviews, it’s worth thinking about intent complexity:
If your content addresses in-depth guides, planning workflows, comparisons, and decision support, it’s directly aligned with the type of queries that Gemini 3 is designed to handle.
Here are practical steps to align with this new Gemini 3 + Search reality:
1. Strengthen Structure and Clarity
2. Create “AI-Usable” Depth
3. Invest in Multimodal and Interactive Assets
4. Watch for AI-Influenced Behavior in Your Analytics
Over time, SEOs may need to treat AI citations and mentions as a new layer of visibility metric, alongside rankings and organic sessions.
Gemini 3 is more than just another model release—it’s Google’s attempt to fuse deep reasoning, multimodal understanding, and agent-style behavior directly into Search. For SEOs and marketers, that means the rules of visibility are expanding: your content must not only rank, but also be understandable, reusable, and trustworthy to an AI system that’s assembling answers on the fly. The sooner you adapt your strategy—focusing on rich structure, genuine depth, and assets that AI can work with—the better positioned you’ll be in this next era of search.
Google recently announced major travel-oriented upgrades to Google AI Mode: a new Canvas workspace for trip planning, expanded Flight Deals, and agentic booking capabilities (for restaurants now, and hotels/flights coming soon).
Canvas: Build Your Trip in-Search
The Canvas tool—already part of Google AI Mode—now supports full travel planning. Users in the U.S. desktop experiment can say something like:
“I want a 5-day trip to Barcelona in April, beach during day, good food at night.”
Then select “Create Canvas”, and Google will pull into a side-panel itinerary: flight and hotel options, Google Maps photos and reviews, suggestions for restaurants and activities based on your criteria (budget, walking distance, etc.).
Users can further refine via follow-up questions, trade-offs (e.g., cheaper hotel vs proximity to restaurant), and return to the plan via history.
Flight Deals: Expanded Global Reach
Google’s AI-powered Flight Deals tool (inside Google Flights) is now rolling out to 200+ countries and territories, supporting 60+ languages. Users can ask in natural language — e.g., “family-friendly beach vacation under $1,200 in June”—and receive tailored destination suggestions.
Agentic Booking: From Research to Reservation
Google is also enhancing agentic booking in AI Mode:
Google’s travel-planning upgrades mark a clear evolution in how search works—moving from simple retrieval to task execution, planning and booking. For travel brands, destination marketers and local businesses, the window to adapt is now: visibility won’t just depend on ranking or content, but on how you integrate into AI-powered workflows, structured data surfaces, and assistant-driven booking flows.
Google Search Console is rolling out a new filter called the Branded Queries Filter, designed to help site owners separate traffic that comes from brand-related searches from traffic driven by discovery or non-brand queries. This update is part of Google’s push to give more nuance to how performance data is segmented and analysed.
What the Filter Does
Better Brand vs Discovery Insight
Understanding the difference between branded and non-branded traffic is critical:
Removes Manual Complexity
Until now many teams used large custom regex filters or external tools to segment brand vs non-brand queries. With this native filter:
Impacts Reporting, Dashboards and Strategy
Limitations & Considerations
The Branded Queries Filter in Search Console may appear modest at first glance, but it offers major implications for how we understand search performance. By giving native access to brand-vs-non-brand segmentation, Google is helping SEO, content and brand teams align more clearly around what’s driving traffic and awareness. As this rolls out, the better prepared teams will be those that have already benchmarked, structured their data, and can act on insights — not just clicks.
Google Search Console has introduced a long-awaited feature: Custom Annotations in the Performance report. These annotations allow users to add notes and markers directly to the performance graphs, making it easier to correlate changes in clicks, impressions, CTR and position with external events such as site migrations, algorithm updates or marketing campaigns.
What the Feature Offers
For marketers, SEOs and web teams, the addition of annotations in Search Console offers several enhancements:
Important Considerations
The addition of Custom Annotations to Search Console marks a useful step forward in search visibility tracking: performance data meets context, and what was once just spikes & dips now has narrative. For teams serious about insights, this is a chance to integrate measurement, collaboration and event-tracking directly within Google’s toolset — and to ensure that when your metrics change, you know not just that they changed, but why.
Adobe announced it will acquire Semrush Holdings, Inc. in an all-cash deal valued at approximately $1.9 billion, paying $12 per share. Pending regulatory and shareholder approval, the deal is expected to close in the first half of 2026.
Adobe frames the acquisition as part of its strategy to expand visibility, analytics, and AI-driven marketing capabilities across both traditional search engines and emerging AI surfaces.
Semrush is one of the most widely used SEO, competitive intelligence, and digital visibility platforms in the world. Founded in 2008, it has grown from a simple keyword-research tool into a multifaceted suite used by 10+ million marketers, agencies, and brands.
Semrush’s core capabilities include:
Semrush has long been considered a “critical tool” in SEO workflows—used by teams ranging from small agencies to global brands. Its blend of search data, competitor intelligence and now AI search visibility metrics is a major reason Adobe sees strategic value in the acquisition.
Adobe says the acquisition will create a unified platform where marketers can understand how users discover their brand across search engines, generative AI assistants, and the web.
Key motivations include:
According to Adobe, brands will be able to see a more complete picture of their visibility:
from traditional organic search → to paid media → to social → to how they appear inside AI-generated answers.
Semrush has been expanding its AI visibility index, measuring how often brands are cited in responses from tools like ChatGPT, Gemini, Claude, etc.
With Adobe’s resources, this dataset could grow dramatically.
SEO will increasingly sit beside:
Adobe will likely try to create “one interface” for marketers to manage all of it.
If Semrush becomes more enterprise-focused under Adobe, smaller businesses could move toward Ahrefs or emerging lightweight SEO tools—rebalancing the market.
Teams want a single view showing:
Adobe + Semrush likely aims to offer exactly this.
Adobe’s $1.9B acquisition of Semrush is more than a corporate deal—it’s a signal that SEO, competitive intelligence and AI visibility are now central pillars of modern marketing. As AI-driven discovery reshapes how users find brands, the tools that track visibility across Google, LLMs and agentic systems are becoming mission-critical. Whether this acquisition unlocks powerful new capabilities or tightens access behind enterprise walls will depend on how Adobe handles the transition—but one thing is clear: the future of search visibility just became even more integrated with the broader marketing ecosystem.
As AI continues reshaping discovery, rankings, and reporting, Google’s latest updates show exactly where search is headed — more personalized, more assistant-driven, and increasingly centered on multimodal intelligence. Meanwhile, Adobe’s acquisition of Semrush reinforces a fast-evolving landscape where SEO tools, creative platforms, and AI ecosystems are beginning to merge. Staying informed is no longer optional; it’s essential for future-proofing your strategy. We’ll continue tracking the shifts, testing what matters, and breaking everything down for you each week.
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