Google’s New AI Mode in Search: What B2B Marketers Need to Know

Google has unveiled a game-changing addition to Search: AI Mode, an AI-powered search experience announced at Google I/O 2025. This new mode transforms how users query and receive information on Google, allowing people to ask complex, multi-part questions in a conversational interface and get rich, synthesized answers – much like ChatGPT. For B2B marketing leaders, AI Mode isn’t just another Google update – it signals a fundamental shift in search behavior that could impact how your content is discovered (or not discovered) by prospects. In this article, we’ll break down what AI Mode is, the key features introduced at I/O 2025, and (most importantly) the strategic implications for B2B marketing and SEO. We’ll also provide guidance on how to adapt your content strategy and stay ahead in an AI-driven search landscape, supported by expert insights and real examples.

In a nutshell: Google’s AI Mode makes search more conversational, analytical, and personalized – and it’s rolling out now. Here’s what you need to know and how to respond.

What Exactly Is Google’s AI Mode in Search?

Google’s AI Mode is an experimental search feature that essentially adds a conversational AI assistant to Google Search. Instead of the classic ten blue links, users can enter detailed questions or tasks and receive an AI-generated answer that draws on multiple sources. Think of it as Google’s version of a chat-based research assistant embedded in search. According to Google, AI Mode lets users ask complex, multi-part questions via an AI interface and even ask follow-up questions in a conversational manner. This feature was initially available only to Search Labs testers, but at Google I/O 2025 the company announced it’s rolling out AI Mode to all users in the U.S. starting this week, with global expansion on the horizon.

Importantly, AI Mode builds on Google’s existing AI Overviews (the AI-generated summaries that have appeared at the top of some search results since 2024). Those AI Overviews gave brief answers for certain queries, but AI Mode goes further – it invites the user to engage in a back-and-forth dialogue and tackle more elaborate questions. In fact, Google sees AI Mode as “its pitch for what the future of search will look like”. The company is clearly betting big on this; Google even started testing an “AI Mode” button on the Google homepage, replacing the iconic “I’m Feeling Lucky” button for some users. As SEO strategist Glenn Gabe noted, Google is giving AI Mode prime real estate – a strong signal of how central this AI-driven search experience is to Google’s strategy.

So how does AI Mode work in practice? Essentially, when AI Mode is activated, your query is handled by Google’s generative AI (powered by a custom Gemini 2.5 model). The AI will break down your question into sub-queries, search the web for relevant information, and then synthesize the findings into a coherent answer with references. You can then ask follow-up questions or refine the query further in a conversational thread. It’s like having a knowledgeable research assistant who can comb through the web and report back to you – all within the familiar Google interface.

Example: Google’s AI Mode interface can handle complex, multi-part questions. In this example, a user asks the AI to research local summer camps with specific requirements (distance, schedules, pricing, activities, etc.). The Deep Search capability will break this down into numerous sub-queries and compile a detailed answer, complete with citations.

Notably, Google has maintained citations and links in the AI Mode results. The answers are accompanied by source links so that users can “dig into the research” themselves if desired. In Google’s words, the AI’s response is like a “fully cited report generated in minutes,” saving users from hours of manual research. This approach is meant to preserve some traffic to content publishers (more on that later), while still giving users direct answers up front. And users are embracing these AI features: Google claims over 1.5 billion monthly users have already tried its AI-powered search features (AI Overviews), so it’s moving AI Mode out of the labs and into mainstream search across 200+ countries and 40+ languages soon.

In summary, AI Mode turns Google Search into a more interactive, AI-driven experience. Users get to ask nuanced questions in natural language and receive aggregated answers from many sources. It’s a powerful tool for searchers – and a paradigm shift that marketers need to understand. Next, let’s look at the specific features and updates Google announced for AI Mode at I/O 2025, as these reveal where search is headed.

Key Features and Updates Announced at Google I/O 2025

At I/O 2025, Google showcased AI Mode’s new capabilities and related search updates that will roll out this year. Here are the highlights that marketers should note:

  • Deep Search for Thorough Answers: One of AI Mode’s headline features is Deep Search. This capability takes a complex question and breaks it into numerous subtopics, essentially running dozens or even hundreds of searches behind the scenes to gather information. The AI then compiles the results into a comprehensive answer. The result is an in-depth, fully cited response that might read almost like a report. Google demonstrated how Deep Search can be a boon for research-intensive queries – for example, planning a big purchase or finding the best kids’ summer camp. At I/O, Google suggested using Deep Search to compare options for a “big-ticket home appliance or a summer camp for the kids,” tasks that typically require scouring many websites. Instead of the user manually checking different sources, AI Mode can do the heavy lifting in seconds and present the distilled insights. This is a clear indicator that Google wants to handle more “open-ended” research queries directly via AI.
  • AI-Powered Shopping & “Virtual Try-On”: Google is also weaving AI Mode into the e-commerce search experience. A new “Shop with AI Mode” experience was introduced, featuring a visual product panel and interactive guidance. For instance, if you search for a travel bag, AI Mode can show a scrollable panel of products tailored to your query.

    You can refine with natural language (e.g. “bags suitable for a trip to Portland, Oregon in May”), and the AI will run multiple simultaneous queries (Google calls it a “query fan-out”) to figure out the best options for your specific context – in this case, perhaps considering bags for long journeys and rainy weather. The product results panel then updates to highlight, say, waterproof bags with lots of pockets. Another impressive shopping feature is virtual try-on for apparel. Google has had rudimentary try-on tech before (overlaying clothes on sample models), but now AI Mode lets users try on clothes on their own photo.

A user can upload a full-body photo of themselves, and Google’s new diffusion AI model will “generate an image of yourself wearing the item” you’re interested in. The AI understands 3D body shape, fabric drape, and stretch, so it can realistically show how a shirt, dress, or pants would look on you. This virtual try-on is launching via Search Labs in the U.S. and will show a “Try On” button next to product listings for various clothing items. Users can even share these AI-generated looks with friends or shop similar styles. For B2B marketers, this specific feature might not apply unless you’re in retail/fashion, but it underscores a larger point: Google is making search results more visual, interactive, and personalised with AI, even to the point of handling tasks (like trying on or comparing) that users used to do off-platform.

  • Automated Price Tracking & Agent Checkout: In addition to discovery, Google is adding AI-driven convenience for purchases. Users will soon be able to “track price” on product results and set a target price – Google’s AI will monitor prices and notify you when a product hits your desired price. At that point, an agent can even help you check out: with a tap of a new “buy for me” button, Google will automatically add the item to the merchant’s cart and initiate checkout using your saved details. Essentially, Google is positioning itself as an intermediary for transactions when conditions are met. While this is more relevant to B2C retail, it highlights Google’s push towards AI agents that don’t just inform users, but act on their behalf within search. This could hint at future capabilities in B2B (imagine an AI that could, say, auto-schedule demos or order supplies when criteria are met).

  • Complex Data Queries (Sports, Finance, etc.): A notable update for AI Mode is support for data-heavy queries. Google demonstrated that AI Mode will soon handle complex statistical questions in domains like sports and finance. For example, a user could ask to “compare the Phillies and White Sox home game win percentages by year for the past five seasons,” and the AI will pull together data from multiple sources, compile it into a single answer, and even generate charts or visualisations on the fly.

    This is essentially Deep Search applied to structured data – something highly relevant for B2B if you think about all the comparative research (e.g. market trends, benchmark stats, product spec comparisons) that business buyers do. The AI can be an analyst, searching out figures and presenting them with visuals. For marketers, this means content like reports or data-driven posts could be mined by Google’s AI to answer user questions directly. Ensuring the AI has access to accurate data from your content (and cites it) could be an opportunity or a risk, depending on how well you’ve optimised that content.

  • AI “Agents” for Local and Task-Based Queries: Google is also introducing more agentic behavior in search. Under a project codename “Project Mariner,” AI Mode can act on local queries that involve checking multiple sources. For instance, if someone is looking for the “best affordable concert tickets this weekend”, AI Mode can automatically check various ticket sites for prices and availability and then summarize the best options.

    Likewise, for restaurant reservations or event bookings, the AI could streamline the research process by aggregating options and even possibly taking actions like holding a reservation slot. This agent-like functionality starts with things like entertainment and dining, but over time one can imagine it extending to other tasks. It’s another sign that Google wants to not only answer questions, but also help users get things done via AI. For B2B, consider how an AI agent might one day assist in scenarios like finding a meeting time (it could integrate with calendars) or gathering quotes from vendors – tasks that typically involve back-and-forth searches or communications.

  • Search Live (Multimodal Search on the Fly): Coming later in the summer, Search Live is an extension of AI Mode that combines search with your device’s camera and microphone for real-time, multimodal queries. This goes beyond Google Lens’ one-shot image recognition. With Search Live, you could point your phone at something and ask questions in real time as the scene changes, with the AI conversing about what it “sees.” Google likened this to its advanced Project Astra multimodal system. For example, you might pan your phone around a store shelf and ask “Which of these would be best for my needs?” or get live translations of signs while asking follow-ups. This might seem futuristic, but it’s directly in line with the trend of blending the physical and digital search experience.

    Marketers should foresee that search will not be confined to typed keywords on a desktop – it will be spoken, visual, and continuous. Users might discover products or information in the wild and expect AI assistance instantly. Ensuring your content (and product info) is optimized for visual search or voice context could become increasingly important.

  • Personalized Results with Integrated Apps: Google is carefully introducing personalization into AI Mode. At I/O, they announced that users will have the option to connect their Google apps (starting with Gmail) to provide personal context to searches. For example, if you allow it, AI Mode can read your Gmail for things like travel bookings; then when you search, say, “best restaurants in Denver,” it knows you’re traveling there next week (from your email itinerary) and can tailor the results or recommendations to your travel dates. Google emphasized privacy controls (you can connect or disconnect at any time), knowing this could raise concerns.

    The first integration is Gmail (e.g. to suggest events at your travel destination based on flight confirmation dates), but one can imagine Calendar, Drive, or other apps could follow. For B2B marketers, this points to a future where search results may be influenced by user-specific context. For instance, if a user has been emailing with vendors or has certain apps connected, the AI might use that to personalize which solutions it recommends. It underscores the importance of being present and highly relevant in the moments that matter – because Google’s AI will use whatever data it has to serve what it deems the most contextually relevant answer.

All told, Google I/O 2025 cemented that AI is now central to the search experience. From richer shopping searches to data analysis to live camera Q&A, Google is infusing generative AI across the board. For marketers, these features signal how user expectations are evolving: people will come to expect search to handle more complex, conversational queries and even proactive tasks. Next, we’ll explore what these changes mean for B2B marketing and SEO strategy.

Strategic Implications for B2B Marketing and SEO

Google’s AI Mode and related AI search updates mark a significant shift in search behavior – one with far-reaching implications for content visibility, SEO, and brand discovery, especially in B2B contexts. As one SEO manager put it, “the old rules of SEO and optimizing content don’t apply like they used to… It’s a fundamental shift that’s happening.”. Let’s unpack the key changes and what they mean:

Search Behavior Is Evolving – More Questions, Fewer Clicks

First and foremost, users are changing how they search. With AI Mode, people can ask more nuanced, long-form questions (even combining what used to be multiple separate searches into one). Search queries are becoming more conversational and complex. For example, a B2B buyer could ask a single question like, “Compare the ROI of cloud ERP vs on-premise for a mid-size manufacturer, and include key security considerations.” In the past, they’d have to perform multiple searches and piece that together from various articles and whitepapers. Now, they might get a synthesised answer directly from the AI.

This means fewer searches and fewer clicks to individual websites for those who use AI Mode. Early data from Google’s AI-powered results already shows a decline in organic clicks. In fact, even before AI Mode’s full rollout, an estimated 60% of Google searches ended without any click to a external website in 2024. Rich snippets and AI summaries have been satisfying many queries directly on the results page – a trend that AI Mode will only accelerate. One analysis predicted that generative AI in search could lead to an 18% to 64% decrease in organic clicks as users get their answers straight from the search engine.

We’re already seeing this play out: publishers have observed that when their content is included in an AI Overview, the click-through rate (CTR) is significantly lower. For example, when the Daily Mail appeared as the top cited source in Google’s AI Overview, it still saw a 43.9% lower CTR on desktop (32.5% lower on mobile) compared to a normal result. In other words, even if your website is “featured” in the AI answer, fewer users may actually click through, because the AI has given them what they need.

From an SEO perspective, this is a paradigm shift. Traditional search optimised for clicks – get to the top of the rankings, earn the click, then engage the user on your site. Now, with “zero-click searches” on the rise, the content may be consumed in summary form on Google itself. A study from BrightEdge found that while search impressions in one period jumped 49% (because Google is surfacing more content via AI), the click-through rate fell by 30% in the same time. Users are letting Google (or Bing, or ChatGPT, etc.) do the reading and filtering for them.

For B2B marketers, this means the top-of-funnel discovery process might increasingly happen without a visit to your blog or resource center. Prospects might get answers to their questions via AI summary, and only click through if they need more depth or see your site as particularly relevant. Content visibility is no longer just about blue links on a SERP – it’s about being present in the AI’s answer.

Content Visibility and Brand Discovery in an AI-Driven Search

If AI Mode and similar generative search features become mainstream, how will prospects discover brands and content? There are two sides to this:

  • Decreased Visibility for Generic Queries: For broad, informational queries (the kind B2B buyers often search in early research stages), AI answers will likely curtail traffic. If someone asks “How to improve supply chain efficiency with AI” and Google’s AI provides a detailed answer citing 5 sources, the user may never visit any of those source sites – unless they want to double-check or dive deeper. Your insightful blog post or whitepaper might be distilled into a snippet within the AI’s response. In essence, Google’s AI becomes a gatekeeper of information, and your content’s role might shift from attracting a click to simply feeding the AI answer. As a result, many companies may see lower organic traffic for non-branded, informational queries. One early finding: non-branded keywords that trigger AI summaries saw about a 20% drop in CTR, while branded searches held up much better.
  • Importance of Brand and Authority: On the flip side, brand-driven searches and reputation become even more critical. If a user specifically searches for your brand or product (e.g. “Acme Corp cybersecurity platform”), they likely have intent to engage, and AI is less likely to interfere with that. In fact, branded searches rarely trigger an AI overview – only ~4.8% of branded queries did, in one analysis. And even when they do, those results can actually increase CTR by about 18.7%, presumably because the AI highlights the brand and reassures the searcher. The lesson: strong brands that people search for intentionally will continue to get traffic (often directly). But if your brand isn’t known, users might rely on AI to suggest options in a category, and you need to be on that list.
  • AI as the New Recommendation Engine: Think about how someone might ask an AI, “Who are the leading providers of data analytics software for retail?” This is a brand discovery question. In a traditional search, the user would get a list of results – perhaps a Gartner Magic Quadrant, some vendor blogs, a Quora thread, etc. They’d scan and pick some links to click, possibly discovering new vendors in the process. In AI Mode, the user might get a curated answer listing a few top vendors with brief descriptions (sourced from somewhere). Whether your brand gets mentioned in that answer could make a big difference. The AI will likely mention a handful of names (and cite sources). If you’re absent, you might be invisible in that research phase. If you’re present, the user might then ask the AI “Tell me more about Candidsky” – effectively letting the AI summarise your value prop. In either case, the initial discovery was controlled by the AI’s selection of which sources (or brands) to include.

In short, AI-driven search shifts some power from users to algorithms in terms of content curation. It’s similar to how featured snippets worked, but on steroids – now entire answers (with possibly multiple parts) are being curated. The role of SEO expands to AI optimization: ensuring that your content is not only ranking, but is also being picked up and accurately reflected by AI answers.

There’s also a dual impact on the marketing funnel: top-of-funnel educational content may see fewer direct visits (as AI summarizes it), while bottom-of-funnel or brand-specific queries might become relatively more important (as those still drive clicks or direct engagement). Some publishers are already adapting by targeting keywords that don’t trigger AI answers to preserve traffic. In a B2B context, that might mean focusing on very niche long-tail queries, proprietary research (that AI can’t easily summarize from multiple sources), or interactive content that doesn’t translate easily into a quick answer.

The Role of AI in Shaping Trust and Authority

Another implication is how trust and authority are conveyed in search results. When the AI provides an answer, the casual user might not distinguish which parts came from which source, or how reliable those sources are. They might just trust the amalgamated answer because it’s from Google. That could flatten the playing field in some cases – lesser-known sources might get included if they have the best info on a sub-question, benefiting from Google’s overall credibility. But it also means as a content producer, you’re increasingly reliant on Google’s AI to properly credit and convey your expertise.

Google has built in source citations (usually with a little annotation or link icon), and users can click to see the original sources. However, not all users will. Over time, we may need to measure success not just by clicks, but by brand mentions or visibility within AI answers. For example, if your brand is mentioned by name in an AI summary (perhaps because the AI pulled a quote or data from your site), that has some branding value even if no click occurs – it’s akin to being quoted by a respected publication. On the other hand, if the AI uses your information but only cites it as a tiny number (with no brand name visible until clicked), the value is more hidden. We’re essentially entering an era where Google’s AI might become the interface to your content for many users.

One more consideration: search queries themselves might get longer and more specific because users trust the AI to handle complexity. We might see fewer short queries like “supply chain AI trends” and more conversational ones like “What are the latest trends in AI for supply chain management and which vendors are leading in this space?” This means the question keywords and phrasing you optimize for could change. The AI will parse the intent regardless, but understanding how your audience might ask a full question can help you tailor content that directly answers it (improving the chance the AI chooses your content as a source).

In summary, B2B marketers must brace for a world where getting a click from Google is harder, and where being included in the answer (even without a click) is a new form of visibility. Search behavior is shifting from “find me a link to click” towards “give me the answer now.” Next, we’ll discuss how to adapt to this shift.

How B2B Marketers Can Prepare and Optimize for AI Mode

Facing these changes, what can B2B marketers and SEO professionals do? While we’re still early in this AI-in-search journey, some clear strategies are emerging. Here are actionable steps to help your B2B marketing team adapt:

1. Create Content That Answers Complex Questions (and Do It Better Than Anyone Else): With AI Mode fielding multi-part questions, it’s hunting for content that provides clear, comprehensive answers. Conduct research on the kinds of complex questions your target audience might ask at different stages of their journey. Then, ensure you have content that directly addresses those – be it in blog posts, guides, FAQs, or whitepapers. Structured, well-organized content is key. Use headings, bullet points, and concise explanations that the AI can easily parse and pull from. If you have authoritative, high-quality content that succinctly answers a tough question, Google’s AI is more likely to include it in the synthesised answer. In other words, aim to be the source that the AI “trusts” for your subject area. This might mean updating old content to add more depth or clarity, or creating new content that fills gaps in common questions.

2. Embrace Structured Data and Schema Markup: While AI Mode uses natural language processing to read webpages, providing machine-friendly cues can only help. Use schema markup for factual information (products, pricing, FAQs, how-tos, etc.). Structured data makes it easier for search engines to identify key facts or steps in your content. For instance, marking up a FAQ page could help Google’s AI directly grab the Q&A pair. For B2B, consider schema types like FAQ, HowTo, Product, SoftwareApplication, etc., where relevant. Also ensure your pages have clear metadata and descriptive titles – these might be used in the AI citations or suggestions. Google’s AI will “issue dozens of queries” in Deep Search model; having structured data might help your content be found in those auxiliary searches.

3. Optimise for Conversational Queries: Start incorporating the actual phrasing of questions in your content. This doesn’t mean you should write unnaturally, but think about adding sections that explicitly ask and answer common questions (even long, multi-clause questions). For example, an article might include an H2 that is a full question: “What are the security considerations when comparing Cloud vs On-Premise ERP?” and then directly answer it. This increases the chance that when a user poses a similar question to AI Mode, your content is seen as a direct match. Some SEO teams are mining tools like People Also Ask, forums, and using their own intuition to list out longer query strings. Keep in mind, Google’s own advice (from the Search Quality Rater guidelines) has always been to create content that demonstrates E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). In an AI-driven search, expert, authoritative content that directly satisfies informational needs will be highly valued. If you have subject matter experts, make sure their insights are captured in your content – unique expertise is harder for an AI to synthesize from generic info, so it stands out.

4. Focus on Original Research and Insights: B2B companies often have access to unique data – whether from your product usage, surveys, or industry research. Original research can be a magnet for AI citations because it provides value that generic content cannot. If your report contains a statistic like “67% of manufacturers plan to invest in AI by 2025,” an AI might quote that stat in an answer about industry trends (potentially citing your brand). Creating rich, insight-driven content (think: reports, case studies with data, expert interviews) not only attracts human readers but also positions your content as a primary source that AI might draw from. Also, if the AI summarizes that insight, a reader might click through to your site for the full context if it’s intriguing enough. Being the source of unique insights ensures that even as AI aggregates answers, your brand gets credit and interest for those insights.

5. Monitor AI Mode Results for Your Key Queries: Just as you monitor your search rankings, you should start monitoring how queries in your space are answered by AI Mode (and other AI search tools like Bing’s chat, ChatGPT plugins, etc.). Identify a set of representative questions a prospect might ask about your product/service or industry. Then use AI Mode (if available to you) to see what answer comes up and which sources are cited. This can be illuminating. You might discover that competitors’ content or third-party sites are being used while yours isn’t – which is a cue to improve your content. Or you might see your content is used but perhaps misinterpreted or lacking a key detail – a chance to update it.

Some companies are even tracking referral traffic from AI. For instance, if Google’s AI Overview or Bing’s chatbot includes a link to you, see if visitors are coming via those links (they often show up with certain query parameters or referrer data). While overall such traffic might be small now, it could grow. Staying informed on how AI presents information in your niche will help you adjust your strategy. Remember, “sustaining visibility on traditional search (in the face of zero-click results), and gaining presence in AI-driven discovery” is the dual challenge ahead. By actively monitoring and optimising for both, you can adapt more quickly than competitors.

6. Leverage Your Brand – Double Down on Brand Marketing: As noted, branded searches are less affected by AI summarisation and often still result in a direct click. That means building a strong brand presence can be a buffer against traffic loss. If a potential customer specifically searches for your company or product by name, they are likely further along the journey or have heard of you elsewhere. Strategies like thought leadership, PR, webinars, and community engagement can increase branded search demand. Also, when users do engage with AI answers, a strong brand can help ensure you’re one of the options they recognise. For example, if an AI lists “Option A, Option B, Option C” and one of those is clearly your well-known brand, a user is more inclined to follow up on that. Additionally, consider providing content or tools that encourage direct visits (like premium content via email signup, calculators, or interactive demos), reducing dependency on search. In essence, cultivate demand generation outside of search to counterbalance any dip in organic traffic.

7. Adapt Your SEO KPIs and Funnel Strategies: With AI mode altering traffic patterns, marketers might need to adjust what success looks like. If you notice certain informational pages losing traffic, it might not mean the content failed – it might be performing too well, feeding the AI answers. You may need to look at metrics beyond clicks: e.g., how often your content is cited by AI (if that data becomes available), or changes in branded search volume, direct traffic, and conversion rates. It’s possible that although top-of-funnel visits drop, the users who do click through are more qualified (because a casual searcher got their quick answer from AI, whereas someone who clicks wants detail or to engage deeper). Monitor lead quality and conversion rates from organic search – are they changing with the adoption of AI results? Also, be prepared to diversify your traffic sources. This is a cue to invest more in channels like LinkedIn, content syndication, or niche industry platforms where you can directly reach your audience. SEO isn’t dead by any means, but it’s evolving – so your playbook should expand accordingly.

8. Explore Emerging Tools and Collaborations: Keep an eye on how Google might allow businesses to interact with AI search. For instance, could there be a way to mark certain content for AI discovery, or feed Google with structured datasets via Google’s Knowledge Graph or other means? We’ve seen early moves: Google’s Search Labs is where these features roll out first – consider joining those if you can, to stay ahead. Additionally, look beyond Google: Microsoft’s Bing is integrating OpenAI’s GPT-4 in search, and they have plugins that can hook into external data. OpenAI’s ChatGPT can browse the web (and has plugins) where you might want to ensure your content is accessible. Being an early adopter of any tools that allow you to provide better data to AI (e.g., Bing’s IndexNow, or Google’s future AI-specific sitemaps if they emerge) could give you an edge. Also, don’t shy from using AI yourself – whether to analyse search results at scale, generate structured FAQs, or identify content gaps. Just as SEO practitioners adapted to voice search by creating Q&A content, adapt to AI search by possibly creating conversational content or even offering your own chatbot trained on your content (as some B2B companies are now doing for customer service).

In implementing these strategies, keep the user’s experience central. Google’s motivation with AI Mode is to serve users better (so they stay in Google’s ecosystem). If your strategy aligns with genuinely helping users get information seamlessly – whether on Google or on your site – you’ll be in a stronger position. As one industry analysis put it, companies now need to “sustain visibility… and [gain] presence in AI-driven discovery” and that may entail “optimising content to be favored by AI summarisers… and focusing on unique content that draws users in even when AI provides a quick answer“. In other words: earn the AI’s favor with great content, and give users compelling reasons to click through when it counts.

Expert Insights and Examples from Google I/O

To ground this in reality, let’s look at a couple of examples and expert observations that illustrate the impact of AI Mode:

  • Google’s Own AI Mode Demo – A Summer Camp Search: At I/O, one live demo showed how a parent could use AI Mode to “help me research affordable summer camps within a 10 min drive for my 9 and 6 year old” with a slew of specific requirements (camp dates, pricing, after-care, activities like STEM or sports, etc.)
  • This single query would traditionally require visiting multiple camp websites, reading reviews, maybe a spreadsheet to compare – a very involved research task. AI Mode’s Deep Search handled it by breaking the query down: finding local camps, pulling in each camp’s details, comparing them against the criteria, and then producing a structured answer recommending the best fit camps (with reasoning). For a B2B parallel, imagine a prospect asking: “Help me compare three project management softwares for a 50-person company, including pricing, key integrations, security certifications, and user feedback scores.” AI Mode could potentially do the legwork of scanning datasheets, pricing pages, and reviews to deliver a summary. This illustrates both the power and the challenge – the user saved a ton of time, but the vendors of those products might not get a direct visit unless the user wants to verify details. It underscores why your content (pricing, integrations, case studies) needs to be easily digestible for an AI to pick up, and also accurate and persuasive enough that if a user sees it summarized, they’re intrigued to learn more on your site.
  • Industry Expert Commentary – Google’s Strategic Shift: Many SEO and digital marketing experts are closely watching Google’s AI push. Industry veteran Barry Schwartz noted Google’s aggressive promotion of AI Mode on the search homepage, interpreting it as Google’s attempt to “get more people to try AI Mode” and familiarize them with this new way of searching. Another expert, Glenn Gabe, commented on how AI Mode is “expanding” and that the new interface is getting prime placement, which he sees as Google doubling-down on AI despite early hiccups. This strategic emphasis suggests that AI Mode (and its successors) aren’t likely to disappear – even if there are kinks to work out (remember the infamous “glue on pizza” AI suggestion that Google’s earlier AI Overview produced). Google appears committed to iterating and making AI a core part of search. For marketers, the takeaway is to lean into this trend rather than hoping it’s a short-lived experiment. Just as mobile-first indexing or the rise of video search required SEO adjustments, AI-driven results require attention and adaptation.
  • SEO Community Adaptation: The SEO community is already sharing tactics and observations from the first year of Google’s AI in search. One lesson from publishers is to identify queries that trigger AI answers and decide whether to compete there or pivot strategy. Some are choosing to focus on content areas that still drive clicks, while others are trying to win the AI snippet knowing that even reduced traffic can be offset by the authority of being featured. B2B marketers might similarly segment their content: for some informational pieces, the goal might shift to brand visibility via AI (even if clicks drop), whereas for other content (say, a high-value lead magnet), you might target channels where you can still draw the user directly. It’s not one-size-fits-all; it’s about understanding where AI will intercept your audience and where it won’t, and tailoring your approach accordingly.
  • Competitive Landscape and Opportunities: It’s worth noting that Google isn’t the only player. Microsoft’s Bing (with OpenAI) was actually first to integrate a chat mode in search, and tools like ChatGPT (with web browsing) and startups like Perplexity.ai are also vying to be the go-to AI research assistant. Google’s AI Mode is partly a response to these, to “not cede search market share”. For marketers, this means your SEO/SEM strategy might broaden to multi-platform search optimization. For instance, optimizing for Bing’s AI chat (which might have different preferences or citation styles) or even creating content that is friendly for voice assistants. The companies that stay ahead will be those who keep a pulse on all these channels. The good news is that many principles remain consistent: high-quality, relevant, trustworthy content is the common currency that all these AI systems trade in.

Looking Ahead: The Future of AI-Powered Search and Staying Ahead of the Curve

Google’s AI Mode is a major milestone in search evolution, but it’s also just the beginning. We can expect rapid developments in the coming months and years. Here are some forward-looking points and how B2B brands can stay ahead:

  • AI Search Will Become the Norm: Just as mobile browsing quietly overtook desktop, AI-assisted search could become an everyday default for users. Today it’s a “Mode” you toggle on, but tomorrow it might be the standard experience for many query types. Google has already indicated that AI Overviews (the summary snippets) are moving out of the experimental phase into 200+ countries. AI Mode, while experimental now, could follow suit once refined. B2B marketers should assume that in the near future, a significant portion of their audience will interact with their content via some AI intermediary. Prepare your content strategy with this in mind – it’s not a fringe scenario, it’s the future of search as Google sees it.
  • Continued Improvements (and Challenges) in AI Accuracy: Early AI search results have sometimes been shaky (from hallucinated facts to odd advice like the aforementioned glue suggestion). Google and others are investing heavily in improving factual accuracy and grounding answers in reliable sources. As models like Gemini advance (Google’s next-gen AI models), we’ll see more accurate and multimodal understanding. This may mean AI can parse videos, PDFs, or even databases for answers. B2B companies often have valuable content in webinars, PDFs, etc. – consider making that content more accessible (transcripts, HTML versions, or structured summaries) so future AI can incorporate it. But also, keep an eye on misinformation. If your industry is subject to frequent inaccuracies or outdated info, it’s wise to proactively publish correct, up-to-date content. That not only serves your audience but also trains the AI on the right data. We might also see Google give users tools to verify AI answers or provide feedback. B2B marketers could encourage their audience to engage critically – for example, if an AI summary about your product is missing something, having comparison pages or FAQ pages that set the record straight could indirectly help correct the AI over time.
  • Integration of Ads and Sponsored Content in AI Results: Google’s business is advertising. It’s likely figuring out how to integrate ads into AI Mode without ruining the user experience. We might see sponsored answers or “AI curated” product showcases (somewhat like how Google Shopping ads appear). Already, in the pilot phase of SGE (Search Generative Experience), Google experimented with displaying ads above and below the AI answers. For B2B, this could mean new opportunities (or competition) for visibility. Imagine an AI answer about “top cybersecurity solutions” that includes a clearly labeled sponsored recommendation. Marketers should stay informed about these monetization changes. It could create new ad formats to engage users who skip traditional ads. Also, if fewer users click through organically, you might need to allocate more budget to paid campaigns to maintain visibility. On the flip side, if you’re the content source for an AI answer, that’s effectively free visibility that might rival an ad – a good incentive to be the best answer out there!
  • Greater Personalization and Contextual Results: As mentioned, Google is dipping its toes into personalized AI results by integrating with user data (Gmail, etc.) It’s possible that in B2B contexts, Google might integrate other signals – perhaps content from Google Drive, or Google Workspace accounts (for enterprise users), to tailor results. If a user is logged in with their work account and searching for solutions, could Google’s AI know which company they work for and adjust results? It’s speculative, but not implausible (with privacy safeguards). This means user context might influence whose content is shown. If Google knows a user is in a certain industry or existing tech stack, the AI might favor content that’s relevant to that context. B2B marketers should thus consider more personalized content as well – for instance, industry-specific landing pages or use-case pages that might get surfaced when context matches. Also, building trust so that users want to connect their data is key. If your content or service is something users might integrate (like a plugin or data source for AI agents), that could be an avenue to explore down the road.
  • Rise of Direct AI Engagement – New Channels: We might also see users going directly to AI platforms for certain queries, bypassing search engines. For example, a procurement manager might ask ChatGPT (via a plugin) to find and compare vendors, or might use a voice assistant to do a quick Q&A instead of typing it. Ensure your digital presence extends to these emerging channels. This could mean providing APIs or data feeds that these AI systems can consume. Some forward-thinking companies are offering knowledge base integrations with AI (so that when asked about them, the AI has an updated reference). While standards are still evolving, staying flexible and ready to integrate with AI platforms (whether it’s allowing your site to be scraped, or publishing content on structured formats) will help. Essentially, think of AI platforms as a new distribution channel for your content. Just as social media became a channel, now AI is one – people won’t just find answers on a webpage, they’ll find them via a chatbot or AI agent.
  • Human Touch and Trust Building: In an AI-saturated search landscape, the human element can become a differentiator. AI might handle facts and basic queries well, but B2B decisions often involve trust, emotion, and nuance. Marketers should continue to emphasise human stories, customer testimonials, and community building. Those are things an AI summary can’t fully replicate. If your content strategy includes fostering a community or delivering experiences (like interactive webinars, live chats, etc.), you create touchpoints that go beyond a quick answer. Think of AI as handling the commoditised info – you should aim to provide value that isn’t commoditised. This might also lead to a renaissance of brand content: podcasts, videos, and events where people can connect with your brand on a more personal level. The AI can serve up data, but humans connect over stories and relationships – and B2B deals, being high-consideration, will always involve that element. Use AI to augment your reach and efficiency, but don’t lose the human voice and authenticity in your marketing.

Staying ahead in this fast-changing environment means embracing continuous learning and experimentation. Encourage your team to pilot new content formats, track performance closely, and even collaborate with your tech/IT folks to ensure your site is technically ready for AI crawling and parsing. Keep up with Google’s announcements (e.g., follow the Google Search Liaison updates, SEO news sites) because the best practices for AI SEO will continue to evolve. The companies that treated SEO as a strategic priority in the early 2000s reaped huge benefits; now, the companies that treat AI-search optimisation as a priority will have the edge in the coming years.

Conclusion: Thriving in the Era of AI Search

Google’s AI Mode in Search represents a transformative leap in how information is discovered and consumed. For marketing decision-makers at B2B companies, it presents both a challenge and an opportunity. The challenge lies in adapting to a world where algorithms might answer your buyers’ questions before those buyers ever visit your website – potentially reducing traffic and control over the narrative. But the opportunity is that those same algorithms need content and expertise to fuel their answers, and that’s where you can shine. By producing authoritative, high-value content (and structuring it for AI consumption), you can become a go-to source that the AI relies on, thus staying visible in the conversation.

The strategic takeaway is clear: SEO and content strategy are no longer just about ranking, but about relevance and presence in an AI-driven context. Marketing leaders should foster a mindset of agility – monitor the data, listen to expert insights, and be ready to pivot tactics. As we’ve discussed, that could mean shifting focus to brand building, re-optimising content for conversational queries, diversifying traffic sources, and keeping technical SEO sharp for AI crawling. It also means educating your organisation: sales and customer success teams should know that prospects might be coming in with AI-curated knowledge, and marketing teams might need to collaborate more with data/IT teams to feed the right information to AI channels.

In this new landscape, those who experiment and learn will outpace those who wait. The fact that Google is putting AI Mode front and center (even swapping out a legacy feature like “I’m Feeling Lucky” for it in tests) signals that this is a long-term direction, not a short-term gimmick. And with competitors like Microsoft and OpenAI pushing their own AI search solutions, the entire search ecosystem is moving this way.

The silver lining is that while technology changes, the core of marketing remains the same: understand your audience and deliver value. AI Mode is simply pushing us to deliver that value in new ways. By staying informed, being strategic, and keeping a user-first (and now AI-aware) mentality, B2B brands can not only survive in the era of AI search – they can thrive, building authority and trust at scale.

Bottom line: Google’s AI Mode is here, and it’s redefining search. It’s time to embrace the change. As you adapt your strategies using the insights and tips above, you’ll position your brand to be discovered in the new AI-driven journey – ensuring that when your prospects ask the AI, it’s your story and solution that comes through. The companies that adapt now are the ones that will lead in the next chapter of B2B digital marketing. Are you ready for AI-driven search? The answers are already out there – let’s make sure they include you.

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