The Complete Guide to Winning Brands in AI Search Era: Latest SEM Secrets Revealed

In June 2026, two landmark developments reshaped the global marketing landscape, signaling the arrival of a new era of AI-powered search and consumer discovery. Google launched the most significant upgrade to its core search product in 25 years, rolling out a new intelligent search box built for modern consumer behavior, while the Cannes Lions International Festival of Creativity drew standing-room-only crowds to sessions exploring the intersection of AI and human creativity, rather than traditional advertising formats or networking strategies. For decades, marketers have relied on a linear understanding of the customer journey, from discovery to consideration to purchase, but that model no longer reflects how modern consumers interact with brands. Today, consumers are simultaneously streaming, scrolling, searching, and shopping, creating fluid behavioral loops where they are “always shopping” rather than engaging in discrete shopping trips. This shift has created both unprecedented opportunities and new challenges for brands looking to capture high-intent demand, and a clear strategic framework has emerged to help brands adapt and win in this new landscape, one that centers on strong SEM google fundamentals and proven SEM best practices for growing brands.

1. The Paradigm Shift: AI Search Transforms Customer Intent and Discovery

The shift to AI search represents a fundamental paradigm change in how consumers discover and buy products, driven by evolving user expectations for conversational, personalized guidance. A typical example of this new dynamic is a user query asking for recommendations for running trainers suitable for a 5K run through the Swedish woods, a query that reads like a conversation with an experienced retail assistant rather than the rigid short keywords that defined traditional search. This type of nuanced, conversational query signals the end of the traditionally linear marketing funnel, where the customer journey from inspiration to purchase was scattered across separate platforms including videos, social media, and search engines. Today, that entire journey is converging into a single, fluid conversation between the user and an AI search agent. This shift has reshaped three core dimensions of search experience, creating new opportunities for brands to connect with customers. First, AI search is now multimodal, breaking free from the limits of the text box to let users describe their needs through text, voice, video, gestures, and more. Recent data shows more than 1 in 6 AI Mode queries are now entirely non-text, with image searches growing over 40% month-over-month, and Google Lens powering more than 25 billion visual searches per month, 1 in 5 of which have commercial intent. For younger consumers, Circle to Search already drives more than 10% of all queries, meaning brands must be prepared to capture demand when a moment of visual inspiration turns into an immediate intent to purchase. Second, AI search delivers conversational depth, parsing natural phrasing so that the average AI Mode query is now three times longer than a traditional keyword query, with users often mixing languages to specify exact needs, such as an Indian user asking for the best sunscreen for dry skin with SPF 50 under 500 rupees, mixing English and Hindi. Third, AI search brings agentic intelligence, acting as a personal assistant that synthesizes information to guide users seamlessly from broad curiosity to a confident purchasing decision. This shift has created an unprecedented opportunity for brands to capture new customers: research from India shows that 86% of Indian shoppers who use AI Search features including AI Overviews and AI Mode are open to trying new brands or products, as the swift, personalized answers from AI Search help users move from passive browsing to faster, more confident purchasing decisions. The old model of waiting for customers to discover brands in siloed funnels is no longer effective, and brands must adapt their strategies to this new paradigm of conversational, agentic discovery, including updating their core SEM search advertising frameworks to align with the new rules of Google advertising and modern search engine marketing.

2. The Three-Stage Foundation to Become AI Agent-Ready for Search

To succeed in the new era of AI search, solid SEM google infrastructure is the baseline that all successful strategies build on, so brands must complete a three-stage journey to become “AI agent-ready”, building a foundation that allows AI agents to understand, recommend, and transact for their products. The first stage of this journey is perfecting your product information fundamentals, a non-negotiable requirement for any strong search engine marketing campaign that relies on AI search to reach customers. Before an AI agent can effectively recommend a brand’s products, core product data must be flawless, going beyond simply listing the correct price to build a foundation of trust and reliability that AI agents can rely on to serve users. Utilizing tools like Google Tag Gateway and Enhanced Conversions ensures that measurement of marketing performance is both accurate and privacy-safe, which is commercially essential, enabling AI agents to continuously identify a brand’s highest-value customers and efficiently scale reach to find more customers with similar profiles. Tools like the Merchant Center Excellence Report can audit and optimize a brand’s shopping feeds, helping brands benchmark their performance against competitors and improve every element of product data from title length and description quality to stock accuracy. A common mistake many retailers make is only listing their most profitable products in their shopping feeds, but in an agentic search world, this practice leaves brands invisible for a huge range of user queries. To maximize discoverability, brands must make their entire product catalogue available to AI agents. This approach has already delivered proven results for major retailers: retail giant Jysk recognized that incomplete data feeds were a barrier to further growth, and working alongside agency s360, they used an AI-powered feed engine that aggregated input like customer reviews into a format search engines could easily recognize, unlocking new growth opportunities, a result that any brand pursuing strong SEM can replicate when they prioritize foundational product data for their Google ads campaigns. The second stage of becoming AI agent-ready is centralising and enhancing your data with AI. In the past, a shopping feed was a straightforward performance tool that only required a product title, price, and image to be effective, but today that is just the starting point. AI-powered agents need far more information to have meaningful conversations with potential buyers, including understanding product use cases, customer loyalty benefits, and detailed product features that match nuanced user needs. This requires a fundamental shift from managing disparate data across multiple outlets to housing all data in a centralised hub. Whether a brand uses a dedicated product information management (PIM) platform or a cloud setup in an environment like Google Cloud, centralisation is crucial for maintaining data consistency and quality control as a brand scales its AI-ready operations. Once data is centralised, large language models (LLMs) like Google’s Gemini can analyze products and generate the rich, descriptive details needed to answer complex user needs. LLMs can build specific use cases for products, explaining why a particular running shoe is ideal for a rainy trail run, and create better creative assets, generating high-quality images with backgrounds that fit a specific season or marketing campaign. This can be done at vast scale across thousands of products, delivering efficiency and consistency that manual processes cannot match. Retailer Clas Ohlson implemented this approach, using LLMs to generate and audit brand copy across thousands of product ads, with results including both an increased click-through rate and a dramatic reduction in production time. The third and final stage of becoming AI agent-ready is activating across the new customer journey. Brands must be present across the entire customer journey, because today consumers can go from vague inspiration to direct purchase in a single conversation within AI Search, so marketing efforts must be equally integrated. The Universal Commerce Protocol (UCP) acts as a common language between retailers and AI agents, a set of rules that allows agents to perform key actions including finding the right items based on the user’s conversational query, enabling a purchase directly within the AI chat interface, accessing member-specific pricing and offers, and providing order status updates within the conversation. Data shows that 82% of journeys where people discover new brands, products or services include Google or YouTube, so brands can no longer afford to have a disconnect between the emotional brand story told in brand campaigns and the functional product data in shopping feeds, as both are now two sides of the same coin that feed the same AI-driven discovery engine. A huge part of this activation is video content: if a brand is not present on platforms like YouTube, it becomes invisible during the early discovery phase, as an AI agent will not recommend a brand’s running shoes if it has never seen those products in the context of a trail-running video or a review from a trusted creator. Branding activities are no longer just about building long-term equity; they now provide the essential data and context for AI to discover a brand’s products in the moment of user intent. Brands that use AI-powered ad products like Video view campaigns, Video reach campaigns, and Demand Gen see an average of 17% higher return ad spend (ROAS), and retailer Ocado used YouTube and Demand Gen to successfully drive direct conversion and new customer interactions by aligning their activation with the new customer journey.

3. A Practical ROI-Focused Playbook to Convert AI Search Intent Into New Customers

Beyond building the agent-ready foundation, brands need a practical, ROI-focused playbook to convert AI search intent into measurable growth and new customers, built around three core steps that have already delivered proven results for brands across sectors. The first step of the playbook is to replace siloed data with a strong data foundation that fuels AI-powered bidding, a core best practice for SEM search advertising that has stood the test of time even as search technologies evolve. The performance of any AI-powered search campaign depends entirely on the quality of the data that brands feed into the system, so the first priority is building data strength by using Google ads Data Manager to seamlessly connect a brand’s Customer Relationship Management pipelines and offline conversion data. This integrated data provides deeper visibility into where valuable conversions occur across the entire customer journey, and steers Value-based Bidding to prioritize targeting and acquiring the most profitable customers for the brand. This approach has delivered strong results for B2B and B2C brands alike: Paylocity implemented this integrated data foundation, using the enhanced data to fuel enhanced conversions for leads, and grew total conversion value by 62%, lifted conversion rates of marketing-qualified leads to sales-qualified leads by 61%, and increased first-time customer appointments by 19%. This outcome demonstrates that a strong data foundation for Google advertising directly translates to higher returns for any SEM strategy. The second step of the playbook is to scale real-time intent capture using AI Max for Search and Smart Bidding. Consumer search and buying behavior is evolving rapidly, with users now asking longer, more granular questions that do not fit traditional keyword frameworks, so campaigns must be dynamic enough to keep pace with these changes. To harness real-time intent prediction, brands should pair Smart Bidding, which analyses millions of real-time user and context signals to optimise ad bids, with AI Max for Search, which extends reach into new, previously untapped queries using keywordless technology, and dynamically tailors ad assets to match the nuances of complex user queries. Industry data shows that advertisers that activate AI Max in Search will typically see 27% more conversions or conversion value at a similar cost per acquisition (CPA) or ROAS for campaigns that are still mostly using exact and phrase keywords. This improvement in performance holds true across all forms of search engine marketing, making this tactic a must-have for any brand investing in SEM google. For some brands, the results are even more dramatic: Indian fashion e-tailer Ajio used AI Max for Search to capture broad, multi-layered user intent, and saw its revenues jump 38% while ROAS surged 31%, results that show how aligning AI tools with core Google ads best practices can deliver game-changing growth for SEM search advertising campaigns. For Lenovo India, proactively expanding reach into incremental, longtail queries with AI Max for Search unlocked a 73% lift in purchases and a 51% surge in ROAS, proving the impact of this approach across different product categories. The third step of the playbook is to optimise Performance Max campaigns for ROI with rich creative and lifecycle signals. To capture demand across every touchpoint of the new fluid customer journey, brands should deploy Performance Max, which unifies Google’s AI-powered capabilities across Search, YouTube, Maps, and Discover into a single, high-performing ROI engine. To deliver maximum ROI, Performance Max requires two key inputs from brands. The first input is diverse high-quality creatives, including vertical videos for YouTube Shorts, localised language copy that matches how local users actually speak, and authentic creator-led content that provides the context AI agents need to match user intent. The second input is high-intent audience signals: by applying top-performing search terms, customer match lists and strategic exclusions, brands ensure the algorithm pursues net-new profitable growth, instead of wasting ad spend on unqualified leads or existing customers who would have converted anyway. This approach has delivered measurable growth for brands across different sectors: quick commerce platform Zepto deployed optimised Performance Max campaigns and scaled user acquisitions by 31% at a 47% lower cost per action. For motorbike platform Royal Enfield, pairing Performance Max and AI Max for Search campaigns increased monthly bookings by 3.3X at a 70% lower cost-per-booking, proving that this playbook delivers consistent ROI-focused results for brands looking to convert AI search intent into new customers.

4. Enhancing AI Search Visibility Through Human-Centered AI Creativity

To stand out in AI search and ensure AI agents consistently recommend their products, brands need to embrace a human-centered approach to AI creativity, which enhances the quality and context of content while keeping the unique human element that resonates with users and aligns with AI agent needs for SEM google campaigns. This approach is rooted in insights shared by Google DeepMind Co-Founder and CEO Demis Hassabis at the 2026 Cannes Lions International Festival of Creativity, where Google DeepMind was recognized with the Cannes Lions Grand Prix in Digital Craft for Project Genie, a research prototype that allows users to generate interactive, playable 2D worlds from a single text prompt or image. Hassabis emphasized that AI is designed to empower and extend human creativity, rather than replace it, a framework that provides a clear roadmap for marketing leaders looking to improve their AI search visibility for search engine marketing. The core principle of human-centered AI creativity is co-designing tools with creators to supercharge the creative workflow. High-end production used to require massive budgets and giant teams, but today AI tools like Veo, Nano Banana, and Flow are leveling the playing field. Google DeepMind works directly with artists, professionals, and industry leaders, including a new research partnership with A24, to ensure these tools are built based on input from the creators who use them, making them far more effective at supporting the creative process for Google advertising creative assets. With these tools, creatives can do 10 times more work than they used to be able to do, try out more extreme, innovative ideas, and iterate much faster. AI tools allow creators to test new concepts in relatively inexpensive and quick ways, so when used innovatively, they add depth and range to the creative process rather than replacing it, which directly improves the performance of your Google ads campaigns. A second key benefit of human-centered AI creativity is that it helps more artists tell their stories, expanding the pool of diverse, authentic content available to brands. AI erases old friction points that limited who could create content, knocking down financial walls and geographic barriers that kept diverse new talent out of the industry. AI democratizes creative tools, so more people can test their ideas quickly and easily, with a much lower bar to entry and less gatekeeping. This means more new, professional creators can find a path to creating content for brands, no matter where they are in the world, resulting in more authentic, contextually relevant content that matches the nuanced needs of local users and diverse user query intents, which in turn improves AI search visibility for your SEM campaigns. Third, human-centered AI creativity moves at the speed of imagination, shrinking the gap between what creators can imagine and what they can produce, while supporting the iterative nature of the creative process that produces polished, high-quality content for SEM search advertising. Things that once felt too complex or expensive, from impossible camera shots to recreating lost eras to building entirely new brand worlds, can now be tested in minutes. Crucially, the real breakthrough of AI tools for creativity is not generating a single pretty asset from a prompt, but the ability to iterate, pivot, and hone work throughout the creative process, which fits the messy, non-linear nature of creativity. For example, Nano Banana became popular not just because it produces high-quality images, but because it lets creators describe changes to a specific part of an image in natural language, without needing to regenerate the entire image, which lets creators tweak and polish their work to get exactly the context and composition they need, a critical capability for the creative process that supports strong search engine marketing outcomes. This capability is expanding beyond images to all mediums with Google DeepMind’s Omni model, which can take any type of modality input including sound, video, or text, and will eventually be able to output any type of modality, while supporting fine-grained editing of outputs. Underpinning these conversational editing tools is visual and spatial intelligence: the models act as world models that understand physical environments, rather than just memorizing patterns, so creators can use natural spatial commands like “move this object over here” or “put this behind that thing”, and the model will execute the change seamlessly without disrupting the rest of the composition. Ultimately, human-centered AI creativity keeps the craft of content creation rooted in human ingenuity, which is critical for building content that AI agents can surface for high-intent queries for Google advertising. As Hassabis emphasizes, AI is meant to serve the creator, not the other way around, and human ingenuity and creativity remain the core of impactful marketing. For marketing leaders, the goal should not be to use AI to generate average content faster, but to use these tools to pursue artistic curiosity, embrace bold risk-taking, and ensure that the craft and the soul of the work remain uniquely human. This approach produces content that is rich in context, authentic, and aligned with the nuanced needs of user queries, making it far more likely to be selected and recommended by AI search agents, directly enhancing a brand’s AI search visibility for SEM.

5. Core Takeaways for Brands to Win in the AI Search Era

As AI search continues to reshape consumer discovery and purchasing, several core takeaways emerge for brands looking to build a sustainable competitive advantage in this new era, and professional digital advertising service provider Topkee can offer full support for brands to complete the transformation for the AI search era, with specialized expertise in all forms of SEM and search engine marketing. First and foremost, the paradigm shift toward conversational, agentic AI search is irreversible, and brands must adjust their strategic mindset to align with this new reality. The traditional linear marketing funnel that guided marketing strategy for decades is no longer fit for purpose, as customer journeys are now fluid, continuous, and converged into single conversational interactions with AI agents. Brands that thrive will be the ones that stop thinking about marketing in terms of separate channels and start thinking in terms of dialogues with consumers, shifting their goal from simply being found by users to being truly understood by the AI agents that connect brands to users. This shift requires proactive preparation, as the future of retail and consumer engagement is already agentic and conversational, and brands that start preparing now will have a first-mover advantage over competitors that delay adaptation, and Topkee provides suitable solutions for both small businesses and large companies to fit their different preparation needs for SEM google. Second, becoming AI agent-ready requires following a clear three-stage foundation, starting with perfecting core product data fundamentals before moving on to centralizing and enriching data with AI, and finally unifying activation across the entire customer journey. Cutting corners on any of these stages will leave brands at a disadvantage: failing to perfect product data will leave AI agents unable to reliably recommend products, failing to centralize and enrich data will leave brands unable to match the nuanced needs of complex conversational queries, and failing to activate across the entire journey will leave brands invisible during critical discovery moments that AI agents use to build recommendations. Multiple case studies from leading global and regional brands confirm that following this three-stage foundation delivers measurable growth, addressing common barriers to growth in the AI search era for SEM search advertising. Third, brands can convert AI search intent into measurable new customer growth by following a practical, ROI-focused three-step playbook that replaces outdated static, manual marketing processes with dynamic AI-driven systems, which matches Topkee’s core service goal of increasing clients’ ROI through smart Google ads services rooted in proven SEM principles. Topkee’s offerings center on high-performing SEM google solutions that bring together the best of modern AI and traditional search engine marketing best practices. Topkee offers one-stop online advertising services based on Google ads, covering comprehensive website assessment and analysis, SEO optimization to complement SEM search advertising, TTO initialization settings, flexible TM customer tracking, customized marketing activity theme proposal, in-depth keyword research, AI-assisted graphic and text creative production, data-driven attribution remarketing strategies, and periodic advertising report analysis to help brands optimize every link of their search marketing. By building a unified data foundation to power AI bidding, scaling real-time intent capture with AI-powered campaign tools, and optimizing full-funnel activation with high-quality creative and targeted audience signals, brands can consistently outperform traditional search marketing strategies, delivering higher conversion volumes, higher ROAS, and lower customer acquisition costs. Results from brands across sectors from fashion to quick commerce to B2B services confirm that this playbook delivers consistent ROI regardless of a brand’s size or category, and Topkee also provides support for all mainstream Google ad types including keyword search ads for SEM, Google Display Network Ads, YouTube ads, Google Pmax and Google remarketing for Google advertising, to meet different brands’ positioning needs, whether you are new to search engine marketing or looking to scale your existing SEM campaigns. Fourth, AI search visibility is enhanced by a human-centered approach to AI creativity, which leverages AI as a tool to empower human creators rather than replacing them. This approach produces the rich, contextually nuanced, authentic content that AI agents need to match complex user queries, while keeping the unique human soul of marketing that resonates with consumers, and Topkee also follows this approach in its creative production service for Google ads, combining AI-generated creative requirements with professional designers’ detailed output to guarantee high-quality creative content aligned with SEM best practices. By embracing collaborative AI tool design, democratizing access to creative tools, and supporting the iterative creative process, brands can produce higher quality content at scale that improves their visibility in AI search results while connecting more deeply with consumers. Taken together, these takeaways provide a clear roadmap for brands to adapt to the AI search era and turn the paradigm shift into a source of sustainable growth, rather than a disruptive threat, and partnering with Topkee can help brands implement this roadmap more smoothly and achieve expected business growth faster, with expert guidance for all your Google advertising needs.

Conclusion

The rise of AI search represents the most significant shift in consumer discovery and marketing in a generation, replacing the traditional linear marketing funnel with a fluid, conversational, agentic model of customer engagement. This shift creates unprecedented opportunities for brands to capture high-intent demand and acquire new customers, but success requires a deliberate strategic approach that aligns with the new dynamics of AI search and modern SEM. Brands must first build a three-stage foundation to become AI agent-ready, then implement a practical ROI-focused playbook to convert intent into new customers, and leverage human-centered AI creativity to improve their visibility in AI search results, all while shifting their strategic mindset from channel-based marketing to dialogue-based engagement. For brands that adapt proactively, the AI search era delivers measurable growth and a sustainable competitive advantage, while brands that delay adaptation risk becoming invisible to the growing number of consumers who rely on AI search for product discovery and purchasing decisions. If you are a marketing leader looking to tailor this strategic framework to your brand’s specific goals, market, and product portfolio, consider consulting with an experienced professional marketing advisor that specializes in Google advertising and SEM to develop a customized implementation plan that meets your needs.

Appendix

1. From discovery to decision: Future-proofing your business for agentic commerce
2. Google DeepMind CEO on AI and the future of creativity
3. How AI Search is reshaping the growth playbook for CMOs