This post is part of a series highlighting the chapters of our Top Franchise Digital Marketing Trends 2026 report, designed for franchise executives, marketing leaders, and agency partners to anticipate what’s next and act on it. If you would like to download a FREE copy of our report, please click here.
Be sure to check out the other posts in our series:
If you are interested in learning more about this topic, check out our 2026 Playbook for Franchises: Competing in AI Search to read alongside this post.
The End of the SERP as We Know It
For nearly two decades, marketers have fought to rank their companies at the top of the search engine results page (SERP). However, the emergence of generative AI has transformed how users find, evaluate, and act on information, which we expect will accelerate through 2026. The familiar model of keyword queries and ranked listings is giving way to a “zero click” experience that amalgamates information from across the web in a single, comprehensive answer.
Franchise executives must understand that this isn’t just a change in interface; it’s a fundamental shift in technology that is fueling new consumer behaviors. Forward-looking companies that are already adapting their search optimization strategies to accommodate AI-based search are the ones who will see success in 2026 and beyond.
What To Expect in 2026
Search and discovery are undergoing the most profound transformation since the early days of Google. What was once a predictable race for keyword rankings has evolved into a dynamic system powered by artificial intelligence that interprets, summarizes, and even acts on behalf of the user. By 2026, generative and agentic AI will shape how consumers find, evaluate, and purchase almost everything, from local services to global brands. The familiar search results page is giving way to conversational answers, visual interactions, and intelligent assistants that can complete entire transactions without a single click.
For franchise organizations, the coming year will reward those who modernize their digital infrastructure, align data across all locations, and design content that machines can understand as easily as people. Those who delay will see their online visibility and local market share quietly decline as AI systems favor competitors with faster, cleaner, and better-structured data.
The following sections outline the three major shifts redefining discovery in 2026 and what franchise marketers can do to remain visible, discoverable, and relevant in a world shaped by artificial intelligence.
From Links to Answers
When Google introduced AI Overviews in 2024, the search landscape quietly entered a new era. Initially, only a limited subset of queries, such as complex questions, product comparisons, and informational topics, triggered AI-generated summaries. But by 2026, it is expected that more than 50% of global searches will return some form of AI-based answer, and that percentage continues to grow each quarter.
Instead of displaying a list of clickable blue links, AI Overviews surface a single, conversational response at the top of the results page. These summaries blend structured data, product information, and third-party reviews into what feels like a definitive answer. They pull from across the open web, including corporate sites, review platforms, local listings, and even video transcripts, to create what analysts refer to as “zero-click experiences.”
Not surprisingly, the introduction of AI Overviews has led to a decrease in clicks on the SERP and a reduction in traffic to websites. A 2025 analysis by Pew Research found that the likelihood of a person clicking one of the search results links decreased by 47% when an AI Overview was included. In addition, the study found that the links associated with the AI Overview itself were only clicked 1% of the time.
The same study found that longer searches and searches that start with a question word were far more likely to trigger an AI Overview. This means that websites that historically have ranked well for “what”, “who”, “which”, “where”, “when”, “how” and “why” types of searches are being disproportionally impacted by the prevalence of AI Overviews. Essentially, companies that historically had strong SEO are seeing a greater impact to their traffic than traditionally poorer performers.
on AI Overviews
The end result is that as of late 2025, most companies are seeing a decrease in organic search traffic to their websites between 30% to 60% due to AI-based search.
Rather than lamenting their decline in website traffic, forward-thinking companies are pivoting their search optimization approach to increase visibility in AI Overviews and other AI search platforms such as ChatGPT, Perplexity, Claude, and Gemini. Generative engine optimization (GEO) is the discipline of positioning your company’s content and data to be included as part of the answer without your brand necessarily being mentioned and without users clicking through to your website.
For franchise organizations, this requires a significant change in mindset. Search optimization has historically been focused on generating website clicks, but optimization for AI-based searches is more about gaining visibility and positioning your company as an authoritative leader in your field.
Multimodal by Default
Search is quickly becoming an experience that spans voice, image, and video. The rise of multimodal search, where users interact via voice, camera, or video overlay, has fundamentally redefined what discoverability means. Increasingly, consumers are not typing queries; they are showing, speaking, or tapping their way to answers.
According to Google, nearly one in three global searches now begins with something other than typed text. This includes spoken questions (“find a restaurant near me that’s open now”), visual prompts (using a phone camera to identify a product or landmark), and contextual actions like pausing a short video and tapping to learn more.
Voice remains the most mature modality within this shift. Statista’s 2025 Global Voice Report found that 27% of all mobile users and 52% of smart speaker owners use voice commands weekly for local intent searches such as finding store hours, nearby services, or menu options. Meanwhile, Comscore predicts that by 2026, over 8 billion voice assistants will be in use worldwide, which is double the number from 2020.
The next frontier is visual discovery. Platforms like Google Lens, TikTok, and YouTube Shorts are merging video and commerce at scale. Users can now:
- Pause a TikTok video and tap on an item to find purchase links instantly.
- Point their phone camera at a storefront or product to view reviews, pricing, or nearby availability.
- Search using screenshots. Adobe’s 2025 Visual Commerce Study found that that an increasing number of Gen Z shoppers have used a photo or video to begin a purchase journey.
Even traditional search engines are embracing this behavior. Google Lens processes over 20 billion visual searches per month as of 2025, with approximately 20% of those visual searches having commercial intent.
This new search behavior has profound implications for franchise brands. Discoverability is no longer just about having the right keywords; it’s about being recognizable to machines. AI models powering these multimodal systems learn from structured metadata, image recognition, and contextual relationships.
To remain competitive, franchise organizations must ensure every digital asset is both visually compelling and machine-readable.
- Image Metadata: Every product photo, menu image, and store visual should include descriptive alt text, EXIF data, and embedded schema markup.
- Consistent Branding: Logos and signage should be uniform across locations to improve AI’s ability to recognize the brand in visual search results.
- Local Integration: Link visuals to structured data such as location, hours, and inventory so search engines can match what users see with where they can buy it.
- Short-Form Video Optimization: Incorporate shoppable elements such as product tags, captions, and local CTAs within TikTok and YouTube Shorts.
The future of search isn’t typed – it’s spoken, shown, and experienced. The franchise systems that connect their visual, voice, and data ecosystems into one structured framework will own the next era of local discovery.
Agentic Behaviors Emerge
The final, and perhaps most transformative, shift in AI-powered discovery is the rise of agentic behavior. In this new phase, AI assistants don’t just answer questions; they act. What began as conversational search has evolved into action-oriented automation, where a single spoken or typed query can trigger a full chain of activities such as comparing options, checking schedules, booking services, sending confirmations, and even generating follow-up communications.
This shift marks the point where search, commerce, and logistics fully converge. Instead of presenting a list of options, the AI assistant will execute based on intent.
Consider a common scenario. A customer says, “Book a haircut at the nearest salon at 4 p.m.” The AI assistant identifies the user’s location, checks nearby appointment availability via a booking API, confirms the slot, processes payment, and sends a calendar invite – all without the customer ever visiting a website or app.
This evolution, where intelligent agents complete tasks autonomously, is redefining customer expectations and rewriting the rules of marketing operations.
According to Gartner’s 2025 Emerging Tech Radar, over 70% of digital interactions will involve some form of AI agency by 2026, whether through chatbots, voice assistants, or embedded commerce integrations. Accenture’s Agentic AI in Retail 2025 report found that agentic systems reduce customer friction by 40% on average, increasing conversion rates by 27% for service-oriented brands.
Google’s Gemini, Amazon’s Alexa, and Apple’s Siri all feature task-completion APIs, allowing users to say things like “Order dinner for two from a local restaurant” or “Book a tire rotation for tomorrow morning,” triggering an immediate, multi-step workflow. Microsoft’s Copilot for Bing even supports direct calendar and CRM integrations, enabling seamless B2B scheduling.
This is not science fiction; it’s an accelerating trend. International Data Corporation (IDC) projects that by 2027, 15% of all e-commerce transactions will be initiated or completed entirely by AI agents, representing nearly $2.5 trillion in global retail value.
Agentic experiences rely on real-time structured data, which is typically delivered through APIs, feeds, and verified business profiles:
- Booking APIs: Allow assistants to schedule appointments directly in real time.
- Inventory Feeds: Expose local stock availability for retail or service items.
- Pricing Transparency: Provide structured, up-to-date pricing data to avoid exclusion from comparisons.
- Customer Communications: Enable AI-triggered confirmations, reminders, and follow-ups through CRM and messaging integrations.
Implications for Franchise Companies
Every day, thousands of potential customers turn to Google, Maps, and voice assistants to find nearby services, read reviews, and compare prices. For most franchise systems, this digital visibility is the lifeblood of customer acquisition and the front line of brand credibility. As artificial intelligence reshapes how search engines interpret and display information, that visibility is at risk for brands that fail to adapt quickly.
The transition to AI-driven discovery is complex, but the consequences of inaction are immediate. Generative and multimodal search models no longer reward sheer volume or keyword optimization; they reward precision, consistency, and structure. They favor brands whose data can be easily parsed, verified, and contextualized, qualities that require new operational discipline at both the corporate and local levels.
For franchise systems, this is not just a marketing issue; it is a strategic infrastructure challenge. Success depends on the ability to unify brand data, align content across locations, and maintain consistent, machine-readable information throughout the digital ecosystem.
Structured Data Is Survival Gear
In the world of AI-driven search, structured data is a must-have. Traditional search engines rely on web crawlers to scan page text, follow links, and interpret relevance. But the new generation of AI models, such as Google’s Gemini, Microsoft’s Copilot, and OpenAI’s GPT-powered search assistants, don’t browse pages in the same way. Instead, they employ structured data graphs that define entities (brands, products, locations, and services) and the relationships between them.
If your franchise company’s information isn’t machine-readable, verifiable, and interconnected, it simply doesn’t exist in this ecosystem. AI systems prefer precision over approximation. They favor brands whose data is current, canonical, and expressed in standardized formats.
At the core of every AI ecosystem lies an entity graph, which is a digital map of what your business is, where it operates, and what it offers. For franchise brands, this means organizing data in a structured hierarchy:
- Brand: Corporate identity, logos, national offers, brand voice
- Categories: Industries, product types, or service areas
- Locations: Each franchise location with address, hours, and contact details
- Products/Services: Offerings, menus, or packages available by region
When properly published, this structure enables AI engines to understand relationships between your brand and its local entities. A user’s query for “affordable family dining near me” should automatically connect to your restaurant franchise, its menu, its current promotions, and verified reviews without ambiguity.
According to BrightEdge’s 2025 SEO & AI Index, businesses with complete schema markup see higher visibility in AI-generated search results, particularly for local and commercial queries.
AI systems depend on schema.org markup to understand meaning. For franchise marketers, five schema types are particularly critical:
- LocalBusiness: Defines each franchise location, including NAP (Name, Address, Phone) and hours.
- Product/Offer: Communicates item details, pricing, and availability.
- FAQ: Surfaces key brand or service information in conversational search.
- Review: Validates credibility through ratings and customer sentiment.
In the AI era, structured data is survival gear. Franchise systems that build robust data foundations will dominate in visibility, trust, and automated commerce. Those that don’t will simply fade into the algorithmic background.
Content Will Compete on Clarity, Structure, and Utility
AI-driven search engines reward clarity, structure, and genuine usefulness over volume or verbosity. The rise of generative search means that algorithms now “read” and interpret content like a well-trained analyst. Google’s documentation on AI Overviews notes that its ranking models prioritize “information that directly satisfies intent, supported by verifiable data and context.” Similarly, Brightedge found that pages that were designed to be concise, structured, and visually supported were 68% more likely to be cited in AI-generated summaries than traditional long-form articles. In this new landscape, content must educate, not just rank.
According to Searchmetrics’ 2025 Content Intelligence Report, pages with at least one structured element, such as a table, chart, or FAQ, saw a higher chance of inclusion in AI-generated search responses compared to purely text-based pages.
AI search thrives on well-organized, unambiguous information. The AI does not reward fluff; it rewards frameworks. For franchise systems, this means rethinking how both corporate and local teams design and populate their pages. The goal is to create explainable, verifiable, and locally contextualized assets that machines can easily interpret and summarize.
AI models prioritize content they can trust and explain. Ambiguous claims, dense paragraphs, or outdated copy reduce the likelihood of citation. Conversely, structured content with clear data points, bullet lists, and verified reviews increases visibility in AI-generated results.
Franchise brands that adopt these principles will outperform competitors still relying on outdated keyword tactics.
Local Wins When It’s Canonical
In the age of generative AI, consistency has become a competitive advantage. AI systems rank, summarize, and recommend based not only on relevance but also the degree to which they can trust that the data they’re retrieving is accurate, current, and corroborated across multiple sources. To ensure consistency, franchise companies should ensure critical information such as location name, address, phone number, hours, pricing, and product/service details are the same on their corporate website, local microsites, Google Business Profile, and other third-party directories to the greatest extent possible.
Moz’s Local Search Ranking Factors Study (2025) found that data consistency across all listings correlates with a 28% higher likelihood of inclusion in AI-powered map packs and generative summaries.
Inconsistency doesn’t just confuse consumers; it erodes machine trust. When AI systems are uncertain about the quality of the information, they omit. The result is that your franchise loses visibility in AI-generated answers, maps, and assistant queries.
To maintain visibility, franchise companies should adopt a canonical data hierarchy, which is a structured framework where the “master truth” for critical information is defined and managed company-wide. Location details such as name, address, phone number, and hours are particularly important from a consistency perspective. Maintaining this information in a single database which is used to populate all placements (corporate website, local microsites, landing pages, location finder, Google Business Profile, other listings), ensures consistency across the web.
