Multimodal AI Will Change How Customers Find You
Introduction
A homeowner notices a crack spreading across their ceiling. They don't know what's wrong. They don't know the right search terms. They don't know whether they need a plumber, a structural engineer, or a roofer.
So they take a photo and ask AI: "What's causing this and who should I call?"
That's multimodal AI. Not typing a keyword. Showing AI the problem and letting it figure out what you need and who can help. And it's going to fundamentally change how customers find local businesses, because it removes the step that traditional search required: knowing what to search for.
Right now, AI search optimization is built around text queries. "Best plumber in Austin." "Who should I hire to fix my roof?" But within the next 12 to 24 months, a growing share of AI queries will be visual (photos and screenshots), audio (voice descriptions and ambient sounds), and video (showing AI what's happening in real time). Each modality creates new signal requirements that most businesses haven't considered.
Why multimodal changes everything for local discovery
The shift from text-only to multimodal AI matters because it changes who finds you and when.
Text search requires the customer to know what they need.
A customer types "best plumber in Houston" because they already know they need a plumber. They've self-diagnosed the problem. They know the service category. They're choosing among known options.
Multimodal search lets the customer show AI the problem without knowing anything.
A customer takes a photo of a water stain on their ceiling. They don't know if it's a plumbing issue, a roofing issue, or an HVAC condensation issue. AI analyzes the image, determines the likely cause, and recommends the appropriate type of service provider.
This is a fundamentally earlier point in the customer journey. The customer hasn't even identified what category of business they need. AI does that for them based on the visual input.
For businesses, this means being visible for queries that don't contain your service name. The customer never typed "plumber." They took a photo of water damage. AI decided they need a plumber and recommended one. If your business isn't positioned to be recommended when AI makes that category determination, you miss a lead that never would have used your category keywords.
The three multimodal entry points
Visual search (photos and screenshots).
Users take a photo of a problem, a product, a location, or a situation and ask AI for help. This is already functional in Google Lens, ChatGPT's vision capabilities, and Gemini's image analysis.
Business implications: AI needs to match a visual problem to a service category, then match that category to a specific business. The businesses that get recommended are the ones with strong entity authority in the service category AI identifies from the image.
Example queries:
- Photo of a damaged roof: AI identifies the issue, recommends a roofing company
- Photo of a skin condition: AI suggests a dermatologist
- Photo of a restaurant storefront: AI provides reviews and descriptions
- Screenshot of a competitor's product: AI recommends alternatives
Voice search (spoken queries with ambient context).
Users describe their situation verbally, often with more context and nuance than they'd type. Smart speakers, phone assistants, and car infotainment systems are the primary interfaces.
Business implications: Voice queries tend to be longer, more specific, and more urgent than typed queries. "I'm driving through downtown and my car started making a grinding noise when I brake. Where should I go?" AI needs to process the situation description, identify the service need (brake repair), and factor in the user's real-time location.
Voice AI recommendations already provide only one or two results. Multimodal voice (voice + GPS location + vehicle diagnostics, for example) makes those results even more targeted.
Video search (showing AI what's happening in real time).
Users show AI a video of a situation: a plumbing leak in progress, a malfunctioning appliance, an insect infestation, a car engine noise. AI analyzes the video to diagnose the issue and recommend a service provider.
Business implications: Video queries are the highest-context, highest-urgency entry point. A user filming a burst pipe needs immediate help. AI's recommendation in that moment carries more conversion weight than any other type of query because the need is immediate and the user has no time to comparison shop.
What new signals multimodal AI requires
Text-based AI selects businesses based on entity authority, citations, reviews, content, and structured data. Multimodal AI uses all of those plus additional signals:
- Service category breadth and specificity.
When AI determines from a photo that the user needs "emergency plumbing" rather than just "plumbing," your entity data needs to include that specific sub-category. Businesses with detailed, specific Service schema markup (including emergency services, specific repair types, and specialty capabilities) are more matchable than businesses with generic service descriptions.
A plumber whose structured data includes "emergency pipe repair," "water heater replacement," "drain cleaning," and "bathroom remodeling" as separate, defined services is matchable against more visual queries than a plumber whose data just says "plumbing services."
Visual content on your web presence.
Multimodal AI can process images on your website, directory listings, and social media. Photos showing your team working, your equipment, your completed projects, and your service environment help AI build a richer understanding of what you do and the quality of your work.
This creates a new signal category: visual entity data. A roofing company with 50 photos of completed roof installations across their website and Google Business Profile gives AI visual confirmation of their capabilities. A roofing company with no photos provides only text-based signals.
Location precision.
Multimodal queries often include implicit location data (GPS from the user's phone, address visible in a photo, location mentioned in a voice query). Businesses with precise geographic data (exact coordinates in structured data, neighborhood-level descriptions, specific service area definitions) match better against location-contextualized multimodal queries.
Real-time availability and emergency capacity.
Visual and video queries for home services often indicate urgency. AI needs to know not just who provides the service, but who can respond now. Businesses that expose availability data (through booking platforms, business hours in structured data, or "emergency service available" attributes) have an advantage in urgent multimodal queries.
Preparing for multimodal AI discovery
The good news: most multimodal AI preparation builds on the same foundation as text-based AI optimization. The bad news: there are additional steps most businesses haven't taken.
Foundation (same as text-based AI optimization):
Citations, entity consistency, structured data, content, reviews. This foundation is required for any AI recommendation, regardless of modality.
Multimodal-specific additions:
Detail your services at the sub-category level. Don't just list "plumbing." List every service type you offer as a separate, defined service with its own description. This enables matching against the specific problems AI identifies from visual and audio inputs.
Add visual content across all platforms. Upload high-quality photos of your work, your team, your equipment, and your location to: your website, Google Business Profile, Yelp, Facebook, and industry directories. Visual content gives AI additional data to associate with your entity.
Include emergency and urgency attributes. If you offer emergency services, include that in your structured data, your directory listings, and your content. "24/7 emergency service available" is a signal that multimodal AI needs when recommending for urgent visual queries.
Optimize for sub-category matching. Create content pages for each specific service that might be triggered by a visual query: "Emergency Pipe Repair in Austin," "Roof Leak Repair in Denver," "Termite Damage Assessment in Charlotte." Each page creates a direct match between a visual problem category and your business.
Ensure your Google Business Profile photos are current and relevant. Google's visual AI capabilities use GBP photos to understand what your business does. Photos of completed work, your storefront, and your team provide visual signals that text alone can't convey.
The industries where multimodal matters most
Home services (highest impact).
Customers frequently can't describe their problem in words. They know something is wrong but not what to call it. Taking a photo or video of the problem and asking AI "who can fix this?" will become the primary entry point for emergency and repair services. Plumbers, electricians, HVAC technicians, roofers, and pest control companies will see the largest shift toward multimodal queries.
Healthcare (high impact).
Patients already take photos of symptoms and ask AI for guidance. "What is this rash?" followed by "should I see a dermatologist?" will increasingly become "what is this rash and who should I see?" in a single multimodal query. Dermatologists, urgent care clinics, dentists (dental issues photographed), and veterinarians (pet symptoms) are affected.
Auto services (high impact).
Drivers will record the sound their car makes ("my brakes sound like this, what's wrong?") or photograph damage ("how much would it cost to fix this dent?"). AI diagnoses the issue and recommends a service provider. Auto repair shops, body shops, and tire shops are primary beneficiaries.
Restaurants and retail (moderate impact).
Customers photograph a restaurant storefront and ask "is this place good?" or photograph a product and ask "where can I buy this cheaper?" Visual search becomes a discovery layer on top of physical exploration.
Real estate (moderate impact).
Buyers photograph houses and ask AI for information: listing details, neighborhood data, agent recommendations. AI becomes an augmented reality layer on top of property tours.
Want to be ready for multimodal AI? Run your free AI visibility audit at yazeo.com and evaluate your current foundation across text-based AI platforms. Then add the multimodal-specific preparations described above. The audit shows where your entity foundation is strong and where it needs reinforcement before multimodal becomes mainstream.
Key findings
- Multimodal AI allows customers to search by showing rather than typing, removing the requirement that customers know what service they need before searching.
- Visual, voice, and video queries enter the customer journey earlier than text queries, before the customer has even identified the service category they need.
- New signal requirements include sub-category service specificity, visual content across platforms, emergency/urgency attributes, and location precision.
- Home services, healthcare, and auto services will see the largest impact from multimodal AI because their customers frequently can't describe problems in searchable text.
- Multimodal preparation builds on text-based AI optimization with additional layers: detailed sub-category services, visual content, and urgency signals.
Frequently asked questions
The camera becomes the search bar
The search bar was the gateway to discovery for 25 years. Type your query. Get your results. That paradigm assumed customers could articulate what they needed in words.
Multimodal AI removes that assumption. The camera becomes the search bar. The microphone becomes the search bar. The customer shows AI the problem, and AI figures out everything else: what's wrong, who can fix it, who's nearby, who's available, and who's trustworthy.
The businesses that are ready for this shift are the ones with entity data detailed enough, specific enough, and visual enough to be matched against problems the customer can't even name. That's the future of local business discovery.
Run your free AI visibility audit at yazeo.com and start building the foundation that serves both text-based and multimodal AI. The search bar is becoming a camera. Make sure AI knows what you look like.