The traditional search bar is undergoing a slow, quiet death. For twenty years, 'getting found' meant playing a game of keywords and backlinks to land on the first page of Google. But the behavior of your customers has shifted. They aren’t looking for a list of ten blue links anymore; they are looking for a definitive answer.
When a customer asks ChatGPT, 'Where is the best place in Manchester for a high-end client lunch that has gluten-free options and a quiet atmosphere?' they aren't performing a search. They are conducting an interview. If your business isn't the one the AI recommends, you didn't just lose a click—you lost the entire conversation. Understanding how to use AI in marketing today isn't about automating your social media posts; it's about becoming an undeniable 'entity' in the world’s most powerful Large Language Models (LLMs).
From Search Engines to Answer Engines
💡 Want Penny to analyse your business? She maps which roles AI can replace and builds a phased plan. Start your free trial →
We are moving from the era of SEO (Search Engine Optimization) to AEO (Answer Engine Optimization). In the old world, Google was a librarian pointing you to a shelf. In the new world, AI is a personal assistant making a choice on your behalf.
This shift creates what I call The Visibility Gap. Most local businesses are still optimized for the librarian, while their customers have already hired the assistant. If you are still paying a marketing agency thousands per month for traditional keyword tracking, you are likely investing in a map of a city that is being rebuilt in real-time.
The Entity Authority Loop: How AI 'Knows' You
AI models don't 'search' the live web in the same way a crawler does. They rely on a combination of their training data and 'Retrieval-Augmented Generation' (RAG)—essentially, their ability to look up trusted sources to verify facts. To show up in these answers, you need to enter the Entity Authority Loop.
An 'Entity' is a unique thing—your business—defined by its attributes: location, price point, vibe, menu, and reputation. AI models look for consensus across the web to build a high-confidence profile of your entity. If your website says you're a luxury boutique but your Yelp reviews describe you as a 'budget find,' the AI experiences a 'Confidence Conflict' and will likely recommend a competitor with more consistent data.
1. Feed the Machine: Schema and Structured Data
If you want an AI to understand your business, you have to speak its language. This isn't just about meta tags anymore; it’s about deep Schema Markup. This is a script in your website’s code that tells a machine exactly what you are.
For example, a retail business looking for AI-driven savings should use Product and LocalBusiness schema to define every SKU, its price, and its availability. When someone asks an AI for 'red leather boots under £100 near me,' the model pulls from these structured data points. Without them, you're just a collection of pixels that the AI has to guess at.
2. The Narrative Saturation Strategy
AI models are trained on the 'Common Crawl'—massive datasets of the entire internet. To become a 'known' entity, you need Narrative Saturation. This means your business needs to be mentioned in contexts that define your attributes.
- Unstructured Mentions: A mention in a local 'Top 10' blog post is more valuable for AEO than a high-DA backlink from a generic site.
- Vertical Aggregators: For hospitality businesses trying to save on customer acquisition, being dominant on niche platforms like OpenTable, TripAdvisor, and even local Reddit threads is critical. AI models 'scrape' these platforms to determine the sentiment of an entity.
The Agency Tax and the Shift to AI-First Marketing
For years, businesses have paid what I call The Agency Tax: high retainers for manual SEO work that is increasingly obsolete. Traditional agencies spend hours writing 'keyword-rich' blog posts that humans don't read and AI models see right through.
How to use AI in marketing effectively means reallocating that spend. Instead of paying for 'content volume,' you should be investing in 'Contextual Accuracy.' This involves:
- Data Cleaning: Ensuring your Name, Address, and Phone Number (NAP) are identical across 50+ directories.
- Review Synthesis: Using AI to analyze your reviews and identifying the specific 'attributes' customers love, then reflecting those exact words back in your website copy to strengthen the Entity Authority Loop.
- API Integration: Making your real-time data (inventory, booking slots) accessible to the web so AI 'agents' can act on your behalf.
The 90/10 Rule of Modern Visibility
I often tell my clients that we are entering the 90/10 Rule of Visibility. 90% of the 'discovery' work—the filtering, the comparing, the shortlisting—will be done by AI. Only the final 10%—the actual conversion—will involve the human visitor.
If you aren't in the AI's shortlist, the 10% never happens.
Action Plan: Dominating the Answer Engine
To move from being a 'search result' to an 'answer,' follow this three-step framework:
Step 1: The AI Audit
Ask ChatGPT, Claude, and Perplexity about your business. 'Tell me about [Your Business Name] in [City].' Observe what it gets right and where it hallucinates. If it doesn't know your opening hours or your 'vibe,' you have a data fragmentation problem.
Step 2: Attribute Alignment
Identify the three 'attributes' you want to be known for (e.g., 'fastest delivery,' 'quietest cafe,' 'best for families'). Ensure these three phrases appear in your site headers, your Google Business Profile description, and are encouraged in your customer reviews. AI loves consistency.
Step 3: Structured Authority
Implement 'LocalBusiness' Schema. If you're a restaurant, implement 'Menu' and 'Review' schema. If you're a service provider, use 'Service' schema. This turns your 'flat' website into a machine-readable database.
The Bottom Line
The businesses that thrive in the next 24 months won't be the ones with the biggest SEO budgets; they’ll be the ones that are the easiest for an AI to understand. The search bar is dying, but the opportunity to be the only answer recommended to a customer has never been higher.
Stop trying to rank. Start trying to be the solution.