AI Agents and the Future of SEO: Brands’ New Battle for Visibility

Search engines are changing. User behavior is shifting. So how should businesses prepare for this new world?

Introduction: The End of an Era or an Evolution?

SEO, the cornerstone of digital marketing for the last 25 years, is facing the biggest transformation in its history. The race to rank at the top of Google’s search results is giving way to a far more complex ecosystem: AI-powered search engines, conversational assistants, and autonomous AI agents.

Platforms like ChatGPT, Google Gemini, Perplexity, Claude, and Microsoft Copilot have fundamentally changed how users access information. People no longer just search for “the best CRM software”; they ask AI assistants, “find and compare the best CRM for my company.” Even more importantly, in the near future, humans may not even ask these questions—AI agents working on their behalf will.

This article takes a comprehensive look at how SEO is evolving in this new era, why businesses need to become “Agent-Ready,” and how you can prepare for this shift.

Section 1: From Search to Answer—A Paradigm Shift

The Classic SEO Model

Traditional SEO was built on a relatively simple model:

1. The user types a keyword
2. The search engine ranks the pages it has indexed
3. The user chooses from the results
4. They click through to the website

In this model, success was measured by ranking high on the search engine results page (SERP). Technical SEO, content optimization, and backlink strategies were the core tools used to achieve that goal.

The New Model: Answer Engines

AI-powered platforms have flipped this model. The process now looks like this:

1. The user asks a question in natural language or defines a task
2. The AI analyzes and synthesizes multiple sources
3. It provides a direct answer or solution
4. In most cases, no website click happens

The consequences of this shift are dramatic: research shows that in AI-powered searches, traditional website traffic has dropped by as much as 40%. When users get the answer directly from an AI, the need to visit the source disappears.

The Rise of Zero-Click Searches

Even Google has had to adapt. The AI Overview feature (formerly SGE - Search Generative Experience) provides AI-generated summary answers at the top of search results. This reduces organic clicks even further.

What does this mean for businesses? It is no longer enough to simply “rank at the top.” Being included in the AI-generated answer—even shaping that answer—has become the new success metric.

Section 2: GEO—Generative Engine Optimization

From SEO to GEO

This new reality has given rise to a new concept in the industry: Generative Engine Optimization (GEO). GEO is the set of strategies and techniques focused on making brands visible within AI-generated answers.

The core differences between GEO and SEO can be summarized as follows:

Dimension	Classic SEO	GEO
Goal	SERP ranking	Presence in AI answers
Metric	Clicks, ranking	Mentions, citations, sentiment
Content	Keyword-focused	Context- and meaning-focused
Technical	Crawl, index, rank	AI interpretability
Competition	10 blue links	One synthesized answer

GEO Strategies

To be visible in AI-generated answers, businesses need to focus on the following core areas:

Strengthening Authority

AI systems prioritize trustworthy sources. Being perceived as an authority in your industry is critical. This requires producing high-quality content, being featured in industry publications, and maintaining a consistent digital presence.

Using Structured Data

Schema.org markup makes it easier for AI systems to understand your content. Using structured data for product information, FAQs, company details, and service descriptions increases your likelihood of appearing in AI answers.

Being Citable as a Source

AI systems cite sources when generating answers. If your content is citable—meaning it contains clear, verifiable, and original information—you increase your chances of being referenced by these systems.

Content in a Q&A Format

Users typically interact with AI in the form of questions. Structuring your content to answer those questions directly increases the likelihood that AI systems will choose you as a source.

Section 3: The Agent Economy—The Next Wave

What Are AI Agents?

GEO is only the first phase of the AI transformation. In the current stage, users still interact with AI directly—they ask questions, get answers, and make decisions themselves.

But the next stage will be very different: autonomous AI agents.

An AI agent is a system that can act independently to accomplish a specific task. These agents can:

• Crawl websites to gather information
• Synthesize data from different sources
• Make decisions or recommendations on a person’s behalf
• Communicate with other systems and agents
• Execute actions automatically

Practical Examples

To make this concept more concrete, consider a few scenarios:

Scenario 1: B2B Procurement

A company’s procurement manager is looking for a new software solution. In the traditional process, they would search on Google, visit several sites, request demos, and evaluate options. In the new process, they tell their AI agent, “research CRM solutions that fit our needs, schedule demos, and obtain price quotes.” The agent crawls dozens of websites, identifies suitable solutions, and can even contact vendors’ agents to get offers.

Scenario 2: Travel Planning

A user wants to plan a vacation. They tell their AI agent their preferences. The agent scans airline sites, hotels, and restaurant reviews; identifies the best options; and makes reservations.

Scenario 3: E-commerce Research

A consumer wants to buy a new product. The AI agent collects prices, features, and user reviews from different e-commerce sites; produces a comparative analysis; and can even complete the purchase with the user’s approval.

Agent-to-Agent (A2A) Interaction

At an even more advanced stage, agents will communicate with each other rather than with humans. A buyer’s agent could negotiate directly with a seller’s agent. In this scenario, the human side could be entirely removed from the process.

How far away is this future? Much closer than expected. Companies like OpenAI, Google, Anthropic, and Microsoft are rapidly improving agent capabilities. According to Gartner’s forecasts, by 2028, 15% of enterprise software operations will be performed by autonomous agents.

Section 4: Why Being Agent-Ready Matters

A New Visibility Paradigm

In the agent economy, the very concept of visibility changes. The questions we need to ask now are:

• Can AI agents understand our website?
• Can agents interpret our products and services correctly?
• Do we have infrastructure that can communicate with other agents?
• Can we track agent interactions?

What Does Agent-Ready Mean?

Being Agent-Ready means your website and digital assets are easy for AI agents to understand, access, and interact with. This concept consists of several core components:

Machine Readability

Agents do not interpret visual design the way humans do. What matters to them is structured data, clean code, and a clear information architecture. Schema.org markup, JSON-LD data formats, and semantic HTML structure are critical.

The llms.txt Standard

Just as robots.txt guides search engine bots, an llms.txt file provides AI systems with a summary of your website. This standard distills your site’s purpose, services, and key information into a format AI can understand easily.

Agent Endpoints

At an advanced level, being Agent-Ready includes providing API endpoints that external agents can query directly. This lets agents retrieve the information they need without crawling the entire site.

A Structured Content Architecture

Clear categorization of information, hierarchical organization, and a consistent information structure make it easier for agents to understand your content.

The Risks of Not Being Agent-Ready

Businesses that do not prepare for the agent economy will face serious risks:

The Risk of Invisibility

If AI agents cannot understand your site, they will not recommend you to potential customers. If your competitors are Agent-Ready and you are not, you will be automatically excluded from evaluation.

The Risk of Misrepresentation

Without structured data, agents may present incorrect information about your business. Pricing, service scope, or product features can be communicated inaccurately.

Competitive Disadvantage

Early movers will secure a strong position in the agent ecosystem. For late adopters, closing that gap will be difficult.

Section 5: Technical Depth—Agent-Ready Infrastructure

Core Technical Components

Let’s examine the technical infrastructure required to build an Agent-Ready website:

1. Advanced Schema Markup

   Schema.org markup is the foundation of Agent-Ready infrastructure. But you need to go beyond the basic schemas used for classic SEO.

   Recommended schema types:

   • Organization: Company details, contact information, social profiles
   • Product/Service: Detailed product and service descriptions
   • FAQPage: Frequently asked questions and answers
   • HowTo: Processes and usage guides
   • Review/AggregateRating: Customer reviews and ratings
   • Offer: Pricing and campaign information
   • LocalBusiness: Local business information

2. The llms.txt File

   This file lives in your site’s root directory and provides AI systems with a summary. Its basic structure includes:

   • A short description of the company/site
   • A list of offered products and services
   • Contact information
   • A list of important pages
   • Answers to frequently asked questions

3. Semantic HTML Structure

   Clean, meaningful HTML makes it easier for agents to understand content. Key considerations:

   • Correct heading hierarchy (H1, H2, H3)
   • Meaningful section and article elements
   • Descriptive alt text
   • Logical content grouping

4. API and Endpoint Strategy

   Advanced Agent-Ready infrastructure provides programmatic access:

   • RESTful API endpoints
   • GraphQL query support
   • Webhook integrations
   • Standard data formats (JSON, XML)

5. Metadata Optimization

   AI systems place strong emphasis on metadata:

   • Open Graph tags
   • Twitter Card information
   • Dublin Core metadata
   • Canonical URLs

Performance and Accessibility

Agents care about speed and accessibility as well:

• Fast page load times
• Mobile compatibility
• HTTPS security
• Compliance with accessibility standards (WCAG)

Section 6: Industry Perspectives

E-commerce

E-commerce will be one of the sectors most affected by the agent economy. AI shopping assistants will research products and make purchasing decisions on users’ behalf.

Priorities for e-commerce sites:

• Detailed product schemas (price, inventory, attributes)
• Comparable product information
• Real-time price and inventory APIs
• Structured presentation of user reviews

B2B and Enterprise

B2B purchasing processes are particularly well-suited to agent automation. Long and complex evaluation processes can be accelerated by agents.

Priorities for B2B companies:

• Detailed service and solution descriptions
• Case studies and success stories
• Pricing and package information
• Integration and technical documentation

Local Businesses

Local searches will gain a different dynamic in the agent economy. Queries like “the best restaurant near me” will be evaluated in far more detail by agents.

Priorities for local businesses:

• Up-to-date and accurate business information
• LocalBusiness schemas
• Customer reviews and ratings
• Reservation and appointment APIs

Finance and Insurance

In the finance sector, agents will play a critical role in comparison and evaluation processes.

Priorities for financial institutions:

• Product and service comparison data
• Transparent pricing information
• Compliance metadata
• Security and privacy standards

Section 7: A Strategic Roadmap

A Phased Transformation Plan

Agent-Ready transformation is not a one-time project; it is a phased process.

Phase 1: Assessment and Core Infrastructure (1-3 Months)

• Assess the current state through an Agent Readiness Audit
• Address schema markup gaps
• Create an llms.txt file
• Perform basic metadata optimization

Phase 2: Content and Structure Optimization (3-6 Months)

• Make the content architecture agent-friendly
• Produce content in a question-and-answer format
• Improve technical documentation
• Optimize internal linking structure

Phase 3: Advanced Integrations (6-12 Months)

• Develop API endpoints
• Set up agent analytics infrastructure
• Implement automated update systems
• Optimize performance

Phase 4: Continuous Improvement (Ongoing)

• Analyze agent interactions
• Competitor monitoring and benchmarking
• Adaptation to new standards and protocols
• A/B testing and optimization

Measurement and KPIs

Measuring the success of Agent-Ready transformation requires new metrics:

• Mention share across AI platforms
• Traffic from agent queries
• Structured data coverage rate
• API usage metrics
• Agent conversion rates

Section 8: Looking Ahead

2025-2030 Predictions

Industry analysts’ forecasts for the evolution of the agent economy look like this:

• 2025: AI assistants become widespread, and GEO strategies become standard. Early adopters gain a competitive advantage.
• 2026: The first commercial AI agents enter the market. Basic purchasing and reservation tasks become automated.
• 2027: Agent-to-agent protocols become standardized. Automated B2B interactions begin.
• 2028: The agent economy becomes mainstream. Businesses that are not Agent-Ready face significant disadvantages.
• 2030: A substantial part of digital commerce occurs through agents. Human intervention shifts to exceptional cases.

The Value of Being Prepared

Even if not all of these forecasts come true, being prepared is critical. Investments in Agent-Ready infrastructure also improve existing SEO performance. Structured data, clean code, and high-quality content create value for both traditional search engines and AI systems.

In other words, Agent-Ready transformation is not an all-or-nothing bet. Every step you take benefits both today and the future.

Conclusion: It’s Time to Act

The digital marketing world is going through its biggest transformation in the last 25 years. The shift from search engines to answer engines, from websites to agent endpoints, and from clicks to automated actions is accelerating.

The businesses that will succeed in this transition will be those that move early. A wait-and-see strategy may have worked in the past, but the pace of technological change no longer allows it.

As Webtures, we have been leading Turkey’s digital transformation for more than 15 years. As the pioneer of SEO in Turkey, we are now ready to shape the next era—the Agent Economy.

Your Next Step

Are you wondering whether your business is Agent-Ready?

Evaluate your current state comprehensively with the Webtures Agent Readiness Audit.

In the audit, you will learn:

• How your website is perceived by AI agents
• Your structured data and schema gaps
• Your comparative Agent-Ready score against competitors
• Prioritized improvement recommendations
• A customized transformation roadmap

Take the first step today to prepare for the agent economy.

[Contact us for the Agent Readiness Audit]

This article was prepared by the Webtures Digital Marketing team. For questions, you can write to info@webtures.com.