SEO in 2026: Why Influence Now Outranks Position

Search has changed more in the past 18 months than in the previous 10 years combined. So, if 2025 was the year brands felt the shift, 2026 is the year they must act.

How?

To get your SEO strategy ready for 2026, you need more than trends. We share what’s in, what’s out, and provide tips to help you adapt your SEO to stay competitive in the era of AI-driven search.

What’s In: Building Influence That AI Trusts

What’s Out: Optimizing Purely for Clicks

The SERP’s purpose has changed.

The organic landscape we once optimized for—a ranked list of blue links—is now an AI-driven answer engine, where success is no longer measured by clicks but by influence. That’s because AI Overviews now sit at the top of results, answering queries directly and pushing traditional listings down the page.

Influence is the degree to which your brand shapes, informs, or appears inside AI-generated answers—even when the user never lands on your website. It reflects how often AI models cite, reference, or learn from your brand across the broader online ecosystem.

In other words, it’s what your brand does to drive visibility and gain brand authority. It’s not about how many clicks you generate.

What we’re seeing today:

• The top organic result is often below the fold
• CTR drops ~35% when an AI Overview appears
• Overall search clicks have fallen 30% YoY

This is why influence-based SEO matters more than position.

So, your 2026 SEO objective? Shape the answers you want to populate.

Even without a click, brands earn visibility by becoming the source behind the answer. That user may recall this authority later in their buyer’s journey.

What’s In: Search as a Personal Conversation

What’s Out: Google-As-We-Knew-It

Thinking about AI Overviews and the “new SERP” is important, but don’t forget LLMs. Today’s buyer journey doesn’t always start on Google; it often begins in more private, untraceable conversations on platforms like ChatGPT, Gemini, and Perplexity.

B2B businesses have massive opportunities here. Buying decisions in this space require a lot of upfront research—LLMs are a perfect place to start. These act like topic experts—curating products, recommending vendors, and shaping decisions via conversational search. Users can make purchase decisions without ever visiting a website; however, they’ll need to click to purchase.

If being the source means being the choice, influence is essential.

How do you get this influence? Entity authority.

If influence is the output—how often AI cites or uses your insights—then entity authority is the foundation; it proves your brand is a credible expert.

What’s In: Entity SEO—Winning as a Brand, Not a Page

What’s Out: Keyword-Centric Optimization

You can copy another business’s keywords. You can’t copy a business’s reputation.

Traditional keyword strategies focus on matching strings of text; however, today’s search evaluates entities—real brands, real expertise, real customer sentiment. This shift is one of the most defining SEO trends for 2026 and requires entity SEO.

To be clear: keywords aren’t off the table. They’re simply no longer enough on their own. Keywords now act as supporting signals, but they only work when they reinforce a strong, trustworthy entity.

Entity SEO includes:

• Authoritativeness: your proven expertise on a topic
• Real-world credentials: your experience, certifications, and awards
• External citations: third-party mentions on industry associations or user-generated sites like Reddit, plus reviews and references
• Topical depth: comprehensive coverage of your core subject areas
• Structured data: the technical layer that helps AI verify, interpret, and connect your entit

This strategy consolidates trust signals across the web to answer one question: Is this brand an expert?

If yes, AI models use your content, and your visibility stays strong.

If not, your visibility shrinks regardless of how keyword-optimized your pages are.

Our case studies page includes trust signals that are verifiable, impossible to copy, and valued by AI.

Action Plan: How to Build Entity Authority (and Gain Influence)

Entity authority is built through consistent, verifiable signals. The steps below show how to create signals that help your brand shape the answers buyers are looking for.

Note: Creating these signals doesn’t happen overnight. It is a significant lift in time and effort, not just in content creation but also in technical SEO. Having a digital marketing partner can not only help get the work done but also keep the signals coming.

1. Add Organization, Author/SME, and Product Schema to Key Pages

Apply schema to your homepage, service pages, and high-authority blog posts. Make sure names, titles, and product identifiers match across your website, LinkedIn, Google Business Profile, and industry publications.

Example: A direct-to-consumer furniture brand publishes a guide on choosing an ergonomic office chair. They add:

• Organization Schema: brand name, founding date, and links to LinkedIn and Google Business Profile
  

  Organizational schema defines who the brand is and connects it to trusted external profiles.

• Author/SME Schema: in-house product designer with 12 years of ergonomic design experience
  

  Author schema defines who is responsible for the expertise behind the content.

• Product Schema: dimensions, materials, warranty details, pricing for three featured chairs
  

  Product schema defines what products are being referenced and their real-world attributes.

Because every detail aligns across their web presence, AI can confidently verify the entity.

2. Encourage (and Organize) Detailed Third-Party Reviews

Reviews are one of the strongest real-world signals. Request specific, descriptive reviews, not generic star ratings, on platforms relevant to your industry.

Example: A patio furniture retailer asks customers to mention:

• the exact product purchased
• materials and durability
• assembly experience
• real-world performance (weatherproofing, longevity, etc.)

These details help AI validate product quality and customer satisfaction.

3. Publish Expertise on High-Value Industry Sites

Pitch guest articles, submit insights to trade publications, or participate in industry association content opportunities. Brands that produce original contributions outperform those that summarize public knowledge.

Strong contribution formats include:

• Proprietary surveys
• Benchmark reports
• Case studies with real numbers
• Internal analyses
• Expert POV backed by real-world experience

These are initiatives no one can replicate or copy from your business.

Example: A precision hydraulic cylinder manufacturer analyzes field service data across three industries and identifies a failure pattern. They publish this insight in a trade journal and on their site. 

Pro-Tip: This is also great content to repurpose for sales decks, social media posts, and email campaigns.

AI interprets the manufacturer as an authoritative, expert entity because the insight is unique, validated, and cited across respected platforms.

4. Consolidate Content Into Topic Hubs

Topical depth is one of the strongest indicators of expertise. To achieve this, build a pillar page supported by 6–10 interlinked articles that comprehensively cover the topic.

Example: OuterBox’s internal efforts

• Core SEO service pages that define our approach and expertise
• Tactical subpages that dive into specific disciplines like content strategy, technical SEO, and link building
• SEO by industry pages that show how strategy adapts across eCommerce, B2B, and enterprise environments
• Educational blog content that explores emerging topics like AI Overviews and content built for AI extraction

All of these assets are interlinked to reinforce context and authority. Together, they help AI systems understand not just that OuterBox offers SEO, but what we’re known for within SEO.

By covering the topic holistically and consistently, we signal sustained expertise rather than isolated relevance.

Before setting this action plan in motion, brands need to consider not just user readability, but AI readability.

What’s In: Content Built for AI Extraction

What’s Out: Paragraphs Built for Humans Alone

AI models are not scanning your entire page for meaning—they’re looking for clean, clearly labeled chunks of information they can lift and reuse without rewriting.

Unlike humans, AI:

• Extracts, it doesn’t interpret prose. LLMs break content into patterns and labeled segments. Bullets, headers, and tables give them predictable shapes.
• Prioritizes clarity over creativity. Short, distinct blocks reduce ambiguity and increase confidence in the accuracy of the information.
• Matches structured content to user intent. If your answer is already formatted like the response a user needs, AI sees it as a “ready-made” insertion.

Put simply: AI favors information that looks like it belongs in an answer box.

This is not to say you are writing for robots. You can do both AI and user intent, adding creative branding a flair in areas like introductions, conclusions, and design while making answers scannable for both.

To appear in AI-generated answers, format your content for effortless reuse. That means:

• H2/H3s written as questions and answers
• Bulleted lists that break down processes and insights
• Comparison tables that present distinctions at a glance
• Short, self-contained sections instead of dense paragraphs
• Schema markup labeling your organization, authors, products, and FAQs

This approach is the foundation of citable content.

Example: A hydraulic systems manufacturer publishes a guide called “How to Diagnose Pressure Loss in Hydraulic Systems.” Instead of writing a long, narrative explanation, they divide the content into clean, extractable blocks:

• Common Causes (internal leakage, clogged filters, worn seals, incorrect viscosity, air entrainment)
• Quick Diagnostic Steps (check system pressure, inspect filters, run a bypass test, verify viscosity, listen for cavitation)
• Typical Loss Ranges (servo systems <10%, industrial hydraulics 10–15%, high-duty systems 15–20%)

Each section is concise, labeled, and formatted like a standalone answer—which makes it far more likely that AI models will lift portions of it.

This isn’t just better for AI. It’s better for users who now expect clear, immediate answers.

This is what that “machine-readable map” looks like in the code vis Schema Markup.

Action Plan: How to Reformat Existing Content for AI Extraction

You don’t have to reinvent the wheel here. Review your existing content and identify formatting solutions.

1. Take any long paragraph and turn it into an H2 or H3 phrased as a question, followed by a short, direct answer.

Example Before: “A pressure drop in hydraulic systems can occur for many reasons, including internal leakage, worn seals, or clogged filters…”

Example After:

What Causes Pressure Loss in a Hydraulic System?

• Internal leakage
• Worn seals
• Clogged filters
• Incorrect viscosity

2. Find any section with commas, long sentences, or multiple ideas and rewrite it as bullets.

Example Before: “Diagnosing pressure loss requires checking system pressure, inspecting filters, performing a bypass test, and verifying fluid viscosity.”

Example After:

Quick Diagnostic Steps:

1. Compare system pressure to spec
2. Inspect filters
3. Perform a bypass test
4. Verify viscosity

SEO in 2026 Belongs to the Brands That Shape the Answers

AI isn’t just answering questions—it’s inadvertently deciding who buyers remember. AI citations are based not on who ranks highest in SEO, but on the entity authority AI trusts most.

For SEO in 2026, remember: Influence beats position and entity authority beats keyword volume.

The brands that adapt today will shape tomorrow’s answers.

If you’re ready to turn your expertise into an AI-ready authority, OBX can help you get there.