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AI Search Isn’t Replacing SEO — It’s Rewriting Visibility: Key Insights from Conductor’s 2026 AEO / GEO Benchmarks Report

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AI-powered search (Google AI overviews, ChatGPT, Perplexity, etc.) is changing where and how brands are discovered online. Are traditional SEO metrics still enough to compete in 2026? What benchmarks should marketers use to measure performance in an AI-driven discovery landscape?

Conductor 2026 report on AEO, GEO, and SEOFind the answers to those questions and more in the 2026 AEO / GEO Benchmarks Report from Conductor.

For those in the digital marketing, SEO, and brand visibility space, this report offers a robust look at how AI answer engines and Google’s AI Overview results are creating new visibility metrics and redefining discovery. Rather than displacing SEO, AI search introduces a parallel visibility surface where brand credibility is measured by citations and mentions within AI responses.

Here are six specific findings from the report’s authors.

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Securing The Front Line: Cybersecurity Essentials For Customer-Facing Platforms

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Contributed post.

Customer-facing platforms often serve as the first point of interaction between a business and its audience. In a B2B environment, these systems shape credibility, influence buyer confidence, and support revenue generation. Cybersecurity plays a direct role in protecting those relationships by safeguarding data, ensuring uptime, and preserving brand trust.

Cybersecurity Essentials For Customer-Facing Platforms

Image credit: Microsoft Stock Images

Why Customer-Facing Platforms Are High-Value Targets

Public platforms handle login credentials, personal details, and transaction data. That combination makes them attractive to attackers seeking financial gain, competitive intelligence, or disruption. Even a short outage or minor data exposure can damage long-term partnerships and slow sales cycles.

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Beyond Stock Photos: Leveraging AI Visuals to Drive B2B Conversion Rates

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Guest post by Zihui Zhang.

In the intensely competitive world of B2B marketing, the battle for attention is fierce. For decades, B2B content strategies have leaned heavily on long-form text—whitepapers, case studies, and technical documentation. While depth remains critical, the delivery mechanism requires an overhaul. The modern B2B buyer, often a millennial digital native, processes visual information 60,000 times faster than text.

AI-driven visuals creationHowever, a “visual strategy” is no longer synonymous with purchasing a subscription to a stock photography site. Generic imagery—the handshake over a conference table or the smiling team pointing at a laptop—has led to a phenomenon known as “banner blindness.”

To improve conversion rates in 2024 and beyond, B2B marketers are turning to artificial intelligence (AI) tools to generate, edit, and optimize visuals that are not just decorative, but strategic drivers of action. Here’s a look at how B2B marketing professionals can utilize AI-driven visuals to enhance engagement and significantly improve conversion rates.
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7 Ways to Use Content to Build Authority and Trust in Any Niche (+ Real Examples)

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Guest post by Natasha Lane.

Building authority in your market segment or niche has nothing to do with budget and everything to do with approach.

7 ways to use content marketing for branding and authority

Image credit: Nick Morrison on Unsplash

A business selling brain health supplements can build just as much trust as a B2B software company. An outdoor equipment retailer can establish authority as effectively as an AI provider. The industry doesn’t matter. It’s the strategy that makes all the difference.

The difference between businesses that dominate their niches and those that fade into the noise? Content that demonstrates expertise instead of claiming it.

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Using E-commerce Datasets to Predict Demand and Optimize Inventory

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Contributed post.

For B2B SaaS providers and AI-powered platforms serving the retail and commerce sector, inventory optimization is no longer just a retailer’s operational problem, it’s a data intelligence opportunity.

Using E-commerce Datasets to Predict Demand and Optimize Inventory As the e-commerce ecosystem becomes more complex, businesses are increasingly relying on software platforms to transform raw commerce data into accurate demand forecasting and automated inventory decisions.

E-commerce datasets are at the center of this transformation. When structured, richly, and modeled correctly, they enable SaaS platforms to provide predictive insights, power machine learning models, and help reduce costs while improving service levels to retail customers.

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