The news: Adobe aims to help brands and publishers improve content placement in AI browsers, search tools, and chatbots with its new suite of AI tools—LLM Optimizer.

What it does: LLM Optimizer tracks which content and offerings—such as website details, products, or articles—are being shown in AI interfaces and where they’re appearing.

• Side-by-side benchmarking lets users know how their content appears in AI engines compared with competitors.
• A recommendation engine offers suggestions about how owned pages and external channels, like Wikipedia or Reddit pages, can be optimized to better appear in large language model (LLM) results.
• An attribution capability shows metrics on user behavior, engagement, and business outcomes to track how AI platforms are affecting engagement and conversion.

Why it matters: AI search engine optimization (SEO) is a new and increasingly important strategy as Google expands its AI offerings and tools like Perplexity gain traction.

Generative AI (genAI) is the top source for purchase recommendations for 18% of genAI users, per Accenture, above social media at 15% and traditional search engines at 11%.

Over half (55%) of US consumers use genAI to conduct shopping research, and 53% plan to use AI to shop online this year, per Adobe.

Yes, but: Half of the puzzle is still missing because LLM platforms are opaque about how content is ranked and selected.

These tools could offer clarity on engagement and placement, but with the haziness surrounding LLM algorithms and data sources, AI SEO may still be an educated guess rather than a concrete strategy.

Our take: Adobe’s new tools, especially outcome metrics and actionable recommendations, can help marketers and brands optimize for each platform—browsers, AI Overviews, and chatbots—and surface data-driven solutions to help improve their AI search presence.

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