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AI recommendation engines rely on reviews, comparisons, and customer signals to decide which brands to surface and trust, according to [MarTech](https://martech.org/customer-experience-outweighs-brand-in-ai-assisted-shopping/). The rules for AI-assisted recommendations have changed. When evaluating brands, AI engines focus less on marketing narratives and more on customer experience.
Many brands still approach AI visibility as an SEO problem.
AI recommendation engines rely on reviews, comparisons, and customer signals to decide which brands to surface. According to [MarTech](https://martech.org/customer-experience-outweighs-brand-in-ai-assisted-shopping/), these engines focus less on marketing narratives and more on customer experience when evaluating brands.
AI recommendation engines rely on repeated external signals to determine which brands feel trustworthy, reliable, and relevant to a specific prompt.
Twilio announced a new conversation layer today at SIGNAL 2026, comprising three components designed to connect data, channels, and both human and AI agents for a continuous customer experience, addressing fragmented interactions across chat, voice, and email.
This week's updates in AI-powered martech, as reported on April 30, 2026, show companies shifting AI from analysis to execution across various tools, including adMarketplace placing ads in AI search responses and Braze automating campaign decisions. According to MarTech, these developments involve Braze adding features to coordinate marketing tasks and ASAPP introducing agents for customer service tasks.