Businesses that have long relied on search engine optimisation to drive leads and sales are racing to adapt to the rise of answer engines , AI-driven systems that deliver direct answers and, increasingly, commerce experiences inside the result itself. According to the report by Forrester, titled "Zero-Click Search Goes Shopping," this trend is compressing the traditional purchase funnel by enabling personalised shopping interactions without sending users to merchant sites, a shift Forrester calls "zero-click shopping." [1][2]
Forrester principal analyst Nikhil Lai urges caution against treating Answer Engine Optimisation (AEO) as a wholly separate discipline from SEO. "One of the most common mistakes companies make is overestimating the difference between answer engines and search engines," he says, adding that both require "precise, straightforward content that bots can access the clearest possible way." That continuity should shape how companies marshal content, metadata and technical infrastructure. [1]
A central technical divergence is which crawlers power the new answer engines. Lai and the Forrester report note that many AI services, including ChatGPT, Microsoft Copilot and Perplexity, draw on Bing’s index and bots to varying degrees; sites optimised only for Google may therefore be under‑represented in AI answers. In practice that means ensuring critical pages serve HTML (or similarly easily rendered formats) rather than relying on client-side Javascript, and using structured data so younger, less capable crawlers can interpret context. The report also highlights IndexNow , Bing’s protocol for being notified about new content , as a tool companies should adopt to prompt faster crawling. [1][2]
The content calculus is changing from purely ranking signals towards a mix of reach, format and relevance. Forrester and industry commentators point out that answer engines tend to have far higher crawl-to-referral ratios than traditional search , Forrester cites a crawl-to-referral ratio for some answer engines in the tens of thousands to one, compared with roughly 5 to 1 for Google , meaning large volumes of content may be scanned without sending proportional traffic back to the publisher. That intensifies the need to ensure content not only exists but answers the kinds of prompts users give these engines. [1]
Quality remains decisive. Lai advises that "the most important thing content needs to do is directly respond to the prompt that’s being used on the engine," noting that answer engines map words in prompts to words in content and that users frequently ask many follow-up questions. Practically, this drives better use of FAQ-style copy, comparison pages (including candid competitor comparisons where appropriate) and media such as infographics and photographs to add the "semantic richness" that models use to assess relevance. The Forrester report warns marketers that because some answer engines privilege third-party signals or what others say about a brand, earned and paid distribution across the open web matters as much as on-site optimisation. [1][2]
The strategic implications extend beyond SEO teams. Forrester survey data from 2025 shows answer engines outperform social media across the discovery, evaluation and commitment stages by 12 percentage points, suggesting AEO is a cross‑functional opportunity spanning content, IT, PR, brand and paid channels. Lai argues companies should reorganise responsibilities now to capture the early benefits; otherwise, they risk ceding visibility within the new decisioning layer that sits above traditional website traffic. [1]
Not all authorities agree on whether new labels such as AEO or Generative Engine Optimisation (GEO) require distinct technical frameworks. Google has publicly stated that standard SEO practices are sufficient for ranking in AI overviews and AI Mode, implying that brands need not adopt separate optimisation silos to appear in AI answers. Other industry voices, such as recent Forbes commentary, treat AEO and related terms as strategic lenses , especially in B2B , that reveal high‑intent signals and competitive positioning, while another Forbes analysis cautions the proliferation of acronyms has introduced confusion for marketers. These differing viewpoints underline that the field is evolving and that firms should balance pragmatic technical fixes with a broader strategic approach to content and distribution. [7][3][5]
Looking ahead, some practitioners propose an even broader evolution , from AEO to Generative Engine Optimisation , that emphasises structuring content to mirror user questions, improve accessibility, and embed schema markup so generative models can produce clearer, verifiable answers. According to a Forbes overview, this progression reflects mainstream AI adoption, rising voice commerce and the need to make answers directly useful inside AI experiences. For marketers, the practical roadmap is thus dual: maintain core SEO hygiene while expanding content formats, distribution and cross‑team workflows to meet the demands of answer engines. [6][4]
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- [1] (Chief Marketer) - Paragraph 2, Paragraph 3, Paragraph 4, Paragraph 5, Paragraph 6, Paragraph 7, Paragraph 8
- [2] (Forrester report) - Paragraph 1, Paragraph 4, Paragraph 5
- [3] (Forbes) - Paragraph 7
- [4] (Forbes) - Paragraph 8
- [5] (Forbes) - Paragraph 7
- [6] (Forbes) - Paragraph 8
- [7] (Search Engine Journal) - Paragraph 7
Source: Noah Wire Services