Answer engines are compressing buying into one reply

Answer engines – A growing share of software and consumer shoppers start their product research with AI chatbots or answer-style results, compressing what used to take hours into a single prompt. At the same time, budgets still largely flow to traditional SEO and sponsored sea

The first thing many buyers see now isn’t a list. It’s an answer.

In 2026. that shift is starting to feel less like a marketing trend and more like a change in how commerce works. Buyer journey compression—reducing the time to find and evaluate products or services—has already moved from the Yellow Pages to the first page of search results. Now, generative AI is compressing product discovery into a single AI-generated response.

The comparison is simple: the Yellow Pages bundled local services into one book; search engines bundled the world’s information into the first page; answer engines bundle product discovery into one reply.

Buyer journey compression is the process of reducing the time to find and evaluate products or services. Over time, the “compression” has happened in distinct eras: the Big Book era (Yellow Pages), the First Page of Search era (search engines), and the Answer Engine era (AI search).

The Yellow Pages era ran as a bustling classified industry with a 30% operating profit margin. growing into a multi-billion-dollar industry by the 1980s. It peaked in 2007. right as the internet era gained steam. when buyers increasingly turned to the World Wide Web to find products and services. After that, the industry shrank in both relevance and revenue.

Then came the First Page of Search era. Google. founded with a laser focus on improving search quality by organizing the world’s information. relied on PageRank to change buyer behavior for millions. Within a few pages of search results, many buyers found helpful resources, built shortlists, and secured solutions. Marketers scrambled to earn their way onto the first page, where clickthrough rates were highest.

In the Answer Engine era, the buyer’s workflow is different. Instead of sorting through multiple websites returned by blue links, AI search provides an answer directly. One prompt—then an answer. Generative AI can reason over a vast amount of data without requiring the buyer to traverse dozens of results.

That’s where the data becomes harder to ignore. A G2 research report. based on a March 2026 survey of 1. 000 B2B software buyers. found that AI chatbots have fundamentally changed how 93% of respondents conduct research. The shift described in the report is consistent with a broader thesis: buyers of all types flock to the most productive tool that helps them get the right product at the right time.

On how many buyers are using AI search instead of traditional search, the split is described as roughly 50-50, but moving quickly.

On the B2B side, 51% of software buyers start their purchase journey on ChatGPT. On the B2C front. a SEMrush 2026 report says 57% of consumers use chatbots to narrow down their shortlists. and about half return to AI search to make their final decision. The expectation heading into 2027 is that the fork will lean more toward answer engines—especially as Google makes AI Mode more visible for searchers.

The biggest change may not be just adoption, but behavior. G2’s research found the most common first prompt buyers use is: “give me the best ______ for ________.” The goal isn’t a collection of websites; it’s a shortlist.

Historically, B2B buyers invested hours building that shortlist. In the answer-engine era, what took hours now arrives through a single prompt. A late 2025 report by 6sense adds a concrete success marker: 9 out of 10 buyers chose the winning vendor from their day-one shortlist.

That produces a pressure point for anyone trying to “win the answer.” If a buyer’s decision starts from an AI-generated shortlist, losing traffic from zero-click sessions is only part of the risk. The more immediate threat is being boxed out of the process earlier than ever.

And yet, budgets haven’t fully caught up.

Despite the market split, the lion’s share of marketing spending still flows to a search-engine-based buyer journey. Mordor Intelligence found that companies will spend $83 billion on SEO services this year. with marketers also spending another $1.33 billion on SEO software. Meanwhile, Answer Engine Optimization spending remains far smaller. QYR Research estimates that 2026 AEO spending will be around $1.5 billion.

For perspective: for every dollar marketers spend on AEO this year, they will spend $60 on SEO.

The reporting then turns practical—how marketers might move dollars from SEO toward AEO. One suggested cut candidate is generic blogs aimed at SEO, including low-intent “what is” articles or keyword-variant content. The guidance also calls for consolidating duplicate SEO tools. especially dashboards that don’t connect clearly to pipeline in a “zero-click environment” created by answer engines.

It also points to a shift in link strategy toward authority-building, while warning not to cut technical SEO, because it remains foundational to organic traffic and stability between these two periods.

As for what the “right” budget split could look like. research from Conductor—canvassing 250 leading-edge enterprise marketers—found they planned to invest 12% of their digital budget in AEO in 2026. That still leaves SEO with the majority share. but it’s framed as a possible start toward catching up with where buyers begin their research.

Sponsored search is a separate battleground. In the age of AI search, the value of Google Ads is described as falling. Triple Whale’s 2025 Google Ads benchmark—based on more than 18,000 brands—found Google Ads ROAS fell 10.03% year over year, conversion rates fell 9.28%, and CPA rose 12.35%.

The argument for why this happens tracks with the behavior shift: as organic reach declines in a zero-click world. marketers may throw more money at ads that no longer perform the way they once did. A historical parallel is offered through the Yellow Pages-to-internet migration period. when advertisers leaned into spending from 2004 to 2007 to maintain foot traffic during the transition.

There is also movement toward paid AI visibility. Earlier this year, OpenAI introduced its version of an ads product to enable brands to invest in paid AI visibility. Early feedback is described as suggesting pricing was too aggressive, and campaigns faced underdelivery. Digiday reported “chronic underdelivery” for early campaigns, while OpenAI has since shown progress, with fill rates rising to 50%.

With OpenAI placing paid AI visibility inside its future revenue strategy, the expectation is improvement over the next year—pricing, delivery, measurability, and results. The practical recommendation is to run a pilot by the end of 2026, using money that can be afforded to be lost, to learn.

Google, for its part, is also moving: it has introduced ads for AI Overviews, claiming AI Overviews performance rivals Sponsored Search, positioning it as a potentially safer testing ground for reallocated budgets.

The report adds that while there is no announcement of ads coming to the Gemini app yet. Google has introduced ads for AI Mode. AI Mode is described as a new service that lets users prompt for an AI-generated answer and then enter chat—like Gemini—to go further. TechCrunch reported that advertisers already using Performance Max. Shopping. and Search campaigns with “broad match” will be eligible for ads to appear in AI Mode. Users in the U.S. will see ads—specifically Search and Shopping ads for now—in AI Mode across desktop and mobile.

The underlying question remains: is the shift to AI search permanent, or will buyers return to traditional search engines?

One stated finding is that people report greater productivity with AI search, with sentiment jumping between 2025 and 2026. When a quicker route from point A to point B is found. the reporting says buyers tend to stay on that path. The message is clear: once the workflow changes, going back feels like choosing slower—and harder—ways of working.

For marketers, the suggested preparation is direct: plan on AI search becoming the dominant way people find products and services in the near future, and if possible, create a three-year plan to transition and meet the moment.

For those still debating a low-cost AI visibility solution while taking meetings to discuss the trend, the warning is that time may not be on their side. The closing metaphor leans into urgency: the best time to plant a tree was 20 years ago; the next best time is today.

The piece ends by inviting readers to subscribe to a LinkedIn newsletter titled “AI Update with Tim Sanders,” framed as a continuing stream of AI research and insights.

AI search answer engines buyer journey compression AEO SEO spend Google Ads AI Mode ChatGPT G2 survey 6sense SEMrush Triple Whale OpenAI ads