Most "AI search in 2027" content is a headline with a year attached to it — a confident-sounding number nobody plans to check back on. The honest version of this exercise has to include checking the last round of confident numbers against what actually happened, because one of the biggest AI-search predictions of the last few years didn't hold up. Here are five predictions for 2027, each tied to a named forecast or measured study, including that correction.
1. Traditional search keeps losing ground in 2027 — but not at the cliff-drop pace a 2024 forecast promised
In February 2024, Gartner predicted that traditional search engine volume would drop 25% by 2026 as users shifted to AI chatbots and virtual agents. It was the single most-cited AI-search statistic of 2024 and 2025. It also, by the numbers available heading into 2027, did not happen at that scale: Google retained roughly 90%+ of search market share, according to a 2026 retrospective analysis citing Statista and SimilarWeb data — AI Overviews changed how results display and kept users inside Google's own ecosystem rather than causing the broad exodus the forecast implied.
Search Engine Journal raised the same doubts before the deadline even arrived, pointing to Gartner's own June 2023 research finding only 8% of customers had used a chatbot in their most recent customer service experience, with just 25% of those willing to use one again — a low-adoption baseline that made a 25% volume drop within two years look aggressive even at the time it was published.
| Forecast vs. outcome | Figure |
|---|---|
| Gartner's Feb 2024 forecast: search volume drop by 2026 | 25% |
| Google's search market share heading into 2027 | ~90%+ |
| Chatbot use in most recent customer service interaction (Gartner, Jun 2023) | 8% |
Sources: Gartner, "Search Engine Volume Will Drop 25% by 2026" (Feb 2024); Search Engine Journal skepticism analysis; 2026 retrospective citing Statista/SimilarWeb.
The credible 2027 prediction isn't a cliff — it's gradual, uneven erosion concentrated on a specific slice of queries, which is exactly what prediction two measures directly.
2. Zero-click keeps compounding through 2027 — concentrated hardest on AI Overview queries, not search overall
Where search volume actually is eroding shows up more precisely in click behavior than in traffic totals. SparkToro's June 2026 analysis of Similarweb clickstream data found 68.01% of U.S. Google searches ended without a click between January and April 2026. That's the headline number — but the more useful one for 2027 planning is the gap: on the roughly 20%+ of Google searches where an AI Overview appears, click-through rates drop by nearly 60% compared to queries without one.
| Metric | Figure |
|---|---|
| U.S. Google searches ending with zero clicks (Jan–Apr 2026) | 68.01% |
| Share of Google searches where an AI Overview appears | 20%+ |
| Click-through drop specifically on AI-Overview queries | ~60% |
Source: SparkToro analysis of Similarweb clickstream data, published June 2026.
The 2027 prediction that follows from this data isn't "clicks disappear" — it's that the gap between AI-Overview-eligible queries and everything else keeps widening. Being the source an AI answer cites becomes the main lever on that growing subset of queries, even as overall search volume holds up better than the 2024 forecasts suggested.
3. Over 40% of agentic AI projects get canceled before 2027 is out
Gartner's June 2025 forecast is specific and blunt: more than 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls. Senior Director Analyst Anushree Verma put the underlying problem plainly: "Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied." Gartner estimates only about 130 of the thousands of vendors marketing "agentic AI" have genuine agentic capability — the rest are largely rebranded chatbots, assistants and RPA tools, a pattern Gartner calls "agent washing."
A January 2025 Gartner poll of 3,412 webinar attendees found 19% had made significant investments in agentic AI, 42% conservative investments, 8% no investment, and the remaining 31% taking a wait-and-see approach.
Source: Gartner, "Over 40% of Agentic AI Projects Will Be Canceled by End of 2027" (June 2025).
The 2027 shakeout doesn't mean agentic AI fails as a category — it means budget concentrates in the projects that can show measurable results past the pilot stage. The same logic applies to AI-visibility and AEO work funded under the same umbrella: programs tied to citation data and pipeline survive the cut; hype-driven pilots don't.
4. Generative AI's share of AI software spend hits 35% by 2027, up from 8% in 2023
Gartner's Artificial Intelligence Software forecast puts total AI software spend on a path to $297.9 billion by 2027, a 19.1% CAGR — and within that total, generative AI's share rises from 8% of AI software spend in 2023 to 35% by 2027. That's not a prediction about whether AI budgets grow; Gartner already expects them to. It's a prediction about where inside that growth the money is pointed: increasingly at generative capabilities rather than the analytical AI tooling that dominated the category before 2023.
Source: Gartner, "Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide."
For marketing teams, this is the infrastructure-spend mirror of the budget case made in how to fund AEO from the 2027 budget without asking for new money: the reallocation isn't hypothetical, it's already the direction Gartner's own software forecast says enterprise spending is moving.
5. AI answers go multimodal — and AEO stops being a text-only discipline
Gartner predicts 40% of generative AI solutions will be multimodal — natively handling text, image, audio and video — by 2027, up from just 1% in 2023. Distinguished VP Analyst Erick Brethenoux frames the shift as models "evolving towards models natively trained on more than one modality," which "helps capture relationships between different data streams" across every AI-human touchpoint, not a narrow set of use cases.
Source: Gartner, "40% of Generative AI Solutions Will Be Multimodal By 2027" (Sept 2024).
The practical consequence for AEO: being citeable can no longer mean well-structured prose alone. Alt text on images, transcripts on video and audio, and structured data that describes non-text content all become part of what an AI system can pull from and cite — and brands that only optimized the article body are optimizing for a shrinking share of how these models will actually answer.
What this means for 2027 planning
None of these five predictions require believing search collapses overnight. They add up to something more specific and more actionable: erosion concentrated on AI-Overview queries rather than search broadly, a shakeout that rewards measurable AEO programs over hype pilots, spending that's already moving toward generative infrastructure, and an answer format that stops being text-only. Build for that version of 2027, not the cliff-drop version that didn't happen in 2026.
See where your brand stands today with a free AI visibility check, or read the 2026 predecessor to this piece for the entity-authority fundamentals this builds on. For the discipline itself, start with what AEO is.
The takeaway: The reliable 2027 predictions aren't the dramatic ones — they're the ones a named forecaster is willing to attach a specific, checkable number to, including the one from 2024 that didn't hold up. Plan around gradual AI-Overview-driven erosion, a funding shakeout that rewards measurable programs, generative infrastructure spend that's already moving, and answer engines that read images and audio, not just text.
Sources
- Gartner — "Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents" (Feb 2024). · primary
- Search Engine Journal — "7 Reasons To Be Skeptical of 25% Search Volume Drop by 2026," citing Gartner's own June 2023 chatbot-adoption research. · secondary analysis of primary data
- 2026 retrospective analysis of search-traffic outcomes vs. the 2024 forecast, citing Statista and SimilarWeb data (April 2026). · secondary report
- SparkToro — analysis of Similarweb desktop/mobile clickstream data, U.S. Google searches, Jan–Apr 2026 (published June 2026). · primary analysis of licensed panel data
- Gartner — "Gartner Predicts Over 40% of Agentic AI Projects Will Be Canceled by End of 2027" (June 2025), incl. Jan 2025 webinar poll of 3,412 attendees. · primary
- Gartner — "Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide." · primary
- Gartner — "Gartner Predicts 40% of Generative AI Solutions Will Be Multimodal By 2027" (Sept 2024). · primary
Frequently asked questions
Will traditional search traffic collapse by 2027?
What share of searches already end without a click?
Are agentic AI projects actually going to fail at that rate?
Does AEO still matter if AI answers become multimodal?
Definitions used in this article
- Zero-click search
- A zero-click search is a search query that ends without the user clicking through to any result — the answer is fully satisfied on the search results page itself, including inside an AI Overview. SparkToro/Similarweb measured this at 68.01% of U.S. Google searches in early 2026.
- Agentic AI
- Agentic AI refers to AI systems that can take multi-step actions toward a goal with limited human intervention, rather than simply responding to a single prompt. Gartner estimates only a small fraction of vendors marketing "agentic AI" products currently have genuine agentic capability.
- Multimodal AI
- Multimodal AI is a generative AI system trained to natively process and generate more than one type of content — text, image, audio and video — rather than text alone. Gartner projects 40% of generative AI solutions will be multimodal by 2027, up from 1% in 2023.