The State of AEO 2026
How marketing teams are measuring, budgeting for, and winning visibility in AI answer engines.
Preliminary · placeholder figures
PLACEHOLDER DATA — the figures below are illustrative and clearly marked while the 2026 survey is in the field. The page structure, methodology, and schema are final; numbers will be replaced with verified results on publication.
Executive summary: the top findings
The five headline findings from The State of AEO 2026, each written to stand on its own — and each linking to its full data below.
- 01
42% of teams now measure AI visibility per engine — more than double the 19% who did a year earlier.
See the data → - 02
Teams allocate a median 15% of their search budget to AEO in 2026, up from 6% in 2025.
See the data → - 03
ChatGPT is the top optimization target at 78% of teams, ahead of Google AI Overviews at 71%.
See the data → - 04
Only 34% of teams track whether AI engines actually cite them — the field's biggest measurement gap.
See the data → - 05
Answer-first content is the highest-rated AEO tactic, called effective by 68% of teams.
See the data →
Cite this study
AEO Canon. (2026). The State of AEO 2026. https://aeocanon.com/state-of-aeo-2026
https://aeocanon.com/state-of-aeo-2026Free to cite and republish with attribution under CC BY 4.0. A link to the canonical URL is appreciated.
The findings
How many teams measure AI visibility per engine?
42% of teams now measure AI visibility per engine, more than double the 19% who did a year earlier.
Show data table
| Response | Share |
|---|---|
| Measure per engine | 42% |
| Measure overall only | 33% |
| Don't measure AI visibility | 25% |
Per-engine measurement is becoming standard practice because answer engines overlap on only a small share of the sources they cite — so a single blended visibility score hides where you are actually winning or losing. The remaining quarter of teams that don't measure AI visibility at all represent the clearest opportunity gap in the field.
# link to this findingHow much of search budget goes to AEO?
Teams allocate a median 15% of their search budget to AEO in 2026, up from 6% in 2025.
Show data table
| Response | Share |
|---|---|
| 0–5% of search budget | 28% |
| 6–15% | 34% |
| 16–30% | 25% |
| 31% or more | 13% |
Budget is shifting from pure ranking work toward earning citations, but most of the spend is still concentrated at the low end — 62% of teams put 15% or less of their search budget into AEO. The leading edge (31%+) is small but growing fastest year over year.
# link to this findingWhich answer engines do teams optimize for?
ChatGPT is the top optimization target at 78% of teams, ahead of Google AI Overviews (71%) and Perplexity (49%).
Show data table
| Response | Share |
|---|---|
| ChatGPT | 78% |
| Google AI Overviews | 71% |
| Perplexity | 49% |
| Gemini | 38% |
| Microsoft Copilot | 22% |
Optimization effort tracks audience usage and citation volume rather than raw model capability. Because the same answer-first, well-evidenced, technically reachable content competes across every engine, most teams optimize once and target the top engines simultaneously rather than building per-engine pages.
# link to this findingWhich AEO tactics do teams rate most effective?
Answer-first content is the highest-rated AEO tactic, called effective by 68% of teams; structured data trails at 41%.
Show data table
| Response | Share |
|---|---|
| Answer-first content | 68% |
| Original data / research | 57% |
| Off-site brand mentions | 52% |
| Freshness / updating | 47% |
| Structured data | 41% |
The ranking mirrors the published research: tactics that make content easier to extract and trust (answer-first writing, original data, off-site mentions) outrank purely technical markup. Structured data rates lowest of the five — useful infrastructure, but not the citation lever teams once assumed it was.
# link to this findingDo teams track whether AI engines cite them?
Only 34% of teams track whether AI engines cite them — the field's biggest measurement gap.
Show data table
| Response | Share |
|---|---|
| Track AI citations today | 34% |
| Plan to within a year | 29% |
| No plans to track | 37% |
Citation is the unit of AEO success, yet two-thirds of teams still can't say whether an engine named them in an answer. The 29% who plan to start within a year suggest tooling and process — not belief — are the bottleneck.
# link to this findingHow has AI search affected organic traffic?
48% of teams report fewer organic clicks because of AI search, while 29% report higher-quality traffic from AI referrals.
Show data table
| Response | Share |
|---|---|
| Fewer organic clicks | 48% |
| No clear change yet | 23% |
| Higher-quality AI referrals | 29% |
The headline story is fewer clicks, but the second story matters more for strategy: nearly a third of teams say the visitors who do arrive from AI surfaces convert better, because they arrive further along in their decision. The shift is less about volume than about where value concentrates.
# link to this findingMethodology
The State of AEO 2026 surveyed 412 respondents via an online self-administered survey. Respondents were in-house and agency marketers responsible for SEO/AEO at organizations of all sizes, primarily in North America and Europe.
- Sample size
- 412 respondents
- Field dates
- January 12, 2026 – February 20, 2026
- Method
- Online self-administered survey
- Margin of error
- ±4.8% at a 95% confidence level
- Population
- In-house and agency marketers responsible for SEO/AEO at organizations of all sizes, primarily in North America and Europe.
- License
- CC BY 4.0
PLACEHOLDER: sample size and field dates are illustrative pending the 2026 fielding. Percentages may not sum to 100 due to rounding or multi-select questions.