The State of AI Distribution 2026 (Mid-Year)

AI Distribution is the work of getting a brand named and recommended when a buyer asks an AI answer engine. Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) are the practitioner labels for the core of that work, so this report uses them where the practice is meant and treats AI Distribution as the category they sit inside. A year ago these were terms used by a handful of vendors. Mid-2026 the work is a line item on B2B growth planning docs. What follows is a working read of where the category sits: what buyers appear to be doing, what the four major engines reward, how tooling is grouping, and which gaps have not yet been filled. It is grounded in publicly visible engine behaviour, product-team observations from early-access work, and the small set of third-party research we consider credible. Where a claim depends on a dataset we do not have, we say so.

Demand side: what buyers appear to be doing

The clearest shift is in the middle of the funnel. Brand-name searches still route through Google. Shortlist and comparison queries are visibly moving toward the answer engines, based on what buyer research vendors like Gartner, Forrester, and the analyst-facing surveys published through 2025 have named as their headline finding. We are not going to invent a proprietary survey to add to that stack. The directional read from public sources:

• Buyer research on shortlist and comparison decisions has visibly split off from Google as the sole surface. Multiple analyst reports through 2025 called this the fastest single shift in B2B buying behaviour since the move to mobile.
• Technical buyer categories (developer tools, infrastructure, API-first SaaS) appear to be leading the shift, driven partly by Perplexity's default of showing its citation trail alongside the answer.
• Google still owns brand-name and support queries. AEO is not replacing Google search; it is displacing the middle of the funnel while brand-search and long-tail SEO continue as before.

The pattern-recognition read: when the ICP is a technical B2B buyer, an answer-engine query now sits between the trigger and the browser tab often enough that a brand missing from the answer is missing from the shortlist. We have not fielded our own survey to pin a percentage on it, and we would rather not add another number to the pile that is impossible to reproduce.

The engines, in scope

Cross-engine citation share is one of the most-asked-about numbers in this category, and it is one we do not yet publish, because our current opt-in dataset is not large enough to source honest per-engine percentages. That analysis will land here when the sample crosses the threshold at which the numbers are defensible. In the meantime, what can be said honestly about the four majors from their public behaviour:

• ChatGPT. Anchor surface for most buyers. The consumer-familiar default. Answers are usually terse, cite fewer sources than Perplexity by design, and reward brands that appear across multiple retrieval passages rather than a single hero page.
• Perplexity. Ships visible source citations by default, which changes the reader's incentive to click through. Over-indexes with technical buyers who value seeing the citation trail. Business tier is maturing and taking share in the shortlist-query segment.
• Google AI Overview. The logged-out research path. Buyers running comparative queries without an OpenAI or Anthropic account default to Overview more often than any dedicated answer engine, and Overview's ranking behaviour visibly leans on classical SERP authority alongside newer retrieval signals.
• Gemini. Concentrated on Workspace-integrated flows and the mobile Android default. Punches above weight on prompts that touch Gmail, Docs, or Sheets, which is a real segment in B2B and worth watching for integration-adjacent categories.
• Claude. Smaller answer-engine footprint than the others but the one Anthropic-first shops route through by default. Technical decision-maker audience skews the qualitative feel of Claude citations toward research-heavy prompts.

Directional read for the second half of 2026: Perplexity looks likely to keep taking share of shortlist queries from ChatGPT as the business tier matures. We would not stake a percentage on it. The observable behaviour is that Perplexity's citation-visible answer format wins where a buyer is comparing more than two options, and that segment is the one where AEO work has the highest revenue impact.

Tooling landscape

Three tiers have emerged, and they are separated more by workflow than by feature list. Prices are public in the categories where vendors publish them; ranges are indicative rather than exact.

• Enterprise tier. Annual-contract tools sold to Fortune-500 growth ops teams, typically at five-figure minimums. Dense dashboards, dedicated consulting layer, weak or absent content-fix layer. Best fit when there is a full-time analyst who can turn measurement into a shipped fix themselves.
• Self-serve tier. Founder-priced monthly. Ships the measurement layer and the fix layer together. Best fit for lean B2B teams that need to be shipping fixes on Monday morning rather than reading a dashboard on Friday. Searchalong AI sits here.
• Free tier. Point-in-time score tools. Useful as a diagnostic on day one and not as an ongoing workflow, because a citation lost between refreshes is a citation the tool cannot help recover.

The observable pattern: enterprise-tier dashboards are richer than self-serve-tier dashboards, and the enterprise-tier teams that publicly discuss their AEO work do not appear to be moving faster than the self-serve teams that do the same. Measurement without a paired fix workflow tends to read as decorative once a category is a year old, whether the price tag is high or low.

The unsolved gaps

Five gaps show up in every buyer conversation we have had this quarter. They are visible to anyone doing the category work; naming them here is a checklist for the next 12 months of vendor building, not a proprietary insight.

1. Attribution to pipeline. Every current tool reports cite-rate. None of them reliably reports the revenue impact of a five-point cite-rate lift. Attribution work remains a manual analyst exercise, and the vendors that solve it credibly will define enterprise procurement for the next 2 years.
2. Multi-brand operator surface. Boutique agencies running ten or more client brands still work out of ten separate accounts. The category has not shipped a dedicated control plane, and the ones building toward it are early.
3. Community citation coverage. Reddit and Substack are appearing more often in the top-three cited sources on comparison prompts, particularly for developer tools and mid-market SaaS. Almost no tool measures Reddit specifically, which leaves a citation surface unmonitored.
4. Voice attribution on generated content. LinkedIn ghostwriter tools ship without stylometric guardrails. Founders using them privately report worry about the voice being spotted; the category has not yet given them a QA layer that closes the loop before publish.
5. Engine-specific tuning. The four majors rank differently and update on different cadences. Most tools treat them uniformly. The next generation is likely to expose per-engine levers as a first-class configuration.

A read on the second half

These are working expectations, not confident forecasts. Reasonable observers can disagree, and some of them will look wrong by December. That is the point of writing them down.

1. AEO and GEO settle as the practice labels inside AI Distribution. AEO leads in commercial tooling, GEO holds in enterprise and academic writing, and both name work that sits under AI Distribution as the category buyers plan around. The vocabulary conversation stops being interesting to the buyer once the category above the labels has a name.
2. Perplexity keeps taking shortlist-query share. The business tier maturing changes the mix. We are not going to stake a specific percentage on it because we do not have the measurement to defend one.
3. The first enterprise AEO platform gets acquired by a mainstream marketing suite. Most likely acquirer profile: HubSpot, Adobe, Marketo, or a private-equity roll-up assembling a growth-analytics stack.
4. Reddit-specific tooling ships. A dedicated product for tracking and lifting citations in Reddit threads becomes the first credible answer to the community-citation gap.
5. The self-serve tier settles into a small number of durable winners. Founder-priced, self-serve, content-fix-first, with attribution work distinguishing them. The tail continues but the top of the category consolidates.
6. JSON-LD FAQPage becomes universal. Every commercial-intent page ships it by year end, and the marginal lift from adding it drops toward zero. The next lever becomes what is inside the schema, not whether the schema exists.

If any of these read as wrong, we would rather hear the counter-case than not. Email hello@searchalong.xyz with the reasoning. The next edition of this report at year end will include a scorecard against these calls and a fresh set for the following half.