We indexed 30 AI GTM tools: the 2026 pricing and capability index
Cite this dataset: DOI 10.5281/zenodo.20632766 (CC-BY 4.0)
Every "best AI tools" list is a snapshot of someone's opinion. This is the underlying data. We track 30 AI go-to-market tools across the three verticals a revenue team actually buys for, marketing and content, SEO and generative engine optimization, and sales and outbound, and we publish the entry price, pricing model, pipeline job, and our merit-placed tier for each. The table below is live: sort any column, filter by vertical, or search. The numbers feeding our roundups all come from here, and the dataset is open under CC-BY so you can use it too.
The interactive index
| Tool ⇅ | Vertical ⇅ | Job ⇅ | Entry (USD/mo) ⇅ | Pricing model ⇅ | Tier ⇅ |
|---|
Three things the data shows
The entry-price floor is low, but the real cost is in the metering. More than half the priced tools start under $50 a month, which makes "AI is cheap" feel true at signup. It is not the number that bites: per-seat multiplication, credit overages, video minutes, and per-engine add-ons routinely push the real bill 1.3 to 2 times the entry price. The index shows the sticker; budget for the meter.
GEO is the most crowded new shelf and the least price-transparent. The SEO and GEO vertical carries the most tools in the index, and a disproportionate share of the quote-only entries sit there, because the GEO category is young and still finding its pricing floor. Expect the numbers in that vertical to move fastest, which is exactly why we date-stamp every row.
Enterprise sales tooling hides its price on purpose. Most of the null (quote-only) rows are enterprise sales-engagement and AI-SDR tools. When a vendor will not publish a number, treat the evaluation as sales-led and budget for a floor several times the per-seat sticker once minimums and annual contracts are counted.
We indexed these 30 tools, then asked AI which ones it actually recommends: see the companion study, Who AI Recommends, which measures what ChatGPT, Perplexity, and Google AI Overviews cite when buyers ask. The roundups built on this data: best AI marketing tools, best GEO / AI-visibility tools, and best AI sales tools. Build a stack from it in the AI stack optimizer.
Rules and data behind this page
What a marketing claim must substantiate, how a paid placement must be disclosed, and how customer data must be handled are set by published federal rules rather than by any platform's best-practice blog. The sources below are the primary ones.
- FTC advertising and marketing guidance sets the federal standard for what a marketing claim must be able to substantiate.
- FTC Endorsement Guides governs how a paid or incentivised recommendation must be disclosed.
- FTC privacy and data security guidance is the authority on how customer data collected by these tools must be handled.
- SBA marketing and sales guidance is the federal reference for the go-to-market motion these tools support.
- SBA business guide covers the wider operating context a sales motion sits inside.
- Census Business Survey data publishes the official firm-size statistics that market-size and TAM claims are checked against.
- NIST AI Risk Management Framework is the reference for evaluating the AI features now embedded in most go-to-market tooling.
- Stanford HAI AI Index publishes the measured benchmarks behind AI capability claims in these products.
This page describes tools and tactics and the rules that constrain them. A reader's own jurisdiction and contracts decide what applies to them.