AI Analytics Tools Pricing: Conversational Analytics Cost, AI BI Tools and Platform Rates

Every serious BI vendor now sells an AI analyst, and no two of them bill for it the same way. That is the whole problem with pricing AI analytics tools in 2026: the seat price on the front of the pricing page tells you almost nothing about what the AI will cost. Some vendors meter tokens. One meters questions. Two of them hide the charge inside a capacity or account fee you buy for other reasons. The table below is every rate we could verify from a vendor's own price list in August 2026, with the date each one was read.

What every major vendor charges for the AI layer

There are only three billing patterns, and they fail differently

Strip the marketing away and every row in that table is one of three models. Knowing which one you are buying tells you more about your future bill than the headline rate does.

Token meters (Looker, Grafana, and Databricks Genie from next February) charge for inference. They are honest and completely unforecastable before deployment, because nobody knows how many tokens a question costs until people start asking questions. Looker's own numbers show how tight the included pools are: the Standard instance pool is 60M input and 1.2M output data tokens a month, which at Looker's list rates is worth $180.00 and $24.00 respectively. Every tier gets fifty times more input than output while output costs 6.7 times more, so output is what runs out first at every tier.

Question caps are ThoughtSpot's approach, and so far ThoughtSpot is alone in it. A Pro seat is $50 a month and carries 25 Spotter questions. Divide one by the other and each AI question costs $2.00 at full use, which is the only per-question figure any vendor in this market lets you compute. Finance departments will prefer this. Analysts will not, because 25 questions a month is roughly one per working day and an AI analyst that you have to ration is not doing the job you bought it for. ThoughtSpot clearly agrees, since Unlimited Spotter appears in its own add-on list rather than in the seat price. The full breakdown, including the tier ceilings, is on our ThoughtSpot pricing page.

Capacity tolls are the least visible of the three. Power BI Copilot has no price of its own; it appears only in the Fabric capacity column, and Fabric capacity meters at $0.18 per capacity unit hour. QuickSight does something similar in reverse: the AI features themselves are attached to Pro seats, but switching any of them on activates a $250 per month per-account infrastructure fee whether one person or one hundred use it. In both cases the AI is cheap and the thing it requires is not.

What 50 people actually costs, on published rates

Take a 50 person team that wants everyone to be able to ask questions in plain English, and price it on list. Only two of the six vendors can be costed honestly, which is itself the finding.

Two of those four rows say the quiet part out loud. Google publishes no dollar figure for Looker Standard, Enterprise or Embed, and Microsoft publishes no figure for the Fabric SKU that Copilot needs. You can price the AI and not the platform, or the platform and not the AI, but not both. Our Looker pricing and Power BI pricing pages set out exactly what each vendor does and does not publish, and the BI tools comparison puts all of them in one table.

Five questions to ask before you sign

• Is the AI metered in tokens, questions or capacity? Ask which, in writing. It determines whether your bill is forecastable at all.
• What is included, and what happens when it runs out? Included pools are small everywhere. Ask for the overage rate and whether unused allowance rolls over. At Looker it does not.
• Do discounts apply to the AI line? Grafana states plainly that they do not apply to tokens. If a vendor will not answer this, assume the same.
• Which tier does the AI actually start on? ThoughtSpot's natural-language search begins at $50, not at the $25 entry tier. Copilot begins at a Fabric capacity, not at a Power BI seat.
• What does the AI need underneath it? Databricks Genie is $0.070 per DBU against SQL Serverless at $0.70, exactly ten times more, and Genie needs that serverless compute to run. The cheap meter is attached to an expensive one.

Where the money goes if you already have a database

Read the table from a distance and one thing stands out: most of what you pay in this market is not for the AI. It is for the BI platform the AI is bolted onto. If your data already lives in Postgres, MySQL, Snowflake or BigQuery and what you actually want is answers rather than dashboards, you are being asked to buy a semantic layer, a modeling project and a seat for every reader in order to get a question answered.

That is the gap Agentsql fills. It connects read-only to the database you already run, turns a plain-English question into SQL, executes it, and returns the answer with a chart, the table and the SQL itself, so an analyst can check the logic before anyone acts on it. There is no per-question allowance and no capacity to size. If the questions you need answered are coming from customers on your website rather than from your warehouse, that is a genuinely different product and you want a chatbot trained on your own site content instead, not an analytics platform.

Pricing the alternatives properly is the point of this whole cluster. Start with ThoughtSpot pricing if conversational analytics is the requirement, QuickSight pricing if you are already on AWS, and Databricks pricing if the question is whether Genie can replace a separate tool. If you would rather just point something at your existing database, our plain-English layer over the database is the shortest route, and our pricing is a flat monthly figure with no query cap attached.