Best AI agents for data analysis (2026): 10 agentic analytics tools compared on actions, governance, and price

The strongest AI agents for data analysis in November 2026 are ThoughtSpot Spotter (search-style analytics with four named agents), Databricks Genie (free for users until January 31, 2027), Snowflake CoWork (per-token pricing with no seat fees), Omni (a semantic model plus scheduled condition checks), and Basedash (an AI data analyst that also writes its own feed of insights). Hex and Sigma suit teams that live in notebooks or spreadsheets, while Looker, Tableau, and Power BI add agents to platforms you may already own. The real differences are what each agent does without being asked, which actions it can take, and whether it runs with each user’s permissions.

“Agentic analytics” here means more than a chat box that writes SQL. An agent plans several queries to answer a “why” question, runs on a schedule or a trigger, and can act: post to Slack, build a dashboard, or call another tool.

How we evaluated AI data agents

We checked each vendor’s official pricing pages and documentation on November 11, 2026, against six criteria drawn from what buyers ask:

1. Multi-step investigation: can the agent plan several queries to explain why a metric changed?
2. Runs without a prompt: scheduled runs, data-change triggers, anomaly monitoring, or an unprompted feed.
3. Actions: posting to Slack, Teams, or email, building dashboards, writing back, or calling external tools, and whether risky actions need approval.
4. Governance: whether the agent runs as the user with row-level and column-level security, plus SAML SSO and SCIM.
5. Openness: an MCP server or API so Claude, ChatGPT, or Cursor can use the agent, and embedding in your own app.
6. Price and proof: a published price, a trial, and any published accuracy number.

AI agents for data analysis compared

Only ThoughtSpot, Snowflake, Hex, Tableau Next, and Basedash publish a price for the agent tier you can budget against without a sales call. Databricks and Looker don’t bill agent usage for now, but both promos end January 31, 2027.

ThoughtSpot: best for search-style analytics with named agents

Best for: enterprises that want an agent suite with anomaly monitoring on a live warehouse. Not ideal for: small teams, since Spotter isn’t on the Essentials plan.

• Pricing: Essentials $25 per user per month, Pro $50 with “Spotter AI Agents (25 queries/month per user)”, Enterprise custom, or a credit plan from $0.10 per credit. 14-day free trial, no card. Verified November 2026.
• Agent: Spotter runs root-cause analysis and multi-step deep research. KPI monitors alert on anomalies, with Slack delivery in early access, and webhooks can start workflows. Anything that writes to another app waits for user approval.
• Governance: row-level and column-level security apply to every agent; SAML, OIDC, and SCIM.
• Openness: Spotter MCP server (an add-on) and SpotterEmbed in the Visual Embed SDK.
• Accuracy: a vendor-run test reports 82.8% on the BIRD benchmark.

Databricks Genie: best value if your data is already in Unity Catalog

Best for: Databricks customers who want research-style answers at no extra license cost. Not ideal for: data that lives outside Databricks, or teams that need agents to write to other systems today.

• Pricing: no AI/BI license fee; Genie One and Genie Agents usage by users is free until January 31, 2027, with SQL compute billed separately. 14-day trial with up to $400 in credits. Verified November 2026.
• Agent: Genie Agents (formerly Genie Spaces) write read-only SQL. Agent mode builds a research plan, runs several queries, and returns a cited report, and Databricks recommends it for “explaining why a metric changed.” Genie One adds schedules, alerts, and MCP connectors for Slack, Gmail, Microsoft 365, Atlassian, and GitHub; MCP writes are in beta.
• Governance: Unity Catalog row filters and column masks are enforced per user; SAML or OIDC SSO; SCIM on Premium and above.
• Openness: Genie MCP servers, a conversation API, and an iframe embed for signed-in users.
• Accuracy: Databricks reports 84.5% on a 28-question internal test with its new Ontology.

Snowflake CoWork: best for Snowflake teams that want per-token pricing

Best for: Snowflake shops that want an agent with no seat licenses. Not ideal for: teams that need documented threshold alerts or a ready-made embeddable chat.

• Pricing: CoWork is billed in AI credits by token, $2.00 per credit with global routing or $2.20 regional, “no per-seat fees,” plus warehouse compute for the generated SQL. 30-day trial, but AI features stay off until you add a card. Verified November 2026.
• Agent: formerly Snowflake Intelligence. Deep Research splits a question into sub-investigations, and Automations email insights on a schedule. MCP connectors let it create Jira tickets, update Salesforce, or post to Slack.
• Governance: inherits row access policies and column-level security; SAML SSO and SCIM.
• Openness: a Snowflake-managed MCP server and an agent REST API; no documented iframe embed.
• Accuracy: on Basedash’s BI Bench, CoWork scored 81.1% with a 55.5-second average. See Basedash vs Snowflake CoWork.

Omni: best for agents grounded in a governed semantic model

Best for: data teams that want an agent bound to one YAML model, with scheduled checks in plain language. Not ideal for: buyers who need a public price or self-hosting.

• Pricing: not published; trials start with a meeting. AI usage beyond the included allotment is $1.00 per credit. Verified November 2026.
• Agent: the Omni Agent plans actions, runs semantic queries, and evaluates results over several steps. AI Routines in condition mode check a plain-language condition on a schedule and deliver to email, Slack, or a webhook. Chat can also create dashboards and routines.
• Governance: respects row-level security, with column-level security through access grants; SAML, OIDC, and SCIM for Entra, Okta, and Rippling.
• Openness: an MCP server with an askOmni tool, and an embeddable agent that runs queries as the embed user.
• Accuracy: no published number; AI Hub lets customers run their own evals.

Basedash: best for an AI data analyst that reports unprompted

Best for: teams that want an agent asking and answering questions on live databases and warehouses without building a semantic model first. Not ideal for: teams that need row-level security outside Postgres, SSO below Enterprise, or a plan under $1,000 per month.

• Pricing: Startup is $1,000 per month plus AI usage for up to 25 users, including $1,000 per month in AI credits. Enterprise is quote only. 14-day free trial, no card; see Basedash pricing. Verified November 2026.
• Agent: the AI data analyst writes SQL, runs it, and lists every query under Sources. Insights is a feed of AI-written posts about changes nobody asked about, generated daily, weekly, or monthly. Automations run a full analysis on a schedule or when a SQL query returns new rows (checked every 15 minutes) and deliver to Slack or email. Through MCP connectors, automations can call tools such as creating a Linear issue, and admins set each tool to always allow, needs approval, or blocked.
• Governance: row-level security for Postgres and Supabase, which also applies to Slack questions; data-source access rules hide schemas, tables, and columns from the AI. Insights run with the earliest admin’s access. SAML or OIDC SSO, SCIM, audit logs, embedding, and self-hosting are Enterprise only.
• Openness: an MCP server on every plan with tools to ask questions and create or edit dashboards and charts, all within the user’s access.
• Accuracy: 95.8% with a 20.9-second average on BI Bench, a benchmark Basedash runs itself; the method is published on the BI Bench page.

The tradeoffs: no free plan, no field-by-field chart builder, and weaker fine-grained governance than ThoughtSpot or Sigma on non-Postgres warehouses.

Hex: best for analysts who want an agent inside notebooks

Best for: data teams that want the agent to write and edit SQL and Python cells they can review. Not ideal for: companies that require SAML SSO.

• Pricing: Community free, Professional $36 and Team $75 per editor per month, Enterprise custom, with monthly AI credit grants per seat. 14-day Team trial. Verified November 2026.
• Agent: Threads plans, uses tools, and iterates; the Notebook Agent creates and modifies SQL, Python, and chart cells. Tasks (beta) schedule a Threads run and deliver it to Slack or email, on Team and Enterprise per the docs. Hex 4.0 entered public beta on November 10, 2026, for contract customers.
• Governance: the agent only searches connections the user can access, and Governed mode limits it to admin-chosen sources. SSO is Enterprise and OIDC only, with no SAML.
• Openness: an MCP server on Team and Enterprise. Embedding needs the Enterprise Embedded Analytics add-on.
• Accuracy: 80.6% with a 198.2-second average on BI Bench. See Hex vs ThoughtSpot.

Sigma: best for agents that act on spreadsheet-style workbooks

Best for: finance and operations teams that want agents writing to input tables on Snowflake or Databricks. Not ideal for: buyers who want a published price or a long trial.

• Pricing: quote only by license type. Since November 1, 2026, agent messages cost 0.1 credit each. 7-day trial. Verified November 2026.
• Agent: Sigma Assistant shows sources, a step-by-step breakdown, and the SQL. Sigma agents can run on a schedule, insert rows into input tables, and notify Slack, Teams, or email; approval prompts are skipped on scheduled runs.
• Governance: row-level security and column masking carry over to Assistant, and the agent API runs with the caller’s permissions; SAML and SCIM.
• Openness: an MCP server, an agent REST API, and agent embedding in JWT-signed chat elements.
• Accuracy: Sigma reports 86% on an internal dashboard-building test, not on question answering. See Sigma vs ThoughtSpot.

Looker: best for teams with a mature LookML model

Best for: Google Cloud customers whose metrics already live in LookML. Not ideal for: anomaly detection or forecasting, which Looker’s Python analysis doesn’t support yet.

• Pricing: quote only. Conversational Analytics has no usage billing through January 31, 2027, then costs $3.00 per million input tokens and $20.00 per million output tokens beyond each user’s included allotment. 90-day trial instances. Verified November 2026.
• Agent: data agents pick LookML fields instead of writing raw SQL, across up to five Explores, with results capped at 50,000 rows. Agentic workflows (preview) add alerts, key driver analysis, and Slack or email delivery.
• Governance: LookML access grants and user attributes; SAML or OIDC; SCIM in preview.
• Openness: a built-in MCP server that can create dashboards, on Looker-hosted instances only.

Tableau: best for Salesforce-centered organizations

Best for: companies already on Tableau Cloud or Salesforce Data 360. Not ideal for: teams that want a documented multi-step root-cause agent or monthly billing.

• Pricing: Standard from $15, Enterprise from $35, and Tableau Next from $40 per user per month, billed annually. Tableau Agent in Tableau Cloud needs Cloud+ or Tableau+, which have no public price. The 14-day Tableau Cloud trial includes Tableau Agent and Pulse. Verified November 2026.
• Agent: in Tableau Next, Tableau Agent monitors data in the background and posts prioritized insights to Slack or Salesforce. Pulse explains what is driving a metric change and sends digests by email, Slack, or Teams.
• Governance: Pulse respects row-level security; Tableau Next uses Data 360 security; SAML, OIDC, and SCIM.
• Openness: a managed Tableau MCP server and an embeddable agent component.

Power BI: best for Microsoft shops on Fabric capacity

Best for: organizations already paying for Fabric F2 or Premium capacity. Not ideal for: Pro-only tenants, or customer-facing embedded apps.

• Pricing: Pro is $14 and Premium Per User $24 per user per month, but Copilot needs F2 or higher Fabric capacity or P1; Pro or PPU alone isn’t enough, and usage is billed in capacity units. The 60-day Fabric trial excludes Copilot and data agents. Verified November 2026.
• Agent: Copilot answers against semantic models as of their last refresh, using a multistep approach with Fabric IQ. Fabric data agents translate questions to SQL, DAX, or KQL but are read-only; monitoring comes from rule-based Activator, not the agent.
• Governance: RLS, column-level, and object-level security apply; sign-in goes through Microsoft Entra ID.
• Openness: a published data agent becomes an MCP server. Copilot isn’t available for app-owns-data embedding.

Which AI data agent should you choose?

• You want an agent that reports without being asked: Basedash Insights, ThoughtSpot KPI monitors, Omni condition routines, or Tableau Next proactive insights.
• You need answers to “why did this change”: ThoughtSpot Spotter, Databricks Agent mode, Snowflake Deep Research, or Omni Agent.
• The agent should act in other systems: Databricks, Snowflake, Basedash, and Sigma connect to Slack, Jira, Salesforce, or Linear. ThoughtSpot and Basedash can require approval before writes.
• Fine-grained access controls are mandatory: ThoughtSpot, Sigma, Snowflake, and Databricks enforce row and column rules per user; Basedash enforces row-level security on Postgres only.
• You want to use the agent from Claude, ChatGPT, or Cursor: every tool here has an MCP server, but Basedash includes it on every plan, while Hex limits it to Team and up and ThoughtSpot sells it as an add-on.
• Budget is tight: if you already pay for Databricks or Looker, their agents bill no AI usage until January 31, 2027; otherwise Hex Professional starts at $36 per editor.
• A Series B company needing real-time dashboards plus an agent: shortlist Basedash, Omni, and ThoughtSpot, then test each on your own warehouse.

For chat-first tools, see our comparison of conversational analytics in BI tools. For how each vendor’s AI handles your data, read how BI tools’ AI assistants handle your data.

Frequently asked questions

What is the best AI agent for data analysis?

It depends on where your data lives. Databricks Genie and Snowflake CoWork fit teams whose data already sits in those platforms and whose governance policies are defined there. ThoughtSpot Spotter and Omni suit enterprises with a governed semantic model. Basedash fits teams that want an AI data analyst on Postgres, MySQL, or a warehouse with automations and an insights feed, starting at $1,000 per month. Hex suits analysts who want to review generated SQL and Python in a notebook. Test two or three on your own questions before buying.

Which BI tools have AI data agents built in?

As of November 2026, ThoughtSpot (Spotter 3 and three companion agents), Databricks (Genie One and Genie Agents), Snowflake (CoWork), Omni (Omni Agent), Basedash, Hex (Threads and the Notebook Agent), Sigma (Sigma agents), Looker (Conversational Analytics data agents), Tableau (Tableau Agent and Tableau Next), and Power BI (Copilot and Fabric data agents) all ship agents. They differ in whether the agent can run on a schedule, take actions in other apps, and enforce row-level security for each user.

Hex vs ThoughtSpot for agentic analytics: which fits better?

Hex fits data teams that want an agent writing SQL and Python cells they can inspect and edit, with Threads for business users and Tasks for scheduled runs. Its SSO is OIDC only, with no SAML. ThoughtSpot fits governed, search-style analytics for many business users: Spotter runs root-cause analysis, KPI monitors alert on anomalies, and row and column security apply to every agent. Hex publishes prices from $36 per editor; ThoughtSpot’s agent tier starts at $50 per user per month.

Sigma or ThoughtSpot for AI agents and automating business workflows?

Sigma is the stronger pick when the workflow writes data: its agents can insert rows into input tables, run on a schedule, and notify Slack, Teams, or email, with agent messages at 0.1 credit each. ThoughtSpot is stronger for monitoring metrics: KPI monitors detect anomalies and fire webhooks into other tools, and writes to external apps wait for user approval. Sigma’s pricing is quote only, while ThoughtSpot Pro is $50 per user per month.

What are the best alternatives to Snowflake Cortex agents?

If you want to stay inside a warehouse platform, Databricks Genie is the closest match, with a free usage period for users until January 31, 2027. If you want a BI layer on top of Snowflake, Omni, Sigma, ThoughtSpot, and Basedash all query Snowflake live, and each adds dashboards and scheduled delivery that CoWork lacks. Sigma can even call Cortex as a warehouse agent. Choose Snowflake CoWork itself if per-token pricing without seat fees matters most.

Which AI agent can read dashboards, send Slack alerts, and take actions, and what does it cost?

Basedash automations post AI analyses to Slack on a schedule or when data changes and can call tools through MCP connectors, from $1,000 per month for 25 users. Omni routines check a condition and post to Slack or a webhook, but pricing is quote only. ThoughtSpot sends KPI anomaly alerts and fires webhooks on the $50-per-user Pro plan. Sigma agents notify Slack and write to input tables, at 0.1 credit per message on top of a quoted license.

Do AI data agents respect row-level security?

The ones built on governed platforms do. ThoughtSpot applies row-level and column-level security to every agent. Databricks enforces Unity Catalog row filters and column masks per user, and Snowflake CoWork inherits row access policies. Sigma and Power BI carry row security over to their agents. Basedash enforces row-level security on Postgres and Supabase, including in Slack. Check how scheduled agents run, too: Basedash Insights use an admin’s access, and Sigma skips approval prompts on scheduled runs.