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Are Your Analytics
Actually Agentic?

10 Ways to Spot the Difference

If you ask three people to define agentic analytics, you’ll probably get three different answers.

But here’s what we know: Gartner® predicts that by 2027, 75% of new analytics content will be contextualized for intelligent applications through GenAI, enabling a seamless connection between insights and action. In other words: agentic analytics.

With so much agent washing and uncertainty about what real agentic analytics looks like, we created this definitive guide to help you cut through the noise and find the fastest path to value.

Backed by industry research and practical examples, this resource will help your team develop a shared language, set success benchmarks, and build a strategic action plan for your organization.

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Ehsan Hoque
Director of Product Management

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1745596328-photo-plain-brian-reynolds

Brian Reynolds
Global Head of Embedded, Go To Market

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ThoughtSpot Agentic Analytics Platform

Analyst Studio

Data Mashups, Data Science,
Python Notebooks, Ad Hoc SQL Analysis

Semantic Model

Trusted & Secure Metrics Layer, Agent-ready
Metadata, Data Security

Data Management

Real time, Zero Copy or In-Memory,
Unified Metadata and Compliance

AI Agents

Spotter - Agentic AI Analyst,
Deep Research, Agent as a Service

AI-Augmented Dashboards

AI-first, Mobile-ready, Automated Insights,
Connected Where You Work

Smart Apps

Embedded Analytics for your customers, Insights to
Actions, APIs and SDKs, Workflow Automation

Smart Apps

Automated
Insights

Data Hub

AI Agents

AI Augmented
Dashboards

Smart Apps

 

The most successful companies use ThoughtSpot