If you are a data and analytics leader, then you know agentic AI is fuelling unprecedented speed of change right now. Knowing you need to do something and knowing what to do, however, are two different things. The good news is providers like ThoughtSpot are able to assist, with the company in its own words determined to ‘reimagin[e] analytics and BI from the ground up’.
“Certainly, agentic systems really are shifting us into very new territory,” explains Jane Smith, field chief data and AI officer at ThoughtSpot. “They’re shifting us away from passive reporting to much more active decision making.
“Traditional BI waits for you to find an insight,” adds Jane. “Agentic systems are proactively monitoring data from multiple sources 24/7; they’re diagnosing why changes happened; they’re triggering the next action automatically.
“We’re getting much more action-oriented.”
Alongside moving from passive to active, there are two other ways in which Jane sees this change taking place in BI. There is a shift towards the ‘true democratisation of data’ on one hand, but on the other is the ‘resurgence of focus’ on the semantic layer. “You cannot have an agent taking action in the way I just described when it doesn’t strictly understand business context,” says Jane. “A strong semantic layer is really the only way to make sense… of the chaos of AI.”
ThoughtSpot has a fleet of agents to take action and move the needle for customers. In December, the company launched four new BI agents, with the idea that they work as a team to deliver modern analytics.
Spotter 3, the latest iteration of an agent first debuted towards the end of 2024, is the star. It is conversant with applications like Slack and Salesforce, and can not only answer questions, but assess the quality of its answer and keep trying until it gets the right result.
“It leverages the [Model Context] protocol, so you can ask your questions to your organisation’s structured data – everything in your rows, your columns, your tables – but also incorporate your unstructured data,” says Jane. “So, you can get really context-rich answers to questions, all through our agent, or if you wish, through your own LLM.”
With this power, however, comes responsibility. As ThoughtSpot’s recent eBook exploring data and AI trends for 2026 notes, the C-suite needs to work out how to design systems so every decision – be it human or AI – can be explained, improved, and trusted.
ThoughtSpot calls this emerging architecture ‘decision intelligence’ (DI). “What we’ll see a lot of, I think, will be decision supply chains,” explains Jane. “Instead of a one-off insight, I think what we’re going to see is decisions… flow through repeatable stages, data analysis, simulation, action, feedback, and these are all interactions between humans and machines that will be logged in what we can think of as a decision system of record.”
What would this look like in…
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