How AI Agents Are Rewriting Enterprise Analytics

Most companies are not short on data. They are short on the time, cost, and coordination required to turn it into action.

Ethan Ding, co founder and CEO of TextQL, joins The Tech Trek to explain how AI agents are changing enterprise analytics. The conversation moves beyond faster dashboards into a larger shift, analysts managing fleets of agents, business teams asking far more questions, and companies finding revenue and cost opportunities that were previously too expensive to pursue.

What Technical Teams Can Take From This

• Making answers cheaper does not reduce analytics work. It increases the number of questions people ask.

• Analysts may spend less time assembling dashboards and more time managing agents, data sources, permissions, quality, and costs.

• The clearest ROI comes from decisions with direct financial outcomes, including fraud prevention, upsell opportunities, churn risk, and unused vendor spend.

• Faster analysis matters most when teams can act on valuable opportunities they previously could not afford to investigate.

• Token costs will force AI companies and buyers to reconsider where software budgets go, especially across BI tools and data platforms.

Moments Worth Hearing

00:00 Ethan explains how TextQL agents work across messy enterprise systems including Cognos, Teradata, Snowflake, Databricks, Tableau, and Power BI.

04:52 Why giving people faster answers does not create free time. It creates even more demand for analytics

07:10 How self service analytics quickly moves from asking what a number is to asking whether it matters and what to do next.

10:08 The analyst role shifts toward managing fleets of agents and tuning an insight factory for the business.

14:38 Why faster access to data can reveal valuable opportunities that were previously too expensive to investigate.

19:55 A practical way to measure analytics ROI through fraud prevention, upsell opportunities, and other direct financial outcomes.

24:18 How token costs, AI margins, and easier migrations could reshape spending on traditional BI tools.

One Line That Stuck

“It becomes much more of an operations manager job. It is a factory. It takes in tokens and churns out dashboards, reports, and recommendations.”

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