The modern BI experience is shifting from building dense dashboards to asking questions in plain English: “What changed in user retention last week?”
or “Which product line is underperforming and why?” Tools like ChatGPT, Gemini, and enterprise AI agents now sit on top of data warehouses, offering contextual insights instantly.
If conversational analytics becomes the new norm, do traditional dashboards and static reports become obsolete—or do they still serve a crucial role?
Avatar The rise of conversational analytics is changing how people interact with data. Instead of navigating layers of dashboards, stakeholders can now ask a question in plain English and get a contextual, almost analyst-level explanation in seconds. It removes friction, reduces dependency on data teams, and makes insights accessible to anyone—whether they’re in product, marketing, or operations. For day-to-day decision-making, this speed and simplicity feels like a game-changer.
But that doesn’t mean dashboards are disappearing. They still play a crucial role as a shared source of truth, especially for tracking core KPIs, aligning teams, and maintaining governance. Conversational tools are incredible for exploration and quick answers, but dashboards provide structure, consistency, and long-term visibility. The future isn’t one replacing the other—it’s both working together: conversational insights for agility, dashboards for stability.
The modern BI experience is undergoing a fundamental shift. For years, organizations relied on dense dashboards and static reports to understand their business, but tools like ChatGPT, Gemini, and enterprise AI agents are changing the way teams interact with data. Instead of navigating filters or drilling through endless visualizations, people can now ask plain-English questions like “What changed in user retention last week?” or “Which product line is underperforming and why?” and receive contextual, narrative insights instantly. But this doesn’t mean dashboards are dying. In reality, dashboards and conversational BI serve different but equally important roles. Dashboards excel at monitoring the health of the business—they provide a stable, governed, trustworthy layer where KPIs are defined consistently, audited, and validated. They’re the “source of truth” for recurring metrics. Conversational analytics, on the other hand, excels at reasoning and exploration. It answers questions dashboards never anticipated, explains why metrics moved, identifies hidden patterns, and supports ad-hoc decision-making on the fly.
