AI-powered agentic analytics restores business leaders’ data trust

Business leaders are facing a growing paradox in data-driven decision-making: as data volumes increase, confidence in using that data is plummeting. This disconnect threatens effective leadership in uncertain times, but a new approach called “agentic analytics” promises to bridge this gap by pairing business users with AI agents that can automate data tasks, proactively identify patterns, and deliver insights in accessible language within existing workflows.

The big picture: Business decision-makers are drowning in data while simultaneously losing faith in their ability to use it effectively, with leader confidence in data-driven decisions dropping 18% since 2023 to less than half overall.

• A Salesforce survey reveals 76% of business leaders feel intense pressure to support their arguments with data, yet many lack the necessary analytical support or training.
• This widening gap between data availability and data usability is paralyzing decision-making precisely when agility is most needed.

Why this matters: Agentic analytics represents the next evolution of business intelligence, democratizing data by enabling AI agents to handle complex analytical tasks for users regardless of their technical expertise.

• Traditional dashboards require users to know what questions to ask—a capability one-third of business leaders admit they struggle with.
• By automating repetitive tasks like data preparation and proactively surfacing insights, these systems eliminate barriers that have traditionally limited data utilization.

What they’re saying: “Most executives don’t have their own data analysts on call,” explains Southard Jones, chief product officer of Tableau. “They also don’t have the training they need to be really confident that they and their team are using the right data to help make the right decisions, especially as these decisions become more involved and more complex.”

Key innovations: Solutions like Tableau Next are designed to rebuild trust between business leaders and their data by fundamentally changing how they interact with analytics.

• AI agents can identify patterns and anomalies without being explicitly prompted, delivering those insights in natural language within users’ daily workflows.
• The technology eliminates friction associated with traditional dashboard interactions, providing not just data visualization but actionable recommendations.

The bottom line: As organizations struggle with the growing disconnect between data abundance and decision confidence, agentic analytics offers a promising path forward by making sophisticated data analysis accessible to everyone, not just technical specialists.