Traditionally, business users must queue up requests with data science teams for insights, causing delays. AI changes this by enabling non-technical users to query enterprise data directly using natural language, receiving answers in seconds and empowering faster, data-driven decisions.

Block's AI agent, Goose, has an accessible UI that allows non-technical employees in roles like sales and finance to build their own software dashboards and tools. This democratizes software creation within the enterprise, turning domain experts into citizen developers.

AI agents are not just chatbots; they are powerful orchestrators that connect to various underlying tools (e.g., portfolio analyzers, databases). This allows non-technical users to perform complex data analysis and execute subsequent actions using simple natural language commands.

With AI tools that allow natural language querying of business data, designers no longer need SQL to understand user behavior. This democratized access empowers them to contribute to strategy and become holistic product thinkers, not just visual executors.

AI-powered platforms transform how leaders consume insights. Instead of passively receiving periodic reports from a central analyst, leaders are empowered to pull real-time information on demand for immediate needs. This enables more timely decision-making without creating an analytical bottleneck.

The most advanced analytics workflow moves beyond manual dashboards to scheduled AI agents. These agents analyze data, synthesize top insights and deviations, and automatically push a report into the team's Slack channel. This frees PMs from routine reporting to focus on strategic action.

Traditional dashboards are obsolete because they create more questions than answers. The future is interactive, conversational AI that allows leaders to ask 'why' and get immediate answers and recommendations, eliminating follow-up meetings and Slack messages.

AI assistants will deliver proactive, conversational insights, freeing CX teams from reactive dashboard analysis. Instead of monitoring static reports, leaders will simply ask their AI what to focus on, rendering traditional dashboards obsolete and enabling a more strategic, real-time approach to customer experience management.

Traditional automated dashboards are often ignored. AI-driven reporting is superior because it doesn't just present data; it actively analyzes it. The AI summarizes trends, generates relevant follow-up questions, and even attempts to answer them, ensuring that insights are never missed, even when stakeholders are busy.