AI platforms like Altruist's 'Hazel' automate laborious, high-value work like complex tax planning. This reduces the unit cost of a sophisticated analysis from thousands of dollars to just a few, making high-end financial advice accessible to a much broader market, not just the wealthy.

Go beyond static content like articles and presentations. Use AI to build an interactive product that encapsulates your expert judgment and decision-making framework. This allows clients or colleagues to work through problems using your model, effectively scaling your most valuable expertise and freeing up your time.

Go beyond using AI for simple tasks. Founder Kat Getzey fed Claude her company's entire revenue and expense data and asked it a complex strategic question: "How much can I afford to spend on personnel next year?" This demonstrates AI's power for high-level, data-driven decision-making.

The primary benefit of using AI for revenue planning isn't just build speed. It's the ability to regenerate a complex, multi-tab model with thousands of formulas in minutes in response to feedback or methodology changes—a task that would previously take days of manual work.

Move beyond simple research and use AI to create complex, interconnected business artifacts like a 20-part security policy architecture or multi-tab financial models. This advanced application can reduce multi-day tasks to minutes, dramatically boosting productivity for core business functions.

For data-heavy queries like financial projections, AI responses should transcend static text. The ideal output is an interactive visualization, such as a chart or graph, that the user can directly manipulate. This empowers them to explore scenarios and gain a deeper understanding of the data.

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.

Instead of presenting a fixed plan, use AI to build proposals where clients can adjust variables like scope, resources, and timelines. This transforms the proposal from a static document into a shared decision-making tool, allowing clients to explore trade-offs themselves and radically reducing the back-and-forth latency of negotiations.

Wilkinson’s CFO, with no prior coding experience, used AI tools to build a sophisticated, customized portfolio management dashboard. This replaced Adapar, a service costing up to $100k annually, demonstrating how AI empowers non-engineers to build complex internal tools and disrupt expensive enterprise software.