How to write better AI prompts for tax research

GenAI research assistants are changing how tax and accounting professionals investigate complex questions. Harnessing these tools effectively all begins with the way prompts are written.

Delivering precise and actionable results is no longer about luck—it's about the quality and clarity of a prompt. Many professionals encounter challenges like unclear responses or too many follow-up requests, causing frustration and wasted time. By defining a more intentional approach to prompting, those obstacles can be transformed into advantages.

The real issue often lies not with the artificial intelligence itself, but with ambiguous or incomplete prompts. When hundreds of technical or factual variables may influence a tax scenario or accounting rule, it's critical to communicate the full context. This is where a structured prompting framework makes a measurable difference.

The CREATE strategy provides a step-by-step guide to making each query sharper, faster, and more productive. Used well, it shapes the effectiveness of every interaction with an AI assistant.

Unlocking Research Efficiency

Smart prompting can turn a GenAI assistant from a generic search tool into a true research partner. For professionals working in tax and accounting, efficiency is everything. The right prompt can mean the difference between spending minutes or hours searching for answers, especially when accuracy is non-negotiable.

A single well-structured prompt reduces the need for back-and-forth, minimizing delays and confusion. Not only does this approach save time, but it also leads to more targeted, relevant results. Structured prompts enhance workflow by:

• Eliminating unnecessary clarifications
• Focusing the AI assistant on exactly what needs to be researched
• Giving the professional more control over the tone, detail, and scope of the output

Understanding the CREATE Strategy

The CREATE strategy maintains clarity throughout every query. CREATE stands for:

• Character: Identify who or what is involved in the research scenario, such as the type of business or situation under review.
• Request: Clearly describe the specific information or outcome needed.
• Examples: Offer real or hypothetical references to illustrate the scope and tone desired.
• Adjustments: Specify unique factors such as jurisdiction, date range, or regulatory context.
• Type of output: Define the delivery format—list, summary, or detailed analysis.
• Extras: Include additional details or keywords relevant to the research.

Each element plays a critical role, transforming broad questions into actionable research requests for the AI assistant.

Applying CREATE to Strengthen Tax and Accounting Research

By applying CREATE, every prompt becomes a blueprint for precise answers. Consider how structuring a query with CREATE leads to better outcomes:

Character sets the stage. Is the focus on a tech company merging or a retail shop adjusting strategy? Request puts the goal front and center—such as uncovering tax consequences or formulating a business plan.

When examples are included, the AI assistant can match the level of detail or mirror industry-appropriate language. If the question requires specificity—perhaps concerning capital gains rules in California—adjustments ensure the right factors are applied. Choosing the type of output (whether that's a strategic summary or in-depth analysis) signals the desired level of complexity. Last, extras such as references to recent case law or industry benchmarks round out the picture.

This method always:

• Saves time by clarifying the research scope from the start
• Improves accuracy by anchoring the assistant in a specific context
• Supports better business decisions by producing relevant, actionable information

CREATE in Action for Tax Professionals

Two scenarios demonstrate CREATE in practice for busy professionals:

Scenario 1:A professional needs to determine tax implications of a merger in the tech sector, focused on California and capital gains. By specifying context, location, examples, and extra data like case law, the prompt becomes: "Seeking the tax implications of a company merger in the tech industry, with a focus on California capital gains tax, including any relevant case law."

Scenario 2:An accountant prepping for a client consult wants actionable strategic advice for a small retail business. By using CREATE, the prompt includes context (retail), the goal (business strategy improvement), relevant examples (industry trends), necessary adjustments (performance data), requested output (strategic plan), and extras (benchmarks, best practices). The result: "Need advice on improving business strategy for a small retail business, considering recent performance and market trends, and focused on creating a strategic plan with industry benchmarks and best practices."

These structured prompts direct the AI assistant efficiently for tax research and client consultation, reducing ambiguity and maximizing relevance.

Advancing Your Practice with CREATE

The CREATE strategy offers a proven path to more productive research and stronger outcomes in tax and accounting. By carefully considering each component—character, request, examples, adjustments, type of output, and extras—queries become clear roadmaps for AI assistants to follow. This approach not only streamlines daily workflows but also supports greater confidence in research findings, helping professionals stay ahead as the demands of the industry evolve.

A smarter prompt is often the difference between guesswork and insight. With a structured strategy like CREATE, unlocking the full potential of an AI research partner becomes a powerful advantage.