Artificial intelligence is reshaping tax research faster than most practitioners expected. What once required hours of reading cases, rulings, and commentary can now begin with a single prompt. For small tax firms, the promise is real: faster answers, lower research costs, and more time for the client-facing work that actually grows a practice. But not all tools are created equal, and none of them eliminate the need for professional judgment.
Here is a practical look at the leading options and how they stack up for smaller firms.
Blue J (with Tax Notes)
Blue J stands out for its predictive AI models and structured legal analysis. Its partnership with Tax Notes adds a strong layer of authoritative content, and it performs particularly well in areas like reasonable compensation, worker classification, and tax law interpretation. Outputs are structured and typically cite relevant authorities, making answers defensible. The tradeoff is cost. Blue J sits at a premium price point, which makes it a stronger fit for mid-sized firms or specialists who regularly tackle complex, judgment-heavy research and need reliable support for the positions they take.
Thomson Reuters Checkpoint Edge
For firms already using Checkpoint, the AI features built into Checkpoint Edge offer a logical next step. The platform draws on a massive, trusted tax library, and its AI tools help users summarize, search, and analyze within that existing content. Accuracy is high precisely because the AI stays grounded in proprietary source material rather than generating open-ended answers. It is a conservative, reliable option for firms that want efficiency gains without overhauling their workflow.
Bloomberg Tax
Bloomberg Tax combines strong editorial content with primary source integration. Its AI tools lean toward summarization and navigation rather than fully generative responses, which keeps accuracy high but limits flexibility. For firms that prioritize editorial depth and curated insight over cutting-edge AI functionality, Bloomberg remains a solid choice, though pricing is comparable to Checkpoint.
General AI Tools (ChatGPT and Similar)
Lower-cost general AI tools have a legitimate place in a small firm's workflow, but only as a supplement. These tools are fast, flexible, and affordable, often under fifty dollars per month. They can help draft client memos, explain concepts in plain language, and support early-stage brainstorming. The risk is accuracy. Without access to proprietary tax databases, general AI tools can produce convincing but incorrect answers, miss critical nuance, or work from outdated interpretations. They should never serve as a primary research platform.
Newer Purpose-Built Tools
A growing category of AI tools built specifically for tax questions, including various conversational Q&A platforms with citation features, offers a middle path. Pricing tends to be more accessible than legacy platforms, and some show genuine promise. Accuracy is improving but remains inconsistent depending on the data sources and model maturity behind the tool. Cost-conscious firms willing to test and verify have options here, but a careful eye is required.
A Critical Caution: Client Data and Security
Before any firm puts an AI tool to work, there is a question that needs a clear answer: what happens to the information entered into the platform? For tax practitioners, this is not a minor technical detail. It is a professional obligation.
The short answer is that client-specific information, names, Social Security numbers, financial figures, business details, or anything that could identify a taxpayer, should not be entered into any AI tool unless the firm has confirmed that the platform meets appropriate data security and privacy standards. Most general AI tools, including the consumer versions of ChatGPT and similar products, use conversation data to train or improve their models by default. Entering client information into those environments is not just a privacy risk; it may constitute a violation of a practitioner's confidentiality obligations under IRC Section 7216 and applicable state rules.
Enterprise or professional versions of these tools often include data privacy agreements and opt-out protections that consumer tiers do not. Thomson Reuters, Bloomberg, and Blue J, as established legal and tax platforms, are built with professional data handling standards in mind, but firms should still review the terms of service and confirm how data is stored, used, and protected before uploading any client-specific details.
The safest approach for any AI research workflow is to keep queries hypothetical. Frame questions around fact patterns rather than real client data. A prompt like "how is a shareholder loan treated when a closely held C corporation..." accomplishes the same research goal as entering the client's name and financials, without any of the exposure. If a tool's value depends on uploading actual client documents, that tool warrants a thorough security review, including a look at whether a Business Associate Agreement or data processing addendum is available and appropriate.
Firms should also consider updating their Written Information Security Plan, commonly known as a WISP, to address AI tool usage specifically. The IRS requires tax preparers to maintain a WISP, and documenting which AI tools are approved for firm use, under what conditions, and with what data restrictions is both a compliance best practice and a liability protection measure.
The Bottom Line
The most important thing to understand about AI-powered tax research is that it is a starting point, not a final answer. The best tools can cut research time dramatically, help junior staff ramp up faster, and bring more consistency to early-stage analysis. What they cannot do is replace a review of primary sources, the application of professional judgment, or proper documentation of the positions a firm takes.
For small practitioners, the smartest approach is hybrid. Use AI to move faster, but anchor conclusions in trusted sources, keep client data out of unvetted platforms, and make sure your firm's security policies reflect how these tools are actually being used. The firms that strike that balance will capture the real efficiency gains without taking on unnecessary risk.
Dr. Christine Gervais is a licensed CPA, using her skills to help businesses grow and achieve their fullest potential. Christine has a Master’s degree in accounting from Southern New Hampshire University in addition to holding her CPA license for over a decade. Notably, Christine is a nationally recognized speaker providing education to other CPAs on how to best serve clients as well as instruction on a wide variety of topics for business owners on how to maximize success. Christine prides herself on the value she can bring to clients with her extensive tax knowledge and provides strategic, forward-thinking financial strategies to help clients grow. When not behind her desk, you can find Christine spending quality time with her daughter and stepson or tending to the family’s excessively loved farm animals.
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