The number of tax practitioners using AI for research has nearly doubled in just a year, which is increasingly leading them to explore alternative billing models.
This is according to data from AI tax research platform
"For years, AI in tax research was treated as something to watch, test or cautiously pilot," said Benjamin Alarie, founder and CEO of Blue J in the report's intro. "That period is ending. The findings in this report show a profession moving from curiosity to reliance. Firms are no longer asking whether AI-powered tax research belongs in the practice of tax. They are asking how to build around it, govern it, train with it, and use it to deliver better advice."

However, while tax practitioners are adopting AI solutions, only a minority are using ones specialized for tax research; in contrast, the overwhelming majority use general AI platforms. The poll found that 90% are using public models like ChatGPT, Gemini, Perplexity or Claude. Following this are the 67% who use traditional legacy tools with tax research capacities, such as Thomson Reuters Checkpoint or CoCounsel, Bloomberg BNA, or Wolters Kluwer CCH Answer Connect. Below that are the 64% who use search engines. And, finally, at 46%, are those who use tax-specialized AI tools.
Of these, 25% have access to TaxGPT, 22% have access to Blue J, and 17% have access to Accordance.
Dave Ragones, head of product for tax, audit and accounting professionals at Thomson Reuters, felt this reflected a lack of distinction in the overall market between general AI tools and professional-grade ones, both of which are often spoken of under the broad umbrella of just "AI."
"As AI adoption in tax accelerates, it's critical for firms to remember that not all AI is used in the same way, and it cannot be held to a single standard. This is especially true in industries with professional liability, where AI must meet a higher bar than general productivity tools. Where outputs shape legal judgments, financial disclosures, regulatory filings, or client advice, 'almost right' falls short. Thomson Reuters defines this higher bar as Fiduciary Grade AI – the standard for how AI should perform in high-stakes professions, and the standard we build to. As AI moves deeper into regulated work, the defining question is no longer whether a system can generate an answer, but whether professionals can verify it, and stand behind it," he said in an email.
The primary reason people use AI for tax research is that it saves time, cited by 84% of respondents (tied with those saying it simplifies complex tax rules, which presumably also saves time.) As for what they're doing with the time they save, 50% said they were improving client response and project delivery timelines, 47% said they're improving work-life balance, and 46% saying they're delivering higher quality advice to clients.
Exactly how these clients will pay practitioners was another aspect of the poll. As AI is said to save time, completing tasks in minutes that once took hours, the concept of the billable hour has become less relevant. As a result, 69% of AI adopters are considering alternatives such as value-based, hybrid and fixed fee billing.
Breaking down the specifics, 37% said they are considering a move to value-based billing, 30% are considering adopting a hybrid billing model and 2% are considering fixed-fee billing. And even if a practitioner were to keep the billable hour model, many still plan to change their approach as 28% said they plan to maintain hourly billing but increase realization. Only 3% said they were not considering any changes at all.
"In a lot of ways, this shift is acknowledging something that's always been true in the profession," said Brandon Allfrey, senior director of tax transformation at CPA.com in the report. "Clients aren't paying for the time it takes to do something right now, they're paying for the sum of experiences over your career. That said, changing billing to reflect that is still a massive change management challenge. Hourly billing is just so entrenched in the profession. Finding a new billing model that works for your firm and then actually implementing that model is very difficult."
Conducted between March 12-23, 2026, the quantitative survey behind the report leveraged responses from 1,000 U.S. accountants working at tax and accounting firms of all sizes. Only respondents who report doing tax research at least a few times a year were included in the sample.







