How to choose an AI implementation partner for a mid-size CPA firm

Three kinds of provider implement AI for a mid-size CPA firm: software you already run, such as Karbon, CCH Axcess, and Intuit; large consultancies and national firms’ advisory arms; and specialist implementers across tax software, practice management, books, and email.

Choose on whether work crosses systems, how client data stays separate, how §7216 consent is handled, who reviews output, and who runs the system after launch.

Who implements AI for a mid-size CPA firm?

Compare the route, not a ranked list. A firm can also build internally.

• Software you run. Fits when the work stays inside one product. Each product sees only its own data, so check what that plan retains.
• Large consultancies. Fit a firm-wide program when the budget matches. Confirm the team and the price fit a firm your size.
• Specialist implementers. Fit when work crosses tax software, practice management, books, and email. Watch maintenance, security, and how review is built in.
• Internal build. Fits if engineers will own it. Upkeep stays with you. See build, buy, or have it built.

The CPA firms page describes what those products cover inside their own walls, with vendor facts checked in September 2026. Turn that AI on before you hire anyone.

What to look for in an AI implementation partner

Use one live workflow, not a demo on someone else’s files. Where to start is the filter: repeated work, written rules, and a person who can say the result is right.

1. One bottleneck. Pick a slice, such as individual returns with a Schedule C, and measure chasing, re-keying, files complete at first review, and days to review. No savings figure before your baseline.
2. Your versions. Desktop packages often rely on exports. Lacerte publishes an SDK. Ask which path fits the version you run. Nothing is written back without staff review.
3. Separate clients. A draft for one client must not draw on another’s return. Ask whether that wall is in the database. See data isolation.
4. §7216 and model terms.
   • Look for a check that the written consent your firm requires is on file before AI processes that return, with processing kept in the United States.
   • The IRS has not said whether an AI tool counts as a third party. For individual returns, a separate consent is the cautious approach. Confirm the wording with counsel.
   • Put zero-retention, no-training terms in writing. See zero data retention.
5. Review, test, and exit. Name reviewers other than the preparer, test on your files, and agree who runs it, what you can export, and what happens to keys. Compare providers with how we protect client data.

How engagements usually work

• Strategy only. You get a plan. Your team builds it, or you configure software. AI strategy is this start when the workflow is still undecided.
• Build, then handoff. A partner builds a defined workflow and your team maintains it. Settle who owns it when a tax-software version changes.
• Build and run. The partner operates and improves the system. Your people still review and approve. Managed AI is this model.

Precision AI OS is the third model. The work follows how we work: Discover, Build, Launch, then Run and grow.

How long does it take?

The CPA firms page uses an illustrative 90-day sequence. It is not a calendar promise, and this guide adds no week counts.

1. Discover and define. Map one workflow, check permissions, and agree what a useful result looks like.
2. Build and test. Connect approved inputs and test drafts on representative examples with your reviewers.
3. Run and improve. Introduce the workflow, monitor exceptions, and compare results with the baseline before you widen scope.

Tax-package access, signed consent for the pilot clients, and reviewer time are the usual reasons the sequence moves.

What stays with your team, and what’s out of scope

Tax judgments, signatures, filings, and client communications stay with your team. So do software choices and billing decisions.

The IRS Office of Professional Responsibility says billing for manual time that was not spent, or double billing for AI-assisted work, may violate Circular 230 §10.27, and that efficiencies should be reflected fairly in billing. That point is on the CPA firms page. This guide is not tax advice.

A partner can prepare the chase and the file. The preparer and the reviewer still decide.

Questions to ask before you sign

1. Systems. What is read, what is written, and how is that confirmed for our versions?
2. Consent. How is processing held until §7216 consent is recorded?
3. Approval. Who approves each output, and where is that recorded?
4. After launch. Who runs it, what does it cost, and can we export data and keys first?
5. Audits. What is complete? If none, which controls are you designed against?

The longer list is 12 questions for an AI vendor.

Where Precision AI OS fits

Precision is a specialist implementer, so read this with that in mind. We work with professional service firms of 10 to 500 people. We build a data pipeline and a private firm OS, then bounded AI agents for jobs such as document collection and review-ready files. By default, your staff approve anything that reaches a client.

Our most complete build so far is in tax. We built an end-to-end tax automation operation for a high-volume solo tax preparer, with under 5 minutes of human-in-the-loop time per return.

Each firm’s data is isolated in the database and encrypted with keys unique to it, and every approval is recorded. See how we protect client data.

Where we’re not the right fit

• Already covered. Your software’s AI already does the job. Use it first.
• You will own the build. See build, buy, or have it built.
• Self-serve. You want a tool your team configures. We build, run, and maintain the system.
• A finished audit today. Our controls are designed against SOC 1 and SOC 2 criteria, but we haven’t completed an audit yet. The security page says that plainly.

Book a discovery call to test one workflow against your own files.

Guides for other firms

The same decision is covered for an independent insurance agency and a mid-size law firm.

Steven de la Fe, CPA, is a co-founder of Precision AI OS. He has 20 years of tax and accounting experience and has helped build Taxfyle for the past ten years.