AI governance & readiness
Governance sounds like paperwork. In practice it's the difference between knowing what your people are doing with client information and finding out later.
AI governance for a professional-services firm means three concrete things: knowing where AI is actually being used inside the firm, having a written policy that tells staff what tools are approved and what data may be entered into them, and having a verification step before AI-assisted work reaches a client or a filing. The obligations behind all three already exist — the rules of professional conduct that govern competence, confidentiality, and supervision apply to AI use whether or not a firm has written anything down. Tienta closes that gap in two phases: a bounded audit that documents real use and produces a firm-specific policy, then ongoing implementation of the tools that make the practice faster.
Free, capable AI tools meeting billable-hour time pressure produce the same result in every firm we walk into: people are already using them, and nobody has written down what's allowed. That isn't a discipline problem. It's what happens when a useful tool arrives faster than the policy governing it.
The professional obligations don't wait for the policy, though. Duties of competence, confidentiality, and supervision of staff apply to AI-assisted work the same way they apply to everything else — and when something goes wrong, the difference between an isolated mistake and a systemic supervision failure is usually whether anything was written down beforehand.
Not the sanctioned tools — the actual ones. Surfacing unapproved use is the whole point, and it's the part a firm cannot do by asking in a staff meeting.
The rule that prevents the most damage per sentence written. Public tools can retain and train on what's typed into them; staff generally don't know which tools those are.
AI produces plausible, confident, wrong output. A named verification step before work reaches a client, a filing, or a return is what keeps that from becoming your problem.
A written policy, a training record, and a review process. This is the difference between one person's mistake and the firm's failure.
Two phases, in order. The second doesn't happen without the first — putting AI to work inside a firm that can't say what it's already doing with AI just adds to the pile.
Phase 1
A bounded engagement that answers the question the firm can't currently answer: what is actually happening with AI here, and where is the exposure? Ends with a written, firm-specific policy and a prioritized readiness score partners can read in one page.
Phase 2
Once the exposure is closed, the same relationship turns to the upside — the drafting, intake, review, and reconciliation work that eats hours becomes solvable. Built and maintained on your own systems and accounts, so client data never leaves your control.
The obligations differ by profession, so the policy does too. The audit is the same engagement; what it measures against is not.
Written against the duties in ABA Formal Opinion 512 and the applicable Rules of Professional Conduct, with the citation-verification and confidentiality failures courts are actively sanctioning.
See the planThe same audit, measured against the obligations that govern client financial data and professional standards in accounting practice. The engagement runs today — the published plan is still being written.
Talk to us about your firmA short conversation is enough to tell whether there's a gap worth closing at your firm. No cost, no obligation, and no assumption that the answer is a project.
