Advising Clients on AI

Policy, risk, adoption, contracts, compliance — the five questions, and how they land by client type.

In this lesson:

• Recognize the five questions underneath every client's AI ask
• Anticipate how the questions land for different client types
• Trace a client's ask back to its trigger and the questions it engages

The firm's own fluency as the credential — and the line between a credible offer and overreach.

In this lesson:

• Identify what makes a firm's AI advice credible to a client
• Distinguish credible offers from overreach
• Assemble the firm's own practice into proof

Readiness assessments, policy drafting, governance design, vendor review — four offerings with a start, an end, and a deliverable.

In this lesson:

• Describe the four core AI advisory offerings
• Scope an engagement with a deliverable, inputs, boundaries, and review
• Turn an open-ended request into a bounded first engagement

Professional boundaries — legal, accounting, consulting, technical — and how to name them without losing the client.

In this lesson:

• Distinguish the legal, accounting, consulting, and technical lanes in AI advice
• Use boundary language that keeps the client's trust
• Build a referral bench for the lanes you do not cover

Fixed-fee offerings clients understand — the packages, the retainer, and a proposal that fits on one page.

In this lesson:

• Explain why fixed fees suit AI advisory work
• Package the four offerings and a retainer at fixed prices
• Write a one-page proposal a client's leadership can approve

A structured method a firm can deliver — four dimensions, an inventory-to-report process, and the report leadership can act on.

In this lesson:

• Assess a client's AI readiness across use, data, people, and controls
• Deliver the assessment as a repeatable four-step method
• Write a short, evidenced, ranked readiness report

Acceptable use, risk tiers, review paths — adapted to the client — and the governance that makes the policy real.

In this lesson:

• Draft the five parts of a client's AI policy set
• Adapt a policy to the client's inventory, tasks, and roles rather than copying a template
• Design governance with an owner, review roles, a reporting path, and a cadence

The terms that matter in an AI contract, explained to a client in words they can act on, and the memo that records the decision.

In this lesson:

• Find the six terms that matter in any AI vendor contract
• Translate vendor language into what it means for the client
• Write a vendor review memo the client can act on and keep

Regulation at principle level as of September 2026 — mapping a client's uses to the principles, dating the map, and where to refer specialists.

In this lesson:

• Describe the regulatory landscape for AI at principle level as of September 2026
• Map a client's AI uses to the principles they engage
• Separate what an advisor maps from what a specialist must decide

Helping a client's people, not only their policy — why adoption needs support, the rollout, and the signals that it is working.

In this lesson:

• Explain why a policy fails without adoption support
• Run a four-step rollout with a client's leadership, trainers, and champions
• Read the signals that show whether adoption is real

What nobody knows yet about AI as of September 2026, and how to advise with confidence anyway.

In this lesson:

• Name what is genuinely uncertain about AI as of September 2026
• Advise on what holds regardless while bounding what does not
• Replace false certainty with honest, dated confidence

Showing clients how the firm works — the practices they should see, the walkthrough, and the mirror test.

In this lesson:

• List the firm's own AI practices a client should be able to see
• Walk a client through the firm's practice as evidence
• Use an admitted gap to make the rest of the practice credible

Principle-level protections — where AI advice creates exposure, the terms an engagement letter should address, and who drafts them.

In this lesson:

• Identify where AI advisory work creates exposure for the firm
• Name the engagement terms that address each exposure at principle level
• Set up the protections with the firm's own counsel, insurer, and professional rules

Three anonymized client engagements — the board question, the customer's deadline, the quiet practice — and what made them valuable.

In this lesson:

• Trace three composite AI advisory engagements from trigger to deliverable
• Identify the choices that made each engagement valuable
• Recognize the pattern shared by good AI advisory work

The one-page offer, the advisor's checklist, and your next client conversation; the finale.

In this lesson:

• Write a one-page AI advisory offer for your firm
• Run the advisor's checklist before and during every engagement
• Complete Advising Clients on AI