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Master AI Accountant & CPA Certification · Digital course

MAAC Level 3 — Advanced AI Accounting Operations

Self-paced enrollment in Level 3 of the Master AI Accountant & CPA Certification: Design AI-assisted engagement workflows that fit a firm's system of quality management: standard operating procedures with control points, a retrieval library built from primary sources, safe integrations with the ledger and tax software, review sampling, escalation and stop rules, and honest performance measurement.

Modules
14
Estimated time
40 hours
Access
Self-paced

Single-user enrollment

$549.00

One-time purchase

Enrollment includes

Controlled AI training built for accounting work

Evaluate AI tools for accounting use cases, limitations, data handling, and control requirements.

Design prompts and review procedures that produce traceable, decision-ready work.

Apply AI to close, reporting, tax, audit, forecasting, and financial analysis workflows.

Automate repetitive processes without removing approvals, reconciliations, or accountability.

Curriculum at a glance

From AI fundamentals to accounting firm growth

View all 14 modules
  1. Module 01

    From Task to System: The Operations View of Accounting AI

    Level 3 opens with the shift from one careful AI-assisted task to work a team runs across many clients: why volume, handoffs and shared inputs change the risk, how workload breeds complacency and silent errors, how confident wrong output travels into later decisions, and why an operation needs a named owner and a measured baseline before redesign.

  2. Module 02

    Mapping a Close, Tax or Engagement Workflow Before Automating It

    Before any AI is added, map the workflow as it really runs. This module captures undocumented steps and exceptions, locates each proposed AI use by COSO's GenAI capability types, marks handoffs, review points and the IT general controls beneath them, and recognises when a public company process change needs evaluation, with step-level timings to test later claims.

  3. Module 03

    Risk-Tiering Accounting AI Tasks by Consequence and Reversibility

    How to sort AI-assisted accounting tasks into tiers by what a wrong output would cost and how hard it would be to undo, raise a tier when reliance factors demand it, attach review depth, reviewer, records and escalation to each tier, start agentic uses at the bottom, and keep a register that says when a task must be tiered again.

  4. Module 04

    Writing an SOP a Reviewing Professional Can Enforce

    How to turn a firm's AI policy into standard operating procedures a reviewer can hold people to: where firm procedure duties come from and what they leave to the firm, steps and verification points for facts, citations and calculations, records of who performed and reviewed the work and how AI was used, and testing the SOP on someone new.

  5. Module 05

    Building a Retrieval Corpus From Firm Knowledge

    How to build the document collection an AI research tool retrieves from: choosing which firm memos, policies and templates belong in it, keeping authoritative sources distinct from firm material, tagging every document by tax year, jurisdiction, entity type, audit framework and currency, and recording provenance, integrity, ownership and retirement.

  6. Module 06

    Retrieval Failure Modes: Superseded Guidance, Wrong Year and Wrong Entity

    How a firm retrieval system fails with confidence: proposed or superseded rules served as current, a wrong tax year, state, entity type or audit framework, invented citations, and poisoned or instruction-laden documents in the corpus. It closes with what changed in the OWASP 2026 list and defences that constrain the system rather than trust the model.