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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
5
Estimated time
16 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 5 modules
  1. Module 01

    Workflow Design for Accounting Engagements

    Map a close, a tax preparation pipeline, or an audit fieldwork plan end to end, find the steps where AI helps, classify each step by the consequence of an error, and write a standard operating procedure with control points that fits the firm's quality management system.

  2. Module 02

    Knowledge Bases and Retrieval for Firm Standards

    Build a retrieval library from the Codification, the Code, regulations, IRS guidance, and firm methodology; manage currency and effective dates so the right year's rule is retrieved; and test retrieval quality before staff rely on it.

  3. Module 03

    Automation and Integrations in the Finance Stack

    Automate transaction classification, reconciliation matching, and document intake with review queues and exception handling, and connect AI tools to the general ledger, tax software, and audit platforms without breaking segregation of duties, validation, or change control.

  4. Module 04

    Quality Assurance and Escalation

    Design sampling and review plans for AI outputs with a shared error taxonomy, define escalation paths and stop rules that halt an automation when it should be halted, and understand how auditors evaluate AI-generated information as evidence.

  5. Module 05

    Performance Measurement and Case Studies

    Measure an AI-assisted workflow honestly — throughput, accuracy, review cost, error cost, and realisation — present results to leadership, and work through two extended case studies: a growing company's month-end close and a mid-size firm's busy-season tax pipeline.