# AI for Accounting and Finance Professionals

> Apply AI to reconciliations, forecasting, reporting and audit work, and manage the control and ethics risks it brings.

- **Provider:** Afriskora Training Solutions
- **Category:** Data, AI & Digital Skills
- **Duration:** 3 days
- **Formats:** classroom (cities across Africa), live virtual (Zoom/Teams), in-house for teams
- **Certificate:** Afriskora Certificate of Completion, verifiable online
- **Booking:** request dates and a quote; invoice and EFT payment
- **Web page:** https://afriskora.co.za/courses/data-ai-digital/ai-for-accounting-and-finance-professionals
- **Request dates:** https://afriskora.co.za/request-training?course=ai-for-accounting-and-finance-professionals

## Overview

Finance teams are using AI to close the books faster, forecast cash more accurately and review far more transactions than sampling allows. This course shows accountants, treasury staff and auditors where AI adds value today, how to use generative AI and Copilot on finance tasks, and how to keep controls, audit trails and professional judgement intact. Practical sessions use anonymised ledgers and budgets.

## Who should attend

- Accountants, financial controllers and CFOs
- Treasury and FP&A teams
- Internal and external auditors
- Finance systems and transformation staff

## Learning outcomes

- Identify high-value AI use cases across the finance function
- Use generative AI for variance commentary, policies and reporting drafts
- Apply machine-learning forecasting to revenue and cash flow
- Use AI-assisted analytics to test entire transaction populations
- Design controls, documentation and ethics safeguards for AI in finance

## Course outline

### Module 1: AI across the finance function

- Automation, analytics and generative AI compared
- Use cases in close, payables, treasury and tax
- Copilot and ChatGPT for finance writing tasks
- Data readiness in the general ledger

### Module 2: Forecasting and analytics

- Machine-learning cash and revenue forecasts
- Anomaly detection in journals and payments
- Full-population testing for audit
- Building an AI-assisted management pack

### Module 3: Control, ethics and adoption

- Model risk and explainability for finance
- IFAC and IRBA guidance on technology
- Segregation of duties when bots post entries
- Roadmap for an AI-enabled finance team