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Applied Generative Artificial Intelligence (AI) for Accounting and Finance

  • Analytics & Tech
  • Artificial Intelligence
  • Finance & Investment
  • Basic
  • SkillsFuture
  • Short Courses
  • This module is part of Industry Graduate Diploma in Artificial Intelligence (AI) for Accounting & Advanced Certificate in Generative and Agentic AI for Accounting

This module is conducted on-campus.

To use your SkillsFuture Credit, please submit your claim through our payment portal. Do not submit the claim manually via the SkillsFuture page. Please refer to our step-by-step guide here.

Next course starts on
To be advised
Fee
SGD3,924* (as low as SGD457.20 after maximum funding) Learn More
Duration

3 days
Weekdays (9am - 6pm)

Level
Basic
Venue

Singapore Management University

Who Should Attend

  • Management Accountants
  • Financial Accountants
  • Auditors
  • Financial Controllers
  • Finance Managers

Overview

Most accounting professionals using Generative Artificial Intelligence (GenAI) lack a principled approach to tool selection. They rely on familiar platforms without assessing whether these tools are appropriate for the task, or whether sensitive financial data should be shared with cloud-based systems at all.

The course addresses this gap through a structured, practice-oriented approach. Participants will develop the judgement to select and apply the right tools across a broader ecosystem beyond ChatGPT and Copilot, including Claude, Gemini, Grok, NotebookLM, and open-source models running locally via Ollama. The focus shifts from "what can AI do?" to "which tool is appropriate for this task, and does the data allow it?"

This distinction is critical in professional settings. Cloud-based tools transmit data externally, which may not be suitable for client financials, confidential reports, or information governed by the Personal Data Protection Act (PDPA) and professional standards. Participants will learn to assess data sensitivity, apply appropriate safeguards, and leverage locally-run open-source models when data cannot leave the organisation's environment.

This course equips accounting and finance professionals with practical capabilities to confidently select and apply GenAI tools across accounting workflows, balancing performance, risk, and compliance in real-world contexts.
 

Learning Objectives

At the end of the 3-day programme, participants will be able to:

  • Distinguish between different Generative Artificial Intelligence (GenAI) tools (e.g., Claude, Gemini, Grok, open-source models, Notebook LM, among others besides ChatGPT and Copilot) and their relative strengths for different accounting tasks
  • Apply browser-based AI tools to research, knowledge synthesis, and framework development tasks, including researching tax law, understanding accounting standards, drafting procedure templates, and synthesising regulatory guidance
  • Assess data sensitivity and select appropriate GenAI tools based on whether data can be shared with cloud platforms or must remain within the organisation's environment
  • Use open-source models running locally through Ollama for confidential accounting data that cannot be uploaded to cloud services
  • Construct effective prompts for research and knowledge tasks using cloud-based tools
  • Critically evaluate AI-generated outputs for accuracy and appropriateness to the task at hand
  • Design a multi-tool approach to a complex accounting problem, justifying tool selection based on data sensitivity and task requirements

Assessment

As part of the requirement for Skills and Workforce Development Agency (SWDA), there will be an assessment conducted at the end of the course. Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion.

Calculate Programme Fee

Click here for more information about SkillsFuture Credits (Not applicable for Company-sponsored participants)
For PSEA - Available only for Singapore Citizen below 31 (Not applicable for Company-sponsored participants)

Total Program Fee: SGD0.00

Fee Table

EMPLOYER-SPONSORED

PARTICIPANT PROFILE

SELF-SPONSORED

SME

NON-SME

Singapore Citizen < 40 years old

Permanent Resident

LTVP+

$1,177.20

(After SWDA Funding 70%)

$457.20

(After SWDA Funding 70%
+ ETSS Funding 20%)

$1,177.20

(After SWDA Funding 70%)

Singapore Citizen ≥ 40 years old

$457.20

(After SWDA Funding 70%
+ MCES Funding 20%)

$457.20

(After SWDA Funding 70%
+ ETSS Funding 20%)

$457.20

(After SWDA Funding 70%
+ MCES Funding 20%)

International Participant

$3,924

(No Funding)

$3,924

(No Funding)

$3,924

(No Funding)

All prices include 9% GST

Please note that the programme fees are subject to change without prior notice.

SkillsFuture Level-Up Programme for Mid-Career Individuals
A SkillsFuture Credit (Mid-Career) top-up of $4,000 will be provided to Singaporeans aged 40 years and above to further offset out-of-pocket course fees for this programme.

Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.

Self Sponsored

SkillsFuture Credit

Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.

This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.

Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).

Workfare Skills Support Scheme

From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.

Employer Sponsored

Enhanced Training Support for SMEs (ETSS)

  • Organisation must be registered or incorporated in Singapore
  • Employment size of not more than 200 or with annual sales turnover of not more than $100 million
  • Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
  • Trainees must be Singapore Citizens or Singapore Permanent Residents
  • Trainees must not be a full-time national serviceman
  • Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here. 

Please click here for more information on ETSS.

Absentee Payroll

Employers who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:

AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)

Intake Information

Next Intake: To be advised

*Registration will close 5 calendar days before the course start date, or once the class is full, whichever comes first.

Course commencement is subject to sufficient enrolment and confirmation by SMU Academy.

Affiliate Faculty

Dr. Benjamin Lee
Assistant Professor of Accounting (Education); Assistant Dean (Student and Alumni Engagement); Faculty Lead (AI in Education)
Singapore Management University
Dr. Benjamin Lee
Assistant Professor of Accounting (Education); Assistant Dean (Student and Alumni Engagement); Faculty Lead (AI in Education)
Singapore Management University

Dr. Lee earned his PhD in Management (Strategy and Technology Management) from Adam Smith Business School, University of Glasgow. His research interests are in the adoption of AIDA technologies to solve accounting problems such as cashflow management, cost allocation, credit risk analysis, financial forecasting, fraud prediction, and inventory control. He has actively shared about the SMU-X learning approach at various conferences and seminars as well as in his May 2022 TED talk titled “Finding our Place in an AI World”.  

Prior to joining SMU, he was a consulting data analyst at the Accountant-General’s Department (Singapore) working on applying machine learning to improve internal auditing processes.  

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