Information Package / Course Catalogue
Artificial Intelligence Applications in Accounting
Course Code: MVU117
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: No
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim of this course is to enable students to acquire fundamental knowledge and skills regarding the use of artificial intelligence technologies in accounting, to become familiar with AI-based applications used in accounting processes, to evaluate the impact of digital transformation on the accounting profession, and to use AI-supported tools ethically, safely, and effectively.

Course Content

The course covers the concepts and fundamental technologies of artificial intelligence, the changing role of the accounting profession in the digital transformation process, and the application areas of artificial intelligence in accounting. It also addresses the use of generative AI tools, document processing and data analysis, AI applications in financial reporting, auditing, and taxation, AI-supported solutions in accounting software, big data analytics and predictive analysis, decision support systems, robotic process automation (RPA), as well as ethical issues, data security, and the protection of personal data. In addition, students will develop practical applications related to accounting processes using current AI tools through case studies and hands-on activities.

Name of Lecturer(s)
Learning Outcomes
1.This course explains the fundamental concepts, components, and applications of artificial intelligence (AI) technologies in accounting.
2.It defines and describes the functions of AI applications used in accounting, financial reporting, auditing, and tax processes.
3.It explains the characteristics, purposes, and potential contributions of generative AI tools used in accounting.
4.It evaluates the role of AI-powered data analysis, reporting, and decision support systems in accounting processes.
5.It assesses AI applications from the perspectives of ethical principles, information security, personal data protection, and professional responsibility.
Recommended or Required Reading
1.Accounting Information Systems – Marshall B. Romney & Paul John Steinbart
2.Lecture Notes, Online Resources
Weekly Detailed Course Contents
Week 1 - Theoretical
Artificial Intelligence: Concepts, Historical Development, Core Technologies, Types of Artificial Intelligence, and Its Importance in Accounting
Week 2 - Theoretical
Digital Transformation, Industry 4.0 and Industry 5.0, the Evolving Accounting Profession, and the Accountant of the Future
Week 3 - Theoretical
Applications of Artificial Intelligence in Accounting Records, Financial Reporting, Auditing, Taxation, Financial Analysis, and Decision Support Systems
Week 4 - Theoretical
FinTech concept and its application areas
Week 5 - Theoretical
Automated Recognition and Classification of Invoices, e-Invoices, e-Archive Invoices, Receipts, and Other Financial Documents Using Artificial Intelligence
Week 6 - Theoretical
Artificial Intelligence Features in Microsoft Excel, Power BI, and Applications of Basic Data Analysis and Reporting
Week 7 - Theoretical
AI-Driven Financial Reporting, Financial Ratio Analysis, Interpretation of Financial Results, and Report Preparation
Week 8 - Theoretical
Applications of Artificial Intelligence in Auditing
Week 9 - Theoretical
Applications of Artificial Intelligence in Auditing
Week 10 - Theoretical
Artificial Intelligence in Tax Processes, e-Government Applications, and Digital Tax Systems
Week 11 - Theoretical
Robotic Process Automation (RPA): Concepts, Automation in Accounting Processes, and Practical Applications
Week 12 - Theoretical
Artificial Intelligence Ethics, Personal Data Protection, Information Security, and Professional Responsibility
Week 13 - Theoretical
Current Accounting Software, Case Studies, Practical Applications, and Project Presentations
Week 14 - Theoretical
The Impact of Artificial Intelligence on the Future of the Accounting Profession and Course Review
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%10
Quiz1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Individual Work1202
Quiz2216
Midterm Examination1516
Final Examination1516
TOTAL WORKLOAD (hours)48
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
2
5
3
2
4
2
3
2
2
OÇ-2
2
5
4
5
5
3
2
4
2
2
OÇ-3
2
4
3
2
5
3
2
4
3
2
OÇ-4
2
4
4
4
5
5
2
5
3
3
OÇ-5
5
3
4
2
4
3
2
3
2
3
Adnan Menderes University - Information Package / Course Catalogue
2026