ID:
511610
Duration (hours):
22
CFU:
3
SSD:
ECONOMIA AZIENDALE
Year:
2025
Overview
Date/time interval
Secondo Semestre (16/02/2026 - 23/05/2026)
Syllabus
Course Objectives
The course aims to provide students with in-depth knowledge of the latest Artificial Intelligence tools for modern management accounting, corporate control, tax litigation, extraordinary corporate transactions, and auditing. Upon completion of the course, students will be able to use the latest Artificial Intelligence applications (ChatGPT 5.0 and subsequent releases, Claude, Power BI, Microsoft Copilot, Notebook LM, Gemini AI, etc.) within the aforementioned business and professional areas. The course also teaches Prompt Engineering techniques and the creation and design of Agentic Applications, enabling them to address the emerging challenges of responsible and sustainable business and professional management, aligned with the goals of the 2030 Agenda for Sustainable Development (SDGs).
Course Prerequisites
The course must be considered as belonging to advanced economic-business training and, as such, requires and presupposes basic knowledge of general and applied accounting and basic knowledge of IT (Windows operating system, Office application system or similar).
Teaching Methods
The course will be delivered through lectures. All lessons will be supported by slides and/or other multimedia content, uploaded to the KIRO learning platform in conjunction with the course. Since it is designed as a laboratory, in addition to the theoretical portion, there will be practical sessions conducted in Work&Class mode, with business and professional case studies (filing a tax appeal, financial statement analysis, company valuation, etc.), to be solved individually or in teams, followed by a general discussion in the classroom. In some lessons, the instructor will be supported by national professionals or managers from software development companies or professional publishing firms.
Assessment Methods
The exam will consist of two written tests. The first, individual, will consist of 60 multiple-choice questions. The second, in teamwork, will focus on a practical case study in a professional firm or company (possible examples: preparing a tax appeal, financial statement analysis, company valuation, planning the activities envisaged for an extraordinary transaction, drafting a business plan or company budget, etc.). This second test will be presented jointly by the team. The grade for the second test will be shared among all candidates in the team. The final grade for each candidate will be the average of the grade assigned in the first individual test and the joint grade assigned to the team in the second test.
Texts
1) ODCEC Milan Accountants Foundation - Examples of basic applications of Business Intelligence in professional firms 2) National Accountants Foundation - The accountant in the age of artificial intelligence 3) PowerBI for budgeting and forecasting 4) Generative artificial intelligence - Guide to using the platforms 5) National Accountants Foundation - Intelligent help for the accountant 6) Kissinger, Schmidt, Huttenlocker - The age of artificial intelligence 7) Other material will be uploaded directly to the Kiro platform
Contents
The course will be divided into the following modules: Module 1 – Introduction to Artificial Intelligence for Economics and Accounting 1.1. What is AI: basic concepts, history, and evolution 1.2. Difference between generative AI and predictive AI 1.3. Impact of AI on the work of accountants and auditors 1.4. The ethical and regulatory framework (GDPR, professional liability, EU guidelines) Module 2 – Generative AI tools for accounting professionals 2.1. ChatGPT, Gemini, Claude, Copilot, Notebook LM: comparative overview 2.2. Generation of professional texts: contracts, opinions, reports 2.3. Practical applications: drafting financial statements, explanatory notes, corporate minutes 2.4. Automation of communication with clients (emails, reports, FAQs) 2.5. Lab: Prompt Engineering for Accounting and Taxation Module 3 – Predictive AI and Data Analysis 3.1. Machine learning for economic and financial analysis 3.2. Predictive balance sheet models: forecasting cash flows, revenues and costs 3.3. Business valuation with predictive models (DCF and AI-assisted multiples) 3.4. Software tools: Power BI, Python (Pandas, Scikit-learn), Excel with AI 3.5. Lab: Building a predictive model on balance sheet datasets Module 4 – Specific Applications for the Accounting Profession 4.1. Legal review and audit with AI tools (anomaly, fraud, risk analysis) 4.2. Tax return automation and tax compliance 4.3. AI for document management and data extraction from PDFs, invoices, contracts 4.4. RPA (Robotic Process Automation) tools integrated with AI 4.5. Workshop: Building a Virtual Assistant for Tax Management Module 5 – Advanced Multimodal Generative AI Tools 5.1. AI for Image and Presentation Generation (MidJourney, DALL·E, Canva AI) 5.2. AI for Speech Synthesis and Analysis (Whisper, Speech-to-Text, Text-to-Speech) 5.3. AI for Videos and Simulations (Runway, Synthesia) 5.4. Workshop: Creating Interactive Reports and Automatic Presentations for Clients Module 6 – Designing Integrated Workflows 6.1. How to Integrate Multiple AI Tools in a Company or Professional Firm 6.2. Automating Tax Deadlines and Periodic Tasks 6.3. Connecting Databases, Management Systems, and AI Tools 6.4. Workshop: Designing an “AI Accounting Workflow” Module 7 – Case Studies and Final Exercises 7.1. Business Case: Financial Statement Analysis with Generative + Predictive AI 7.2. Tax Case: Automated Drafting of a Tax Opinion 7.3. Management Case: Building Predictive Dashboards for Strategic Decisions 7.4. Student Final Project Presentations Module 8 – Future Perspectives 8.1. Evolution of AI for Accounting Professionals 8.2. New Skills Demanded by the Market 8.3. Towards the “Augmented Accountant”
Course Language
Italian
More information
No additional study material is provided for non-attending students.
Degrees
Degrees
BUSINESS ADMINISTRATION AND LAW
Master’s Degree
2 years
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People
People
Teaching staff
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