Introduction:

Excel has long been the cornerstone tool in accounting, but the integration of Artificial Intelligence (AI) is transforming how accountants analyze, process, and present financial information. Today’s accountants need more than formulas and pivot tables; they must leverage AI techniques, predictive analytics, and intelligent automation directly within Excel and Microsoft’s ecosystem. This conference provides advanced structures for financial analysis, reporting, auditing, and compliance through Excel enhanced with AI tools. It equips participants with frameworks, methods, and applications that drive accuracy, efficiency, and forward looking decision making in accounting functions.

Conference Objectives:

By the end of this conference, participants will be able to:

Analyze financial data using advanced Excel models integrated with AI techniques.
Explore predictive analytics and machine learning algorithms in Excel for accounting forecasts.
Classify automated auditing and reconciliation methods powered by AI Excel integration.
Evaluate tax, compliance, and reporting processes through AI-driven Excel solutions.
Use advanced financial models that combine Excel functionality with AI enabled tools.

Target Audience:

Accounting Managers and Supervisors.
Financial Analysts and Controllers.
Internal Auditors and Compliance Officers.
ERP and Accounting System Specialists.
Accountants seeking advanced AI-driven Excel skills.

Conference Outline:

Unit 1:

Advanced Excel Structures for Accounting Analysis:

Frameworks for multi-sheet financial modeling and structured consolidation.
Methods for advanced pivot tables linking large-scale accounting datasets.
Tools for variance and sensitivity analysis using dynamic Excel functions.
Structures for cash flow tracking and revenue-expense alignment.
Steps for integrating external financial databases with Excel for enhanced accuracy.

Unit 2:

AI Powered Data Management in Excel:

Methods for cleaning and structuring accounting data using Power Query with AI support.
Application of natural language queries in Excel to process large datasets instantly.
AI driven classification of transactions into standardized accounting categories.
Automation of repetitive accounting entries through AI enabled macros.
Structures for detecting inconsistencies in ledgers using anomaly detection models.

Unit 3:

Predictive Analytics and Forecasting in Excel:

AI assisted forecasting techniques for revenue, expenses, and cash flows.
Time series modeling in Excel for budget and performance predictions.
Predictive models for credit risk assessment embedded within Excel.
Key steps for integrating machine learning models from Azure ML into Excel for financial forecasts.
Evaluation frameworks for accuracy and reliability of predictive accounting models.

Unit 4:

Intelligent Automation and Audit Functions:

Structures for automating reconciliations between bank statements and general ledgers.
AI enhanced audit sampling techniques embedded in Excel for compliance checks.
Methods for anomaly detection in expense claims and vendor invoices.
Governance frameworks for AI driven error correction in accounting spreadsheets.
Tools for linking Excel with Power Automate to streamline audit workflows.

Unit 5:

Specialized AI Applications in Excel for Accounting:

AI driven reconciliation models for invoices, payments, and journal entries.
Structures for automated fraud detection using anomaly recognition algorithms.
Advanced frameworks for tax calculation and compliance monitoring through Excel AI integration.
Predictive cash flow modeling with AI assisted time series forecasting tools.
Methods for embedding AI powered audit trails within Excel to ensure transparency and regulatory adherence.

Conference on Excel Skills and AI Knowledge Related to Accounting