Artificial Intelligence in Accounting: Practical Applications

What Accountants Need to KnowIntroductionHistory of AIHistory of Accountants Using TechnologyOverview of How Accountants Are Using AIHuman Intelligence versus Artificial IntelligenceWhat Accountants Need to Know About AIArtificial IntelligenceArtificial Narrow Intelligence (ANI)Artificial General Intelligence (AGI)Machine ReasoningExpert SystemsMachine LearningSupervised LearningUnsupervised LearningSemi-supervised LearningReinforcement LearningDeep LearningNatural Language ProcessingData MiningText MiningRobotic Process Automation (RPA) and AIApplication Programming Interfaces (API) and AIBest Programming Languages Accountants Should Learn for Artificial Intelligence ApplicationsNotesReferencesApplications of AI in AccountingFinancial Accounting ApplicationsCash and Account ReconciliationsReceivables and SalesInventoryAccounts PayableManagement Accounting ApplicationsAudit ApplicationsTax ApplicationsAdvisory ApplicationsConclusionNoteReferencesRobotic Process Automation (RPA) and AIOverview of RPARPA VendorsWhen to Use RPA?Advantages and Challenges of RPAChallenges of RPAApplications of RPA in Public AccountingRPA in AuditsRPA in TaxApplications of RPA in Corporate AccountingImplementation of RPAWhy RPA FailsIntegrating RPA with AI/ML ApplicationsReferencesText MiningWhat is text mining?The role of natural language processing in text miningOverview of Text Mining ResearchMethods and Technologies Used in Text MiningDocument PreprocessingData Selection and FilteringData CleaningDocument RepresentationMorphological Normalization and ParsingSemantic AnalysisMiningClusteringClassificationEntity and Relation ExtractionVisualizationVisualization Techniques for Multidimensional DataText SummarizationAdvantages and Disadvantages of Text MiningCurrent and Potential Applications of Text Mining in AccountingAudit AutomationAccounting AutomationTax AutomationBusiness Advisory AutomationReferencesContemporary Case StudiesCase Study #1: Use of NLP for Risk Analysis (KPMG)Case Study #2: Use of AI for Tax Transfer Pricing Services (KPMG)Case Study #3: Autonomous Audit Drones for Inventory Management (EY)Case Study #4: Use of AI to Augment Auditor Judgment (Deloitte)Case Study #5: Use of Data Automation and RPA for Tax Functions (Grant Thornton)ConclusionNotesReferenceChallenges and Ethical Considerations of AIAlgorithmic BiasDefinition of Algorithmic BiasGuidance for Algorithmic Bias ConsiderationsSecurity, Privacy and Change Management RisksSecurity and Privacy RisksChange Management RisksRegulations Related to AIEthical ConsiderationsAccountability and Professional ResponsibilityFairness and Non-DiscriminationHuman Control of TechnologyPrivacy and SecurityTransparency and ExplainabilityPromotion of Human ValuesNoteReferencesFuture OutlookFuture of the Accounting ProfessionTechnology Changing the Landscape of the Accounting ProfessionFirm Hiring Trends of Accounting GraduatesSkillsets Needed in the Next Ten YearsAccounting EducatorsStrategies for Incorporating AI into the ClassroomAI Training for FacultyConclusionReferences
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