Tax, Technology & AI — Study Summary
Tax, Technology & AI
Study Summary
Core Overview · Exam Themes · Consolidated Glossary
Part 1 — Core Overview.............................................................................................................. 2
1. Big Picture: What This Course Is About...............................................................................2
1.1 Tax & Technology.........................................................................................................2
1.2 AI Regulation & Governance.........................................................................................2
1.3 Data Protection & Fundamental Rights.........................................................................2
1.4 Tax Compliance, Risk & Control....................................................................................2
1.5 Algorithmic Transparency & Accountability...................................................................2
2. Core Themes for the Exam..................................................................................................3
2.1 Digital Transformation of Tax (Tax Administration 3.0)..................................................3
2.2 AI and Algorithmic Decision-Making in Tax...................................................................3
2.3 The EU AI Act — Risk-Based Regulation......................................................................3
2.4 GDPR and Data Protection in a Tax/AI Context............................................................3
2.5 Fundamental Rights and Proportionality........................................................................3
2.6 Tax Control, Governance, and Cooperative Compliance..............................................4
2.7 Algorithm Registers and Transparency Initiatives..........................................................4
Consolidated Glossary A–Z.......................................................................................................... 5
Page 1 of 22
, Tax, Technology & AI — Study Summary
Part 1 — Core Overview
1. Big Picture: What This Course Is About
The course sits at the intersection of five interconnected fields:
1.1 Tax & Technology
• Digital transformation of tax administrations (Tax Administration 3.0).
• Use of AI, data analytics, ERP platforms, and e-invoicing in tax compliance.
• Tax Operating Models (TOM) and Tax Control Frameworks (TCF) in a data-driven
environment.
1.2 AI Regulation & Governance
• The EU AI Act: a risk-based approach to AI systems.
• Classification of AI systems (prohibited, high-risk, limited-risk, etc.).
• Obligations of providers and deployers, conformity assessment, and CE marking.
1.3 Data Protection & Fundamental Rights
• GDPR principles, rights, and obligations.
• Automated decision-making and profiling (Art. 22 GDPR).
• Charter of Fundamental Rights: privacy, data protection, non-discrimination, right to a fair
trial, and proportionality.
1.4 Tax Compliance, Risk & Control
• Tax risk management, governance, internal controls, and KPIs.
• Cooperative compliance and the taxpayer–authority relationship.
• Data quality, governance, and analytics to support correct tax outcomes.
1.5 Algorithmic Transparency & Accountability
• Public algorithm registers.
• Documentation and explanation duties for government use of algorithms.
• Human oversight, bias mitigation, and accountability.
Part 1 provides a conceptual map of these areas and an alphabetical glossary you can annotate
for exam preparation.
Page 2 of 22
, Tax, Technology & AI — Study Summary
2. Core Themes for the Exam
2.1 Digital Transformation of Tax (Tax Administration 3.0)
• Shift from paper-based to data-driven, real-time tax compliance.
• Key examples:
◦ E-invoicing and continuous transaction controls — real-time reporting of invoices.
◦ Automated VAT reporting from ERP systems.
◦ Data-matching and risk scoring by tax authorities.
• Taxpayers need robust Tax Operating Models (TOM), Tax Control Frameworks (TCF)
integrated with business and IT, and data governance ensuring quality, completeness,
and timeliness.
2.2 AI and Algorithmic Decision-Making in Tax
• Tax authorities and companies use risk-scoring models for audits, profiling of taxpayers,
and chatbots/LLMs for guidance and internal support.
• Legal and ethical issues include:
◦ Transparency — why did the system flag this taxpayer?
◦ Explainability versus black-box models.
◦ Bias and discrimination risks (e.g., profiling of certain groups).
◦ Effective human oversight, rather than mere rubber-stamping.
2.3 The EU AI Act — Risk-Based Regulation
• AI systems are categorised by risk level:
◦ Prohibited AI — unacceptable risks (e.g., manipulative or exploitative systems).
◦ High-risk AI — subject to strict obligations; includes many public-sector, financial,
and tax uses that affect individual rights.
◦ Limited/low-risk AI — transparency duties only (e.g., chatbots must disclose their
nature).
• Key obligations for high-risk systems: risk management and data governance; technical
documentation and record-keeping; transparency and information provision; human
oversight; and accuracy, robustness, and cybersecurity.
• Providers and deployers have distinct legal responsibilities.
• Conformity assessment and CE marking are required before a high-risk AI system may
be placed on the EU market.
2.4 GDPR and Data Protection in a Tax/AI Context
• Core principles: lawfulness, fairness, and transparency; purpose limitation; data
minimisation; accuracy; storage limitation; security; and accountability.
• Special issues:
◦ Automated decision-making and profiling (Art. 22 GDPR).
◦ Data Protection Impact Assessments (DPIA) for high-risk processing, including many
AI systems.
◦ Data subject rights: access, rectification, erasure, objection, and others.
◦ Distinction between controllers (who determine purposes and means) and
processors (who process on the controller's behalf).
2.5 Fundamental Rights and Proportionality
• Relevant Charter provisions:
Page 3 of 22
Tax, Technology & AI
Study Summary
Core Overview · Exam Themes · Consolidated Glossary
Part 1 — Core Overview.............................................................................................................. 2
1. Big Picture: What This Course Is About...............................................................................2
1.1 Tax & Technology.........................................................................................................2
1.2 AI Regulation & Governance.........................................................................................2
1.3 Data Protection & Fundamental Rights.........................................................................2
1.4 Tax Compliance, Risk & Control....................................................................................2
1.5 Algorithmic Transparency & Accountability...................................................................2
2. Core Themes for the Exam..................................................................................................3
2.1 Digital Transformation of Tax (Tax Administration 3.0)..................................................3
2.2 AI and Algorithmic Decision-Making in Tax...................................................................3
2.3 The EU AI Act — Risk-Based Regulation......................................................................3
2.4 GDPR and Data Protection in a Tax/AI Context............................................................3
2.5 Fundamental Rights and Proportionality........................................................................3
2.6 Tax Control, Governance, and Cooperative Compliance..............................................4
2.7 Algorithm Registers and Transparency Initiatives..........................................................4
Consolidated Glossary A–Z.......................................................................................................... 5
Page 1 of 22
, Tax, Technology & AI — Study Summary
Part 1 — Core Overview
1. Big Picture: What This Course Is About
The course sits at the intersection of five interconnected fields:
1.1 Tax & Technology
• Digital transformation of tax administrations (Tax Administration 3.0).
• Use of AI, data analytics, ERP platforms, and e-invoicing in tax compliance.
• Tax Operating Models (TOM) and Tax Control Frameworks (TCF) in a data-driven
environment.
1.2 AI Regulation & Governance
• The EU AI Act: a risk-based approach to AI systems.
• Classification of AI systems (prohibited, high-risk, limited-risk, etc.).
• Obligations of providers and deployers, conformity assessment, and CE marking.
1.3 Data Protection & Fundamental Rights
• GDPR principles, rights, and obligations.
• Automated decision-making and profiling (Art. 22 GDPR).
• Charter of Fundamental Rights: privacy, data protection, non-discrimination, right to a fair
trial, and proportionality.
1.4 Tax Compliance, Risk & Control
• Tax risk management, governance, internal controls, and KPIs.
• Cooperative compliance and the taxpayer–authority relationship.
• Data quality, governance, and analytics to support correct tax outcomes.
1.5 Algorithmic Transparency & Accountability
• Public algorithm registers.
• Documentation and explanation duties for government use of algorithms.
• Human oversight, bias mitigation, and accountability.
Part 1 provides a conceptual map of these areas and an alphabetical glossary you can annotate
for exam preparation.
Page 2 of 22
, Tax, Technology & AI — Study Summary
2. Core Themes for the Exam
2.1 Digital Transformation of Tax (Tax Administration 3.0)
• Shift from paper-based to data-driven, real-time tax compliance.
• Key examples:
◦ E-invoicing and continuous transaction controls — real-time reporting of invoices.
◦ Automated VAT reporting from ERP systems.
◦ Data-matching and risk scoring by tax authorities.
• Taxpayers need robust Tax Operating Models (TOM), Tax Control Frameworks (TCF)
integrated with business and IT, and data governance ensuring quality, completeness,
and timeliness.
2.2 AI and Algorithmic Decision-Making in Tax
• Tax authorities and companies use risk-scoring models for audits, profiling of taxpayers,
and chatbots/LLMs for guidance and internal support.
• Legal and ethical issues include:
◦ Transparency — why did the system flag this taxpayer?
◦ Explainability versus black-box models.
◦ Bias and discrimination risks (e.g., profiling of certain groups).
◦ Effective human oversight, rather than mere rubber-stamping.
2.3 The EU AI Act — Risk-Based Regulation
• AI systems are categorised by risk level:
◦ Prohibited AI — unacceptable risks (e.g., manipulative or exploitative systems).
◦ High-risk AI — subject to strict obligations; includes many public-sector, financial,
and tax uses that affect individual rights.
◦ Limited/low-risk AI — transparency duties only (e.g., chatbots must disclose their
nature).
• Key obligations for high-risk systems: risk management and data governance; technical
documentation and record-keeping; transparency and information provision; human
oversight; and accuracy, robustness, and cybersecurity.
• Providers and deployers have distinct legal responsibilities.
• Conformity assessment and CE marking are required before a high-risk AI system may
be placed on the EU market.
2.4 GDPR and Data Protection in a Tax/AI Context
• Core principles: lawfulness, fairness, and transparency; purpose limitation; data
minimisation; accuracy; storage limitation; security; and accountability.
• Special issues:
◦ Automated decision-making and profiling (Art. 22 GDPR).
◦ Data Protection Impact Assessments (DPIA) for high-risk processing, including many
AI systems.
◦ Data subject rights: access, rectification, erasure, objection, and others.
◦ Distinction between controllers (who determine purposes and means) and
processors (who process on the controller's behalf).
2.5 Fundamental Rights and Proportionality
• Relevant Charter provisions:
Page 3 of 22
