Legal, Contracts, and Procurement
Artificial Intelligence (AI) and Law
A five-day course on the legal rules and risks that apply to artificial intelligence, covering AI fundamentals, data protection, liability and accountability, intellectual property and sector regulation, and AI governance and contract design. Participants learn to assess AI systems against regulatory requirements and allocate responsibility with contractual clarity.
Introduction
Artificial intelligence now drafts documents, screens contracts, predicts litigation outcomes, and supports judicial research. Each of those uses raises legal questions the existing framework only partly answers: who is liable when a model errs, what data may lawfully be used, and how far a regulator can inspect an opaque system. This Artificial Intelligence (AI) and Law Training Course gives legal, compliance, and technology professionals a complete working method for these questions. Participants learn AI fundamentals, data protection and liability frameworks, intellectual property questions, sector regulation, and AI governance design.
Artificial Intelligence (AI) and Law Course Objectives
- Apply AI fundamentals: machine learning, generative models, and their limits.
- Apply data protection law, including GDPR principles, to AI processing.
- Apply liability frameworks to AI-caused damage and automated decisions.
- Apply intellectual property questions in training data, outputs, and ownership.
- Apply sector regulation: finance, healthcare, employment, and consumer law.
- Apply the EU AI Act risk-based classification and obligations.
- Apply algorithmic transparency, explainability, and human oversight duties.
- Apply AI contract clauses: warranties, indemnities, and output rights.
- Apply AI governance programmes and internal control design.
- Measure performance with compliance coverage, incident rate, and review quality.
Course Methodology
- Facilitated sessions built on real regulatory texts, AI contracts, and enforcement decisions.
- Case workshops on automated decision liability, data misuse, and output ownership.
- Risk classification, clause drafting, and governance design exercises with live cases.
- AI policy and compliance framework drafting labs.
- Group exercise on an AI governance framework with a risk register.
Who Should Take This Course
- In-house counsel and legal advisors.
- Compliance and data protection officers.
- Technology and AI product managers.
- Contracts and procurement professionals buying AI systems.
- Risk managers and internal auditors.
- Regulators and policy analysts.
Artificial Intelligence (AI) and Law Course Outlines
AI Technology and Legal Context
- • Machine learning, neural networks, and generative AI basics.
- • Supervised, unsupervised, and reinforcement learning.
- • Model training data, bias, and accuracy limits.
- • Automated decision-making and profiling.
- • AI use cases in law: research, drafting, review, and prediction.
- • Legal profession duties and professional responsibility.
- • Framing legal questions about AI systems.
Data Protection and Privacy in AI
- • GDPR principles and lawful basis for AI processing.
- • Purpose limitation and data minimisation in model training.
- • Special category data and sensitive inference.
- • Automated decision-making rights and safeguards.
- • Cross-border data transfer for AI services.
- • Data retention, deletion, and model unlearning limits.
- • Data protection impact assessments for AI systems.
Liability, Responsibility, and Accountability
- • Liability sources: contract, tort, product liability, and negligence.
- • Responsibility for autonomous and semi-autonomous systems.
- • Causal attribution when multiple models contribute.
- • Insurance for AI-related losses and its limits.
- • Consumer protection and unfair practice rules.
- • Professional liability when AI aids advice.
- • Emerging liability proposals and compensation schemes.
Intellectual Property and Sector Regulation
- • Copyright in training data and text and data mining exceptions.
- • Ownership of AI-generated outputs and patentability questions.
- • Trade secrets and model disclosure conflicts.
- • The EU AI Act: risk categories and obligations.
- • Financial services, healthcare, and employment AI rules.
- • Facial recognition, biometric, and surveillance restrictions.
- • Sector enforcement trends and supervisory expectations.
AI Governance, Contracts, and Compliance
- • AI governance frameworks and accountability structures.
- • Risk assessment, model registers, and documentation.
- • Human oversight, testing, and monitoring duties.
- • AI contract clauses: warranties, indemnities, and audit rights.
- • Vendor due diligence and assurance for AI procurement.
- • Incident response and regulatory notification.
- • KPIs: compliance coverage, incident rate, and review quality.
- • Building an AI governance and compliance roadmap.
Conclusion
By successfully completing the Artificial Intelligence (AI) and Law Training Course, participants will have acquired a thorough working knowledge of AI technology and its legal context, data protection obligations, liability and accountability frameworks, intellectual property and sector regulation, and AI governance and contract design. They will leave able to assess AI systems against regulatory requirements, allocate responsibility with contractual clarity, and build a governance programme that withstands supervisory scrutiny. Gentex Training Center delivers this programme with legal, compliance, and technology practitioners working on live AI deployments.
FAQs for the Artificial Intelligence (AI) and Law course
— What is the "Artificial Intelligence (AI) and Law" course about?
It is a five-day programme on the legal rules and risks that apply to artificial intelligence. It covers AI fundamentals, data protection, liability and accountability, intellectual property and sector regulation, and AI governance and contract design.
— What are the key benefits of the "Artificial Intelligence (AI) and Law" course?
Participants assess AI systems against regulatory requirements before deployment, allocate liability and output ownership with contractual clarity, and build a governance programme with documented oversight that withstands supervisory scrutiny. They also respond to AI incidents with a prepared notification and remediation route.
— What skills will I gain from the "Artificial Intelligence (AI) and Law" course?
You will gain AI technology and legal context analysis, data protection and privacy compliance for AI, liability, accountability, and intellectual property assessment, and AI regulation, governance, and contract management.
— What tools, methods, or standards are covered in the "Artificial Intelligence (AI) and Law" course?
The course works with machine learning, neural network and generative AI fundamentals, supervised, unsupervised and reinforcement learning, model training data, bias and accuracy assessment, automated decision-making and profiling analysis, GDPR principles and lawful basis for AI processing, purpose limitation and data minimisation, special category data and sensitive inference, automated decision-making rights and safeguards, cross-border data transfer, data retention, deletion and model unlearning limits, data protection impact assessments, liability sources covering contract, tort, product liability and negligence, responsibility for autonomous and semi-autonomous systems, causal attribution analysis, AI insurance cover, consumer protection and unfair practice rules, professional liability for AI-assisted advice, copyright and text and data mining exceptions, ownership of AI-generated outputs and patentability, trade secret and disclosure conflicts, the EU AI Act risk categories and obligations, financial services, healthcare and employment AI rules, facial recognition and biometric restrictions, AI governance frameworks and accountability structures, risk assessment, model registers and documentation, human oversight, testing and monitoring duties, AI contract clauses covering warranties, indemnities and audit rights, vendor due diligence and assurance, incident response and regulatory notification, and KPIs covering compliance coverage, incident rate and review quality.
— How is the "Artificial Intelligence (AI) and Law" course applied in real-world practice?
Teams apply it when assessing an AI recruitment tool against employment and data protection rules, drafting contract clauses for an AI vendor covering output ownership and indemnity, running a data protection impact assessment for a model, classifying a system under the EU AI Act, responding to an AI incident with regulatory notification, and reviewing governance coverage at a compliance committee.
Scheduling in Progress | Training Arranged Around Your Needs
Our team can coordinate this program based on available dates and locations. Contact us to explore training options that best fit your needs.
Introduction
Artificial intelligence now drafts documents, screens contracts, predicts litigation outcomes, and supports judicial research. Each of those uses raises legal questions the existing framework only partly answers: who is liable when a model errs, what data may lawfully be used, and how far a regulator can inspect an opaque system. This Artificial Intelligence (AI) and Law Training Course gives legal, compliance, and technology professionals a complete working method for these questions. Participants learn AI fundamentals, data protection and liability frameworks, intellectual property questions, sector regulation, and AI governance design.
Artificial Intelligence (AI) and Law Course Objectives
- Apply AI fundamentals: machine learning, generative models, and their limits.
- Apply data protection law, including GDPR principles, to AI processing.
- Apply liability frameworks to AI-caused damage and automated decisions.
- Apply intellectual property questions in training data, outputs, and ownership.
- Apply sector regulation: finance, healthcare, employment, and consumer law.
- Apply the EU AI Act risk-based classification and obligations.
- Apply algorithmic transparency, explainability, and human oversight duties.
- Apply AI contract clauses: warranties, indemnities, and output rights.
- Apply AI governance programmes and internal control design.
- Measure performance with compliance coverage, incident rate, and review quality.
Course Methodology
- Facilitated sessions built on real regulatory texts, AI contracts, and enforcement decisions.
- Case workshops on automated decision liability, data misuse, and output ownership.
- Risk classification, clause drafting, and governance design exercises with live cases.
- AI policy and compliance framework drafting labs.
- Group exercise on an AI governance framework with a risk register.
Who Should Take This Course
- In-house counsel and legal advisors.
- Compliance and data protection officers.
- Technology and AI product managers.
- Contracts and procurement professionals buying AI systems.
- Risk managers and internal auditors.
- Regulators and policy analysts.
Artificial Intelligence (AI) and Law Course Outlines
AI Technology and Legal Context
- • Machine learning, neural networks, and generative AI basics.
- • Supervised, unsupervised, and reinforcement learning.
- • Model training data, bias, and accuracy limits.
- • Automated decision-making and profiling.
- • AI use cases in law: research, drafting, review, and prediction.
- • Legal profession duties and professional responsibility.
- • Framing legal questions about AI systems.
Data Protection and Privacy in AI
- • GDPR principles and lawful basis for AI processing.
- • Purpose limitation and data minimisation in model training.
- • Special category data and sensitive inference.
- • Automated decision-making rights and safeguards.
- • Cross-border data transfer for AI services.
- • Data retention, deletion, and model unlearning limits.
- • Data protection impact assessments for AI systems.
Liability, Responsibility, and Accountability
- • Liability sources: contract, tort, product liability, and negligence.
- • Responsibility for autonomous and semi-autonomous systems.
- • Causal attribution when multiple models contribute.
- • Insurance for AI-related losses and its limits.
- • Consumer protection and unfair practice rules.
- • Professional liability when AI aids advice.
- • Emerging liability proposals and compensation schemes.
Intellectual Property and Sector Regulation
- • Copyright in training data and text and data mining exceptions.
- • Ownership of AI-generated outputs and patentability questions.
- • Trade secrets and model disclosure conflicts.
- • The EU AI Act: risk categories and obligations.
- • Financial services, healthcare, and employment AI rules.
- • Facial recognition, biometric, and surveillance restrictions.
- • Sector enforcement trends and supervisory expectations.
AI Governance, Contracts, and Compliance
- • AI governance frameworks and accountability structures.
- • Risk assessment, model registers, and documentation.
- • Human oversight, testing, and monitoring duties.
- • AI contract clauses: warranties, indemnities, and audit rights.
- • Vendor due diligence and assurance for AI procurement.
- • Incident response and regulatory notification.
- • KPIs: compliance coverage, incident rate, and review quality.
- • Building an AI governance and compliance roadmap.
Conclusion
By successfully completing the Artificial Intelligence (AI) and Law Training Course, participants will have acquired a thorough working knowledge of AI technology and its legal context, data protection obligations, liability and accountability frameworks, intellectual property and sector regulation, and AI governance and contract design. They will leave able to assess AI systems against regulatory requirements, allocate responsibility with contractual clarity, and build a governance programme that withstands supervisory scrutiny. Gentex Training Center delivers this programme with legal, compliance, and technology practitioners working on live AI deployments.
FAQs for the Artificial Intelligence (AI) and Law course
— What is the "Artificial Intelligence (AI) and Law" course about?
It is a five-day programme on the legal rules and risks that apply to artificial intelligence. It covers AI fundamentals, data protection, liability and accountability, intellectual property and sector regulation, and AI governance and contract design.
— What are the key benefits of the "Artificial Intelligence (AI) and Law" course?
Participants assess AI systems against regulatory requirements before deployment, allocate liability and output ownership with contractual clarity, and build a governance programme with documented oversight that withstands supervisory scrutiny. They also respond to AI incidents with a prepared notification and remediation route.
— What skills will I gain from the "Artificial Intelligence (AI) and Law" course?
You will gain AI technology and legal context analysis, data protection and privacy compliance for AI, liability, accountability, and intellectual property assessment, and AI regulation, governance, and contract management.
— What tools, methods, or standards are covered in the "Artificial Intelligence (AI) and Law" course?
The course works with machine learning, neural network and generative AI fundamentals, supervised, unsupervised and reinforcement learning, model training data, bias and accuracy assessment, automated decision-making and profiling analysis, GDPR principles and lawful basis for AI processing, purpose limitation and data minimisation, special category data and sensitive inference, automated decision-making rights and safeguards, cross-border data transfer, data retention, deletion and model unlearning limits, data protection impact assessments, liability sources covering contract, tort, product liability and negligence, responsibility for autonomous and semi-autonomous systems, causal attribution analysis, AI insurance cover, consumer protection and unfair practice rules, professional liability for AI-assisted advice, copyright and text and data mining exceptions, ownership of AI-generated outputs and patentability, trade secret and disclosure conflicts, the EU AI Act risk categories and obligations, financial services, healthcare and employment AI rules, facial recognition and biometric restrictions, AI governance frameworks and accountability structures, risk assessment, model registers and documentation, human oversight, testing and monitoring duties, AI contract clauses covering warranties, indemnities and audit rights, vendor due diligence and assurance, incident response and regulatory notification, and KPIs covering compliance coverage, incident rate and review quality.
— How is the "Artificial Intelligence (AI) and Law" course applied in real-world practice?
Teams apply it when assessing an AI recruitment tool against employment and data protection rules, drafting contract clauses for an AI vendor covering output ownership and indemnity, running a data protection impact assessment for a model, classifying a system under the EU AI Act, responding to an AI incident with regulatory notification, and reviewing governance coverage at a compliance committee.
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Frequently Asked Questions
Does Gentex provide this training course in-house training?
Yes. Gentex Training Center can deliver this course as an in-house training program for your organization. The course content, schedule, and delivery can be customized to meet your team’s specific needs and business objectives. Learn more about our In-House Training solutions.