Introduction
The programme “Legal Data Analysis Using Artificial Intelligence” develops professional practice in Law. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from legal analysis, research, and memorandum drafting to governance, accountability, and compliance management, with practical work on artificial intelligence applications and controls, data analysis and decision support, contract drafting and allocation of obligations and risks. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Analyze a legal issue and write a memorandum distinguishing facts, rules, and alternatives in an application related to “Legal Data Analysis Using Artificial Intelligence”.
- Design an AI use case with verification criteria and human review.
- Turn available data into documented analysis that supports a specific professional decision.
- Draft contractual clauses connecting scope, acceptance, payment, and risk allocation.
- Define decision-making authority, accountability mechanisms, and obligation monitoring.
Learning areas
1. Legal Analysis, Research, and Memorandum Drafting
- Define the legal question, facts, documents, and parties, separating established facts from accounts and untested assumptions.
- Identify the relevant legal system, jurisdiction, and sources, and verify the law currently in force, its effective date, and amendments before applying it.
- Analyze the relationship between the rule and facts and areas of interpretation and disagreement, documenting arguments and evidence supporting each alternative.
- Draft a memorandum covering the issue, facts, analysis, options, and risks in clear language that preserves precise legal terminology.
- Review the memorandum for consistency, confidentiality, and citation accuracy, and identify matters requiring specialist advice or additional documents. The application examines a case related to “Legal Data Analysis Using Artificial Intelligence”.
2. Artificial Intelligence Applications and Controls
- Identify a task that AI can support, and separate inputs and human decisions from outputs produced by the tool.
- Prepare suitable test data and examples while respecting confidentiality, privacy, and permissions, and use de-identified training exercise data.
- Write clear instructions covering the task, context, constraints, and output format, and compare multiple formulations using a fixed set of examples.
- Check outputs for errors, bias, and unsupported information, and identify cases that require specialist review.
- Assess the feasibility of use in terms of quality, time, cost, and risk, and document controls for approval, monitoring, and stopping when failures occur.
3. Data Analysis and Decision Support
- Frame an analytical question linked to a specific decision, and define the unit of measurement, time period, and data needed to answer it.
- Check data quality for completeness, accuracy, consistency, and duplication, and document cleaning steps and limitations on reliance.
- Select appropriate comparisons, indicators, and charts, and distinguish statistical correlation from causal explanations of results.
- Interpret results in the work context, test assumptions and unusual values, and present alternatives and their associated uncertainty.
- Prepare an analytical report containing the finding, recommendation, data source and date, review owner, and next follow-up step.
4. Contract Drafting and Allocation of Obligations and Risks
- Define the contract's purpose, parties, legal capacity, signing authority, and constituent documents, and verify the relevant law and jurisdiction.
- Draft a clear scope, deliverables, acceptance criteria, and delivery schedule, and clarify the relationship between specifications, appendices, and document precedence.
- Review price, payment, change, warranty, and liability terms, connecting obligations to verification methods and evidence that can be retained.
- Define notice, delay, suspension, termination, and dispute resolution mechanisms, checking internal consistency and ensuring clauses do not conflict.
- Prepare a matrix for managing obligations, deadlines, correspondence, and changes, and practice handling a disagreement over scope or acceptance.
5. Governance, Accountability, and Compliance Management
- Map decision-making, oversight, and execution levels, and identify separation of roles and potential conflicts of interest.
- Review policies, committees, delegated authorities, and reporting frequency, and connect each responsibility to clear authority and limits.
- Create an obligations register specifying the source, scope, responsible party, and compliance evidence, and review applicable local requirements.
- Define disclosure, accountability, complaint handling, and misconduct reporting mechanisms, and protect information confidentiality during follow-up.
- Assess a practical governance case and prepare a gap remediation plan with review indicators and evidence of action closure.
Practical outputs
- A legal research memorandum, source list, and issues requiring verification.
- A use case brief and a test template for the quality of AI outputs.
- A dashboard and decision memo explaining the data, assumptions, and alternatives.
- Draft contract clauses, an obligations matrix, and a contract review checklist.
- An authority matrix, obligations register, and escalation and review mechanism.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in law, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Legal Data Analysis Using Artificial Intelligence” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Legal Data Analysis Using Artificial Intelligence” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.