Overview:
The integration of artificial intelligence is significantly reshaping the legal sector, with approximately 79% of law firms now employing AI tools within their operations. AI applications span generative research and drafting, predictive analytics for case strategies, and advanced contract review and document automation, marking substantial growth across the legal landscape. This course presents an accessible overview of core AI concepts-such as large language models, multimodal AI, and agentic systems-as well as common use cases. Participants will learn how legal professionals can increase efficiency and accuracy by leveraging AI technology.
The curriculum features practical examples of AI utilization in the legal profession, including automated document review, optimized contract analysis, and enhanced client communication. It also introduces industry tools such as ChatGPT, Claude, Harvey, CoCounsel by Casetext, Lexis+ AI, Spellbook, and other AI-driven legal research platforms, outlining both their capabilities and limitations. A strong emphasis is placed on the responsible adoption of AI, covering ethical and professional obligations, approaches to mitigating AI hallucinations, safeguarding client data confidentiality, and maintaining human oversight over AI-generated outputs.
Upon completion, attorneys will be equipped with a structured plan for incorporating AI into their practices. They will gain a comprehensive understanding of AI’s advantages and risks, including effective hallucination management, robust data governance, and compliance with emerging regulatory standards, and acquire best practices for prompt engineering and AI oversight. The course ensures participants leave with actionable guidance for the effective and ethical implementation of AI-powered legal technologies.
Course Objective:
By the end of this course, participants will:
- Grasp essential concepts in AI-such as generative models, large language models, multimodal AI, and agentic systems—and their relevance to legal practice.
- Recognize AI tools-including general models like ChatGPT, Claude, Gemini, and legal platforms like Harvey, CoCounsel, Lexis+ AI, Spellbook-that enhance research, drafting, contract review, and automation.
- Apply best practices for AI integration in legal workflows, upholding ethical standards through governance, managing hallucinations, prompt engineering, and ensuring client confidentiality.
Target Audience:
- Attorneys and legal professionals
- Law firm administrators
- In-house counsel
- Legal operations professionals
- Law students and legal researchers
Basic Knowledge:
- Basic understanding of legal research and writing
- General familiarity with legal technology and case management software
- No prior knowledge of AI is required
Curriculum
Total Duration: 1 Hour
Introduction to AI in Law (The 2026 Landscape)
Defining artificial intelligence and its operational principles, including large language models, generative AI, multimodal systems, and agentic AI platforms
Charting the progression of AI in legal practice: from foundational automation to advanced generative technologies and the emergence of agentic legal AI solutions
AI-Powered Tools for Legal Professionals
Overview of general-purpose generative AI models (such as ChatGPT, Claude, Gemini, Copilot) and their applications in legal research
Examination of legal-specific AI platforms: Harvey, CoCounsel, Lexis+ AI, Spellbook, and Kira Systems supporting contract review and document automation
Enhancing Legal Workflows with AI
Leveraging AI agents to automate routine tasks and optimize efficiency across legal processes
Employing AI for case law analysis, argument formulation, predictive analytics, and understanding opposing counsel behaviour patterns
Risks, Limitations, Ethical Considerations, and AI Governance
Identifying AI hallucinations, inherent biases, and system limitations; emphasizing the necessity for human oversight
Upholding confidentiality, robust data governance, client protection, and adherence to legal ethics alongside evolving AI regulations
Implementing AI in Legal Practice
Selecting appropriate AI solutions tailored to specific practice areas, distinguishing between general-purpose and legal-focused platforms
Adopting best practices for AI integration: beginning with pilot programs, utilizing prompt engineering, and establishing comprehensive AI governance frameworks