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AI TRAINING

AI for Legal Teams: Contract Review and Discovery

Legal professionals gain practical AI skills to accelerate contract analysis, privilege review, and e-discovery workflows.

Format
programme
Duration
16–28h
Level
practitioner
Group size
6–20
Price / participant
€3K–€5K
Group price
€18K–€40K
Audience
General Counsels, in-house legal counsel, and legal operations managers in mid-to-large organisations
Prerequisites
Basic familiarity with contract management processes and e-discovery; no prior AI or data science experience required

What it covers

This practitioner-level programme equips in-house legal teams with the tools and frameworks to deploy AI across contract lifecycle management, privilege log generation, and e-discovery. Participants learn to evaluate and select legal AI vendors, understand the implications of AI-assisted billing models, and build governance guardrails for privileged and confidential data. Sessions combine live tool demonstrations, hands-on contract analysis exercises, and structured discussion of real-world implementation cases from comparable legal departments.

What you'll be able to do

  • Configure and run an AI-assisted contract review workflow, including clause-level risk flagging against a defined playbook
  • Design a privilege review protocol that combines AI classification with attorney sign-off checkpoints and a defensible audit trail
  • Evaluate and score at least three legal AI vendors against a structured RFP scorecard covering accuracy, data residency, and integration
  • Identify and mitigate the top five AI-related professional responsibility and confidentiality risks specific to in-house legal teams
  • Build a business case quantifying time and cost savings from AI-assisted review for presentation to executive stakeholders

Topics covered

  • AI-assisted contract review: clause extraction, risk flagging, and deviation detection
  • Privilege review workflows: using AI for log generation and responsiveness classification
  • E-discovery fundamentals: AI-driven document review, technology-assisted review (TAR) and continuous active learning (CAL)
  • Legal AI vendor landscape: evaluating tools such as Relativity, Kira, Harvey, and Luminance
  • Data security and confidentiality: handling privileged and sensitive data in AI environments
  • Billing model shift: implications of AI on hourly billing, alternative fee arrangements, and outside counsel management
  • AI governance and ethics in legal practice: hallucination risk, audit trails, and professional responsibility
  • Change management: building legal team adoption and defining human-in-the-loop review standards

Delivery

Delivered as a blended programme across four half-day sessions (remote or in-person) with optional on-site workshop for tool demonstrations. Hands-on work accounts for approximately 50% of contact time, including live access to sandboxed contract review and e-discovery platforms. Participants receive a legal AI vendor comparison matrix, a privilege review protocol template, and a governance policy starter kit. Cohorts can be run as open-enrolment or closed in-house programmes tailored to the organisation's existing tech stack.

What makes it work

  • Nominating a legal ops champion who owns the AI tooling roadmap and acts as the internal point of escalation for quality issues
  • Establishing a human-in-the-loop review standard before any AI-assisted output is used in litigation or transactional matters
  • Running a pilot on a contained, low-risk contract corpus before scaling to high-value or regulated agreement types
  • Aligning general counsel and CFO on revised billing assumptions early to prevent internal friction as AI reduces billable-hour proxies

Common mistakes

  • Treating AI output as final without attorney review, creating professional responsibility exposure and eroding court defensibility
  • Selecting a legal AI vendor based on demos alone without assessing data residency, model transparency, and privilege handling protocols
  • Failing to update outside counsel guidelines and alternative fee arrangements to reflect AI-driven efficiency gains
  • Deploying AI contract tools on unstructured legacy contract repositories without a data cleansing and metadata tagging phase

When NOT to take this

This programme is not suitable for a small law firm or solo practitioner whose document volumes are too low to justify AI-assisted review tooling — the ROI calculation will not close and the governance overhead will outweigh the efficiency gains.

Providers to consider

Sources

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