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Legal · AI Course · LEG-6

Ethical AI Use Under the ABA Model Rules

A rule-by-rule walk through AI in practice — competence, confidentiality, supervision, fees, and communication — with a firm policy you can adopt.

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The Short Answer

AI in practice touches at least six Model Rules, and most firm policies address only confidentiality. ibl.ai supports compliance across all of them by running inside the firm where you own all the code and the data — which resolves the 1.6 analysis and makes the 5.1 and 5.3 supervision duties auditable.

On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network.

The full course design is published below — every module, its objectives and hands-on activity, the capstone, and every source it cites.

What is this course about?

AI touches at least six Model Rules and most firm policies address one. This course works rule by rule: competence under 1.1, confidentiality under 1.6, supervision under 5.1 and 5.3, fees under 1.5, communication under 1.4, and the unauthorized practice question under 5.5 for client-facing agents.

Who is this course for?

  • Ethics and risk counsel
  • Managing partners and general counsel of the firm
  • Practice group leaders
  • Professional responsibility committee members

What do I need before starting?

  • Licensed attorney
  • Familiarity with your jurisdiction's rules

What will I be able to do afterwards?

  • Apply Rule 1.1 competence to AI tool selection and use
  • Apply Rule 1.6 confidentiality to AI deployment architecture
  • Discharge supervisory duties under Rules 5.1 and 5.3
  • Address Rule 1.5 fee reasonableness when AI compresses work
  • Determine Rule 1.4 communication obligations to clients

What does each module cover?

1

What does competence require about AI?

40 min

Rule 1.1 and the technology comment, and what a lawyer must understand before using a tool.

Objectives

  • State the technology competence duty
  • Determine the understanding required before use
  • Distinguish competence from expertise

Topics

Rule 1.1Technology commentRequired understandingCompetence versus expertise

Activity. Assess whether your firm's current AI use meets the competence standard.

2

What does confidentiality require?

45 min

Rule 1.6 and reasonable safeguards, connecting the ethics duty to an architecture decision.

Objectives

  • Apply Rule 1.6 to AI deployment
  • Determine what safeguards are reasonable
  • Connect the duty to architecture

Topics

Rule 1.6Reasonable safeguardsArchitecture implicationsVendor assessment

Activity. Map Rule 1.6 requirements onto a specific deployment architecture.

3

How do you supervise a tool?

45 min

Rules 5.1 and 5.3 extended from people to systems, and what supervision means in practice.

Objectives

  • Apply supervisory duties to AI-assisted work
  • Design supervision that discharges the duty
  • Establish accountability across the firm

Topics

Rules 5.1 and 5.3Supervising systemsPractical supervisionAccountability

Activity. Design the supervision structure for AI-assisted work in one practice group.

4

Can you bill for work AI did in seconds?

45 min

Rule 1.5 fee reasonableness when the efficiency gain is large and the client is paying hourly.

Objectives

  • Apply fee reasonableness to AI-compressed work
  • Determine what may be billed
  • Consider alternative fee structures as the honest response

Topics

Rule 1.5Efficiency and billingValue versus timeAlternative fees

Activity. Work through three billing scenarios where AI compressed the work substantially.

5

Must you tell the client?

40 min

Rule 1.4 communication and the circumstances that make disclosure obligatory rather than optional.

Objectives

  • Determine when disclosure is required
  • Draft client communication about AI use
  • Handle a client who objects

Topics

Rule 1.4Disclosure triggersCommunication draftingClient objection

Activity. Draft the client communication and engagement letter language.

6

Does a client-facing agent practise law?

45 min

Rule 5.5 and the unauthorized practice question when an agent answers a client directly.

Objectives

  • Analyze the unauthorized practice question
  • Set boundaries for client-facing agents
  • Design supervision that addresses the concern

Topics

Rule 5.5Unauthorized practiceClient-facing boundariesSupervision design

Activity. Set the boundary for a client-facing agent and defend it under Rule 5.5.

7

How do you track your jurisdiction's guidance?

35 min

State variation and the ethics opinions that are being issued continuously.

Objectives

  • Identify your jurisdiction's AI-specific guidance
  • Track new opinions systematically
  • Handle multi-jurisdiction practice

Topics

State variationOpinion trackingMulti-jurisdiction practiceUpdate process

Activity. Build a tracking process for AI ethics guidance in your jurisdictions.

8

Drafting the firm policy

50 min

The workshop module: a policy mapped rule by rule and ready for committee.

Objectives

  • Draft a firm AI policy mapped to the rules
  • Cover every rule the course addressed
  • Prepare it for professional responsibility committee review

Topics

Policy draftingRule mappingCommittee preparationAdoption path

Activity. Draft the policy and map every provision to a rule.

What is the capstone project?

Firm AI policy mapped rule by rule

Draft a firm AI policy addressing competence, confidentiality, supervision, fees, client communication, and unauthorized practice, with every provision mapped to a specific rule and a tracking process for jurisdiction guidance.

Deliverable: A firm policy with a rule-by-rule crosswalk ready for professional responsibility committee review.

How are learners assessed?

  • Every rule addressed or explicitly deferred with reasoning
  • Billing scenarios worked through with defensible conclusions
  • Policy reviewed by ethics counsel

What ships with the course?

Facilitator guide

Session-by-session running order, discussion prompts, and the questions that reliably derail a room.

Learner workbook

Exercises, checklists, and the templates each module's activity produces.

Hands-on lab environment

A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.

Assessment bank

Scenario questions and rubric criteria mapped to each stated learning outcome.

Source bibliography

Every primary regulation and standard cited on this page, linked and dated.

Which AI agents does this course use?

The hands-on modules run against agents already deployable on the ibl.ai platform for legal.

Where does the course material come from?

Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.

Delivery notes

Binding guidance for anyone preparing and delivering this course.

  • Module 4 is the module partners resist. Fee reasonableness when AI compresses six hours into one is genuinely uncomfortable, and the course should sit with the discomfort rather than resolving it with a convenient answer.
  • State opinions are being issued continuously and vary meaningfully. Ship Module 7 as a tracking process rather than a list, and localize the whole course per jurisdiction.
  • The course frames analysis and does not give ethics advice. State this explicitly and require ethics counsel review before any firm adopts the policy.
  • Module 6's unauthorized practice analysis is unsettled for client-facing agents. Present the competing positions rather than a conclusion.
  • Coordinate with LEG-1 and LEG-9 — confidentiality is covered in depth in LEG-1 and governance in LEG-9, and this course should reference rather than repeat them.

Why run AI training on a platform you own?

You own the course, not a licence to it

Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.

Model-agnostic delivery

Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.

No per-seat training licences

Usage-based or self-hosted, so cost tracks actual use rather than headcount.

Deploy anywhere

Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.

Frequently asked questions

What does the Ethical AI Use Under the ABA Model Rules course cover?

AI touches at least six Model Rules and most firm policies address one. This course works rule by rule: competence under 1.1, confidentiality under 1.6, supervision under 5.1 and 5.3, fees under 1.5, communication under 1.4, and the unauthorized practice question under 5.5 for client-facing agents. It runs 5 hours across 8 modules across 8 modules, at foundational level, and closes with a capstone: Firm AI policy mapped rule by rule.

Who should take Ethical AI Use Under the ABA Model Rules?

It is written for Ethics and risk counsel, Managing partners and general counsel of the firm, Practice group leaders, Professional responsibility committee members. Prerequisites: Licensed attorney; Familiarity with your jurisdiction's rules.

Can we run this course on our own infrastructure?

Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for legal teams that cannot send work to a public AI tool.

How do we get access to Ethical AI Use Under the ABA Model Rules?

Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.

How much does AI training for legal cost on ibl.ai?

There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.

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Tell us about your cohort and we will set it up — hosted by ibl.ai, or running against your own deployment, where you own all the code and the data.