Capstone Project Proposal
AI in International Arbitration: A Comparative Analysis of Global Approaches
Intern Information
| Field | Details |
|---|---|
| Name | Isabel Budenz |
| Program | LLM International Commercial Arbitration, University of Stockholm (2025-2026) |
| Background | LLB International and European Law, University of Groningen (2022-2025) |
| Languages | German (Native), Spanish (Native), English (C2), French (B1) |
| Relevant Experience | Legal Researcher, A for Arbitration (2019-2025); Clifford Chance Antitrust Global Virtual Internship |
| Relevant Coursework | Introduction to AI and the EU AI Act; International Commercial Arbitration |
Executive Summary
This project will produce a comprehensive comparative analysis of how AI is being adopted, regulated, and governed in international arbitration across major jurisdictions and arbitral institutions. The deliverables will provide actionable guidance for [Company Name]’s dispute resolution practice and position the organization as a thought leader in this rapidly evolving space.
Problem Statement
The international arbitration landscape is undergoing significant transformation with the introduction of AI tools:
- November 2025: AAA-ICDR launched the first AI-native arbitrator for documents-only construction disputes
- 2025: ICC Commission established a Task Force on AI in arbitration
- Ongoing: Major arbitral institutions (SIAC, LCIA, HKIAC, DIAC) are developing AI policies with varying approaches
However, there is no comprehensive comparative framework that:
- Maps how different institutions are approaching AI adoption
- Analyzes the ethical and procedural implications across jurisdictions
- Provides practical guidance for practitioners navigating this evolving landscape
Business Need: [Company Name] requires clear guidance on AI use in arbitration proceedings to advise clients, manage risk, and identify opportunities for efficiency gains.
Project Objectives
Primary Objectives
- Map the global landscape of AI adoption in international arbitration across 8-10 major arbitral institutions
- Analyze regulatory and ethical frameworks governing AI use in arbitration proceedings
- Identify best practices for AI-assisted case management, document review, and decision support
- Develop practical guidance for [Company Name]’s arbitration practice
Secondary Objectives
- Assess risks and limitations of current AI arbitration tools
- Compare jurisdictional approaches to AI-generated evidence and AI-assisted awards
- Create internal training materials for the dispute resolution team
Scope
In Scope
| Area | Details |
|---|---|
| Institutions | ICC, AAA-ICDR, LCIA, SIAC, HKIAC, DIAC, SCC, VIAC, DIS, CAM |
| Jurisdictions | EU (Germany, France, Spain), UK, USA, Singapore, Hong Kong, UAE |
| AI Applications | Case management, document review, predictive analytics, arbitrator selection, AI arbitrators |
| Legal Issues | Due process, transparency, confidentiality, enforceability, liability |
Out of Scope
- Technical implementation of AI tools
- Domestic litigation and court proceedings
- Mediation and other ADR mechanisms (except where integrated with arbitration)
- Detailed analysis of specific AI vendor products
Deliverables
| # | Deliverable | Description | Format | Due |
|---|---|---|---|---|
| 1 | Institutional Landscape Report | Comparative analysis of AI policies and practices across 10 arbitral institutions | PDF Report (25-30 pages) | Week 4 |
| 2 | Jurisdictional Analysis Memo | Legal analysis of AI in arbitration across key jurisdictions (leveraging multilingual research) | Legal Memo (15-20 pages) | Week 6 |
| 3 | Best Practices Guide | Practical guidance for using AI in arbitration proceedings | Handbook (20-25 pages) | Week 8 |
| 4 | Risk Assessment Matrix | Framework for evaluating AI tools for arbitration use | Excel/Interactive Tool | Week 8 |
| 5 | Executive Presentation | Summary findings and recommendations for leadership | PowerPoint (20 slides) | Week 9 |
| 6 | Training Module | Internal training materials for dispute resolution team | Slide deck + facilitator guide | Week 10 |
Methodology
Phase 1: Research Foundation (Weeks 1-2)
Week 1: Institutional Research
- Collect and analyze official AI policies, guidelines, and announcements from target institutions
- Review institutional rules for AI-relevant provisions
- Identify key contacts and published commentary from institution leadership
Week 2: Literature Review
- Academic literature on AI in arbitration
- Industry surveys (White & Case 2025 International Arbitration Survey)
- Legal commentary and practitioner perspectives
- News and developments tracking
Phase 2: Comparative Analysis (Weeks 3-6)
Week 3-4: Institutional Comparison
- Develop comparison framework (adoption level, permitted uses, restrictions, governance)
- Complete institutional landscape report
- Create visual mapping of global approaches
Week 5-6: Jurisdictional Deep Dive
- Analyze legal frameworks in target jurisdictions
- Leverage multilingual capabilities for primary source research:
- German: DIS rules, German arbitration law commentary
- Spanish: Spanish Arbitration Act, Latin American perspectives
- French: ICC materials, French arbitration doctrine
- English: Common law jurisdictions, international materials
- Assess enforceability considerations for AI-assisted awards
Phase 3: Practical Guidance Development (Weeks 7-8)
Week 7: Best Practices Synthesis
- Distill findings into actionable guidance
- Develop decision frameworks for AI tool adoption
- Create risk assessment methodology
Week 8: Tool Development
- Build risk assessment matrix
- Draft best practices handbook
- Internal review and refinement
Phase 4: Knowledge Transfer (Weeks 9-10)
Week 9: Leadership Presentation
- Prepare executive summary presentation
- Present findings to dispute resolution leadership
- Incorporate feedback
Week 10: Training Development
- Develop training module for wider team
- Create facilitator guide
- Deliver pilot training session
Timeline
Week 1 ████████░░░░░░░░░░░░ Research: Institutional policies
Week 2 ████████░░░░░░░░░░░░ Research: Literature review
Week 3 ░░░░████████░░░░░░░░ Analysis: Institutional comparison
Week 4 ░░░░████████░░░░░░░░ Deliverable: Institutional Landscape Report
Week 5 ░░░░░░░░████████░░░░ Analysis: Jurisdictional deep dive
Week 6 ░░░░░░░░████████░░░░ Deliverable: Jurisdictional Analysis Memo
Week 7 ░░░░░░░░░░░░████████ Synthesis: Best practices development
Week 8 ░░░░░░░░░░░░████████ Deliverables: Guide + Risk Matrix
Week 9 ░░░░░░░░░░░░░░░░████ Presentation: Executive briefing
Week 10 ░░░░░░░░░░░░░░░░████ Training: Module delivery
Key Milestones
| Week | Milestone | Checkpoint |
|---|---|---|
| 2 | Research complete | Mentor review of research plan |
| 4 | Institutional report delivered | Stakeholder feedback session |
| 6 | Jurisdictional memo delivered | Legal team review |
| 8 | Best practices guide complete | Quality assurance review |
| 10 | Project complete | Final presentation and handoff |
Resources Required
Access
- Westlaw/LexisNexis for legal research
- Arbitration institution databases and rules
- Academic journal access (Kluwer Arbitration, etc.)
- Internal matter management system (for context on current arbitration matters)
Tools
- Microsoft Office Suite (Word, Excel, PowerPoint)
- Reference management software (Zotero or equivalent)
- Collaboration platform (Teams/Slack)
- Document sharing (SharePoint/Google Drive)
Subject Matter Expert Support
| Role | Purpose | Estimated Time |
|---|---|---|
| Primary Mentor | Weekly guidance, deliverable review | 2 hrs/week |
| Arbitration Partner | Strategic input, quality review | 2 hrs total |
| Technology Counsel | AI legal issues consultation | 3 hrs total |
| Knowledge Management | Training module development | 2 hrs total |
Budget
| Item | Estimated Cost |
|---|---|
| Research database access | Existing subscription |
| Conference/webinar attendance | $500 |
| Printing/materials | $100 |
| Total | $600 |
Success Criteria
Deliverable Quality
- All 6 deliverables completed on time
- Institutional report covers minimum 8 institutions comprehensively
- Jurisdictional memo includes analysis in 4+ languages (primary sources)
- Best practices guide approved by arbitration practice leadership
- Risk matrix validated by technology counsel
Business Impact
- Guidance adopted by dispute resolution practice
- Training delivered to minimum 10 team members
- At least 2 client-facing applications of research identified
- Positive stakeholder feedback (>4/5 satisfaction rating)
Professional Development
- Demonstrated ability to translate technical AI concepts to legal frameworks
- Enhanced comparative law research skills across multiple jurisdictions
- Established relationships with dispute resolution team members
- Portfolio-ready deliverables for future career applications
Risks and Mitigation
| Risk | Likelihood | Impact | Mitigation |
|---|---|---|---|
| Rapid regulatory changes during project | Medium | Medium | Build in flexibility for updates; establish news monitoring protocol |
| Limited public information from some institutions | Medium | Low | Supplement with practitioner interviews and secondary sources |
| Scope creep from stakeholder requests | Medium | High | Clear scope boundaries; change request process with mentor approval |
| Language/translation complexity | Low | Medium | Prioritize key documents; leverage native fluency strategically |
| Technical AI concepts beyond legal expertise | Low | Medium | SME consultation scheduled; focus on legal/governance aspects |
Stakeholders
| Stakeholder | Role | Engagement |
|---|---|---|
| [Mentor Name] | Primary mentor, day-to-day guidance | Weekly 1:1 meetings |
| [Partner Name] | Executive sponsor, strategic direction | Bi-weekly check-ins |
| Dispute Resolution Team | End users of deliverables | Feedback sessions at Weeks 4, 8 |
| Technology/Innovation Team | AI expertise, tool evaluation | Ad hoc consultation |
| Knowledge Management | Training deployment | Weeks 9-10 collaboration |
Communication Plan
| Cadence | Format | Participants | Purpose |
|---|---|---|---|
| Daily | Async updates (Slack/Teams) | Mentor | Progress, blockers |
| Weekly | 30-min 1:1 | Mentor | Detailed review, guidance |
| Bi-weekly | 30-min check-in | Executive sponsor | Strategic alignment |
| Week 4, 8 | Feedback sessions | Stakeholder group | Deliverable review |
| Week 10 | Final presentation | Leadership team | Project completion |
Value Proposition
For [Company Name]
- Competitive advantage: First-mover guidance on AI in arbitration
- Risk management: Framework for evaluating AI tools before adoption
- Client value: Ability to advise clients on AI implications in disputes
- Thought leadership: Potential for external publication/presentation
For Isabel Budenz
- Specialization: Establishes expertise at intersection of arbitration and AI
- Portfolio: Six substantial deliverables demonstrating hybrid legal-tech skills
- Network: Relationships with arbitration practitioners and AI specialists
- Career positioning: Differentiated profile in emerging practice area
Post-Project Sustainability
Knowledge Maintenance
- Quarterly update protocol for institutional policy changes
- Designated owner for ongoing guidance maintenance
- Integration with firm’s arbitration practice resources
Potential Extensions
- External publication (article or client alert)
- Conference presentation (ICCA, IBA, or regional arbitration events)
- Development of AI tool evaluation service for clients
- Expansion to include AI in mediation and other ADR
Appendix: Preliminary Research Sources
Institutional Sources
- ICC Commission Report on AI in Arbitration (forthcoming 2026)
- AAA-ICDR AI Arbitrator Program Documentation
- SIAC Guidelines on AI Use in Arbitration
- LCIA Notes on Technology in Arbitration
- Silicon Valley Arbitration & Mediation Center Guidelines
Academic and Industry Sources
- White & Case 2025 International Arbitration Survey
- Kluwer Arbitration Blog - AI coverage
- Journal of International Arbitration - AI articles
- Global Arbitration Review - technology coverage
- Queen Mary University International Arbitration Survey
Regulatory Sources
- EU AI Act - implications for arbitration
- UNCITRAL Technical Notes on ODR
- New York Convention - enforcement considerations
- National arbitration laws (Germany, France, Spain, UK, Singapore, USA)
Approval
Intern Acknowledgment
I have reviewed this proposal and commit to delivering the outlined project within the specified timeline and quality standards.
Intern Signature: _________ Date: _____
Isabel Budenz
Mentor Approval
I approve this project proposal and commit to providing the mentorship and resources outlined.
Mentor Signature: _________ Date: _____
[Mentor Name], [Title]
Executive Sponsor Approval
I approve this project and confirm alignment with organizational objectives.
Sponsor Signature: _________ Date: _____
[Partner Name], [Title]
| *Proposal Version 1.0 | Prepared January 2026* |