Structured evaluation criteria ensure fair assessment and clear expectations for intern performance.

8.1 Performance Assessment Framework

Multi-Dimensional Rubric Approach

Rather than binary pass/fail judgments, use rubrics with multiple performance levels:

LevelDescription
ExceptionalExceeds all expectations; demonstrates innovation
ProficientMeets all expectations; solid professional work
DevelopingMeets most expectations; areas for growth identified
Needs ImprovementBelow expectations; significant development required

8.2 Evaluation Dimensions

Legal Competencies

  • Quality of legal research and analysis
  • Accuracy in regulatory interpretation
  • Clarity of legal writing
  • Risk identification and assessment
  • Attention to detail and precision

Technical Competencies

  • Understanding of AI/technology concepts
  • Ability to translate between legal and technical domains
  • Comfort with technical documentation
  • Digital tool proficiency

Professional Competencies

  • Communication effectiveness
  • Collaboration and teamwork
  • Initiative and problem-solving
  • Time management and organization
  • Adaptability and learning agility

Business Impact

  • Alignment with organizational objectives
  • Quantifiable outcomes achieved
  • Stakeholder satisfaction
  • Portfolio-ready deliverables created

8.3 Success Metrics

Quantitative Measures

  • Deliverables completed on time
  • Stakeholder feedback scores
  • Compliance gaps identified/addressed
  • Documentation accuracy rates

Qualitative Measures

  • Quality of analysis and recommendations
  • Effectiveness of communication
  • Integration with team dynamics
  • Professional growth demonstrated

Career Outcome Indicators

  • Intern-to-full-time conversion potential
  • Portfolio strength for future applications
  • Network and relationship building
  • Skill development achievement

This is Part 8 of a 10-part series on best practices for designing capstone projects for legal interns at AI companies.