Personal AI Competency Assessment Model
(PAI-CAM)
(PAI-CAM)
Objective Competency Assessment
Personal Development Roadmap
Education and Resource Management
Increased Technical Capacity and Implementation Capability
Career and Workforce Development
Competitive Advantage
AI Ethics and Regulatory Compliance
Scalability and Innovation Management
Strategic Planning and Decision Making
Stakeholder Collaboration and Ecosystem Participation
AI Knowledge
Technical Skills
Problem Solving and Critical Thinking
Data Literacy and Management
AI Ethics and Responsible AI
Communication and Collaboration
Application and Industry Knowledge
Continuous Learning and Adaptability
Sub-Levels:
At each level, 3 sub-competence levels are defined.
At the lower levels, it is determined in detail which subjects of artificial intelligence need to be known and which technical skills need to be possessed.
In the BYZ-YOM model, a three-stage strategy is followed to objectively determine the level at which the individual is:
1. Self-Assessment
To clarify the individual's perception of his/her own artificial intelligence knowledge and experience, areas of interest and learning needs. (Survey)
2. Theoretical Evaluation (Knowledge/Conceptual Test)
To measure the theoretical knowledge and conceptual infrastructure of the individual. (Exam)
3. Practical Assessment (Project/Practical Test)
To measure the individual's practical application skills , ability to work with data and produce projects.
• Small Project with Real Dataset
• Code Review
• Presentation (Demo)
In the BYZ-YOM model , after determining the level of the individual, a competency development strategy is determined for him/her to reach the next level. In the model, the activities from one level to the next level, the subjects that the individual needs to learn, where they can learn them, the technical skills that they need to acquire and how they can acquire these skills are defined.