Identifying and Developing AI Skill Competencies
Description
Identifying and developing AI skill competencies ensures your organization can define, measure, and build the capabilities needed to scale GenAI effectively. This capability focuses on creating a role-specific AI competency framework that guides hiring, development, and performance expectations across the enterprise.
Why it's Important
GenAI adoption touches nearly every function, yet most organizations lack a clear view of what “good” looks like for GenAI-related roles. Without defined competencies, it’s difficult to evaluate candidates, support upskilling, or align performance goals with GenAI priorities. A robust competency model ensures that individuals understand the expectations tied to their roles and can build skills with purpose. It also allows leaders to identify gaps, prioritize development efforts, and scale GenAI capabilities with consistency and confidence.
Why it's Challenging @ Scale
- Lack of Shared Definitions for AI Competencies: Without a clear, enterprise-wide model, teams interpret AI capabilities differently-leading to misalignment.
- Inconsistent Role Expectations Across Functions: Varying definitions for skills like data literacy, prompt engineering, or risk mitigation cause confusion and uneven enablement.
- Difficulty Measuring Competency Maturity: Organizations often lack tools to assess how well individuals meet defined expectations, especially for non-technical roles.
- Rapid Evolution of Required Skills: The competencies that matter today may be outdated tomorrow-requiring constant revision.
- Disconnect Between Competencies and Development Paths: Without integration into learning journeys, certification, or performance management, competency models become shelfware.
Complexity
High: Maturing this capability requires coordination between HR, learning, and functional leaders, along with ongoing iteration to reflect changing GenAI priorities.
Taking Action
Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.
Exploring 
Experimenting
Exploring Experimenting - Explore Key Concepts & Best Practices: Complete the Enterprise GenAI Talent Best Practices workshop (2 hrs.) to understand foundational key concepts and explore applied best practices.
Click here to review Specific Areas of Focus
- Identifying skills and capabilities needed for GenAI success.
- Defining GenAI-specific roles and responsibilities.
- Planning onboarding and upskilling programs.
- Evaluating current talent gaps and readiness.
- Building talent strategies aligned with GenAI roadmap.
- Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy.
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- Align on your Current State and define your Target State.
- Create an actionable enablement plan.
- Define target timeline and measures of success.
- Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame.
Click here to review Specific Areas of Focus
- Draft Initial GenAI Competency Clusters: Define foundational, role-specific skill areas (e.g., data fluency, AI ethics, tool usage).
- Test with a Focus Group: Share early versions with a cross-functional pilot group and gather actionable feedback.
- Map Competencies to One or Two Priority Roles: Create full competency definitions for 1-2 high-impact GenAI roles to prove value and test applicability.
Experimenting 
Lifting-Off
Experimenting Lifting-Off - Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
Click here to review Specific Areas of Focus
- AI Awareness & Literacy Enablement Best Practices
- Defining Your AI Job Family
- Role-Based GenAI Skill Acceleration Best Practices
- GenAI Talent Management (Brand, Recruiting, Retention, Performance Management, & 3rd Party Management) Best Practices
- Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale
Click here to review Specific Areas of Focus
- Assess Your Proposed Solution or Process: Validate your GenAI competency framework with business and HR leaders for accuracy and usability.
- Define in-scope Processes and Guardrails: Determine which roles require competency definitions and how those will tie into HR systems.
- Close any Data or Measurement Gaps: Establish methods to assess competency proficiency and track development progress over time.
- Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units
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- Define Your Phased Implementation Plan: Prioritize rollout based on role criticality and readiness across the organization.
- Build Awareness and Finalize Enablers: Provide managers with guides to apply competencies in hiring, performance, and development.
- Operationalize Your Comms Plan: Ensure internal alignment through clear messaging about the purpose and use of the competency framework.
Lifting-Off 
Accelerating
Lifting-Off Accelerating - Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases
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- Publish a GenAI Competency Framework Handbook: Clearly define each competency, expected behaviors, and level-specific descriptors.
- Integrate Competencies into Core Talent Processes: Embed definitions into hiring rubrics, development plans, and performance reviews.
- Establish Governance for Ongoing Updates: Assign ownership for refreshing competencies as GenAI technologies evolve.
- Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers
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- Expand Role Coverage Across Functions: Scale competency definitions across business, technical, and support roles involved in GenAI.
- Build a Competency-Driven Enablement Ecosystem: Align learning journeys, certifications, and coaching programs to defined skills.
- Create Cross-Functional Competency Champions: Train managers and team leads to reinforce expectations and skill growth.
- Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum
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- Spotlight Teams Applying the Framework Successfully: Share internal stories of how competency models improved hiring or learning.
- Recognize Individual Growth Through Competency Mastery: Highlight employees demonstrating strong GenAI skill advancement.
- Tie Recognition to Development Milestones: Use certifications or skills badges to reinforce achievement and motivate continued learning.
Accelerating 
Breaking-Away
Accelerating Breaking-Away - Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine
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- Link Competency Frameworks to Career Architecture: Integrate GenAI competencies into enterprise role structures and growth ladders.
- Use Competency Models in Strategic Workforce Planning: Align role expectations with future needs, demand forecasting, and hiring plans.
- Build GenAI Fluency into Enterprise Learning Portals: Surface relevant content and assessments based on individual competency profiles.
- Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort
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- Automate Skills Assessment and Progress Tracking: Use AI-based tools to gauge current state and monitor improvement over time.
- Recommend Learning Based on Competency Gaps: Deliver personalized learning paths tied to observed or self-reported skill gaps.
- Integrate Competency Signals into Talent Systems: Use data to inform recruiting, succession planning, and internal mobility decisions.
- Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases
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- Update Competency Models Based on Emerging Capabilities: Continuously refine definitions to reflect new technologies and job demands.
- Expand to Cover Partner and Ecosystem Roles: Define expectations for external talent contributing to your GenAI success.
- Benchmark Competency Maturity Against Market Leaders: Use internal and external data to assess competitive advantage and identify gaps.
Key "Watchouts"
- Overcomplicating the Framework: Too many competencies, levels, or jargon can make the model hard to apply and sustain.
- Leaving Out Non-Technical Roles: AI competency isn’t just for engineers-business, legal, design, and ops teams also need clarity.
- Failing to Tie Competencies to Action: Without linkage to performance, development, or hiring, the framework won’t drive behavior change.
- Ignoring the Feedback Loop: Teams may quickly outgrow the initial model-without updates, it becomes obsolete.
- Treating It as an HR-Only Initiative: True adoption requires business ownership and relevance to day-to-day work.
Targeted Benefits
- Clear Expectations for GenAI-Enabled Roles: Teams know what good looks like and how to achieve it.
- Faster, More Targeted Development: Learning and enablement programs are aligned with role-specific skill needs.
- Improved Hiring and Talent Mobility: Competency definitions support better interviews, onboarding, and internal movement.
- Stronger Performance Alignment: Goals and reviews reflect actual expectations for GenAI maturity and impact.
- Strategic Workforce Readiness: Leaders can better identify skill gaps, forecast needs, and scale responsibly.
Looking to Move Faster, and 'Go Bigger'?
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