AI Competency
Assessment and Framework
Most AI competency frameworks live on slides. Bryq's is a working measurement instrument, grounded in UNESCO, SFIA, and OECD research, used by HR, TA, and L&D teams to score AI competency against actual roles. Same framework, same scoring, used for hiring and for the workforce you already have.
AI Competency
Assessment and Framework
Most AI competency frameworks live on slides. Bryq's is a working measurement instrument, grounded in UNESCO, SFIA, and OECD research, used by HR, TA, and L&D teams to score AI competency against actual roles. Same framework, same scoring, used for hiring and for the workforce you already have.
AI Competency
Assessment and Framework
Most AI competency frameworks live on slides. Bryq's is a working measurement instrument, grounded in UNESCO, SFIA, and OECD research, used by HR, TA, and L&D teams to score AI competency against actual roles. Same framework, same scoring, used for hiring and for the workforce you already have.
What is an AI competency framework?
What is an AI competency framework?
An AI competency framework is a structured model of the skills, knowledge, and behaviours that constitute capable AI use at work. It is more than a skills checklist. A competency is a skill plus the behaviours and knowledge that allow the skill to be applied effectively in a given role. Frameworks make competencies measurable: you can map a role's required competencies, score a person against them, identify gaps, and design development paths to close those gaps.
Frameworks differ from assessments. The framework describes the structure of capability. The assessment measures a person against it. Bryq publishes both. The five-dimension framework is the structural model; the AI Proficiency Assessment is the measurement instrument.
An AI competency framework is a structured model of the skills, knowledge, and behaviours that constitute capable AI use at work. It is more than a skills checklist. A competency is a skill plus the behaviours and knowledge that allow the skill to be applied effectively in a given role. Frameworks make competencies measurable: you can map a role's required competencies, score a person against them, identify gaps, and design development paths to close those gaps.
Frameworks differ from assessments. The framework describes the structure of capability. The assessment measures a person against it. Bryq publishes both. The five-dimension framework is the structural model; the AI Proficiency Assessment is the measurement instrument.
An AI competency framework is a structured model of the skills, knowledge, and behaviours that constitute capable AI use at work. It is more than a skills checklist. A competency is a skill plus the behaviours and knowledge that allow the skill to be applied effectively in a given role. Frameworks make competencies measurable: you can map a role's required competencies, score a person against them, identify gaps, and design development paths to close those gaps.
Frameworks differ from assessments. The framework describes the structure of capability. The assessment measures a person against it. Bryq publishes both. The five-dimension framework is the structural model; the AI Proficiency Assessment is the measurement instrument.
Three frameworks Bryq's model is grounded in
Three frameworks Bryq's model is grounded in
Bryq's framework integrates published competency research from three sources. We do not claim to have invented the structure. We adapted recognised frameworks for the specific use case of measuring applied AI capability in hiring and workforce contexts.
Bryq's framework integrates published competency research from three sources. We do not claim to have invented the structure. We adapted recognised frameworks for the specific use case of measuring applied AI capability in hiring and workforce contexts.
Bryq's framework integrates published competency research from three sources. We do not claim to have invented the structure. We adapted recognised frameworks for the specific use case of measuring applied AI capability in hiring and workforce contexts.
Framework
Framework
Framework
What it covers
What it covers
What it covers
Where Bryq integrates it
Where Bryq integrates it
Where Bryq integrates it
Foundational AI literacy competencies for teachers and learners across cognitive, behavioural, and ethical domains
Foundational AI literacy competencies for teachers and learners across cognitive, behavioural, and ethical domains
Foundational AI literacy competencies for teachers and learners across cognitive, behavioural, and ethical domains
Informs the Ethical & Responsible Use and Critical Evaluation dimensions
Informs the Ethical & Responsible Use and Critical Evaluation dimensions
Informs the Ethical & Responsible Use and Critical Evaluation dimensions
Industry-standard digital skills framework including AI-related competencies at multiple proficiency levels
Industry-standard digital skills framework including AI-related competencies at multiple proficiency levels
Industry-standard digital skills framework including AI-related competencies at multiple proficiency levels
Informs the level-progression logic and the Workflow Integration dimension
Informs the level-progression logic and the Workflow Integration dimension
Informs the level-progression logic and the Workflow Integration dimension
Cross-country research on AI capability development in the workforce
Cross-country research on AI capability development in the workforce
Cross-country research on AI capability development in the workforce
Informs the cross-role applicability and the longitudinal measurement design
Informs the cross-role applicability and the longitudinal measurement design
Informs the cross-role applicability and the longitudinal measurement design
These three are the primary inputs. Bryq's framework also draws on three additional peer-reviewed research bodies in adjacent fields (industrial-organizational psychology, adult learning theory, and digital workforce research).
These three are the primary inputs. Bryq's framework also draws on three additional peer-reviewed research bodies in adjacent fields (industrial-organizational psychology, adult learning theory, and digital workforce research).
These three are the primary inputs. Bryq's framework also draws on three additional peer-reviewed research bodies in adjacent fields (industrial-organizational psychology, adult learning theory, and digital workforce research).
The five AI competencies Bryq measures
The five AI competencies Bryq measures
Dimension
Dimension
Dimension
What it measures
What it measures
What it measures
AI Task Strategy
What it
measures
AI Task Strategy
When and how to deploy AI in a workflow; recognising the right and wrong moments to use it.
When and how to deploy AI in a workflow; recognising the right and wrong moments to use it.
When and how to deploy AI in a workflow; recognising the right and wrong moments to use it.
Prompting & Interaction
Core
approach
Prompting & Interaction
Effective input design, iteration, and getting useful output from a generative system.
Effective input design, iteration, and getting useful output from a generative system.
Effective input design, iteration, and getting useful output from a generative system.
Critical Evaluation
AI
proficiency
Critical Evaluation
Spotting hallucinations, bias, factual errors, and weak outputs before they reach a decision.
Spotting hallucinations, bias, factual errors, and weak outputs before they reach a decision.
Spotting hallucinations, bias, factual errors, and weak outputs before they reach a decision.
Ethical & Responsible Use
Candidate
experience
Ethical & Responsible Use
Handling sensitive data, transparency to candidates, knowing what to escalate.
Handling sensitive data, transparency to candidates, knowing what to escalate.
Handling sensitive data, transparency to candidates, knowing what to escalate.
Workflow Integration
Candidate
experience
Workflow Integration
Embedding AI into real work without becoming dependent or losing judgement.
Embedding AI into real work without becoming dependent or losing judgement.
Embedding AI into real work without becoming dependent or losing judgement.
Each dimension is scored 0–100. The composite is mapped against a role-specific Ideal Candidate Profile that Bryq's AI builds from the role description. The output is a ranked shortlist with dimension-level insight, not a single opaque score.
Each dimension is scored 0–100. The composite is mapped against a role-specific Ideal Candidate Profile that Bryq's AI builds from the role description. The output is a ranked shortlist with dimension-level insight, not a single opaque score.
Each dimension is scored 0–100. The composite is mapped against a role-specific Ideal Candidate Profile that Bryq's AI builds from the role description. The output is a ranked shortlist with dimension-level insight, not a single opaque score.
How Bryq adapts the assessment to the role
Before running the assessment, you pick the proficiency level the role demands. Bryq then uses scenarios matched to that level. Scoring is always 0 to 100 across the five dimensions, no pass/fail.
Aware
Roles where basic AI awareness is sufficient. Scenarios test whether the candidate can use AI tools for simple tasks, understand their limitations, and avoid common pitfalls.
Functional
Roles where regular AI use is expected. Scenarios test whether the candidate can prompt AI tools effectively, evaluate outputs critically, and integrate AI into standard workflows.
Advanced
Roles requiring sophisticated AI application. Scenarios test whether the candidate can design complex AI workflows and evaluate AI opportunities strategically.
How to apply the framework
How to apply the framework
Hiring
Hiring
Use the assessment as a screening step in your existing ATS workflow. Bryq's AI builds an Ideal Candidate Profile from the role description, specifying the required level per dimension. Candidates complete the 15-minute assessment; the output is a ranked shortlist with dimension-level insight.
Use the assessment as a screening step in your existing ATS workflow. Bryq's AI builds an Ideal Candidate Profile from the role description, specifying the required level per dimension. Candidates complete the 15-minute assessment; the output is a ranked shortlist with dimension-level insight.
Use the assessment as a screening step in your existing ATS workflow. Bryq's AI builds an Ideal Candidate Profile from the role description, specifying the required level per dimension. Candidates complete the 15-minute assessment; the output is a ranked shortlist with dimension-level insight.
L&D programmes
L&D programmes
Use the framework as the backbone of an AI L&D programme. Baseline the workforce on the five dimensions. Identify the dimensions with the widest gap-to-role-required. Design targeted training. Re-baseline to measure progress. The data drives where you spend training budget.
Use the framework as the backbone of an AI L&D programme. Baseline the workforce on the five dimensions. Identify the dimensions with the widest gap-to-role-required. Design targeted training. Re-baseline to measure progress. The data drives where you spend training budget.
Use the framework as the backbone of an AI L&D programme. Baseline the workforce on the five dimensions. Identify the dimensions with the widest gap-to-role-required. Design targeted training. Re-baseline to measure progress. The data drives where you spend training budget.
Workforce capability mapping
Workforce capability mapping
Run the assessment across the workforce and produce a capability map by team or business unit. Identify roles where the dimension-required-vs-dimension-actual gap is largest. Inform strategic workforce planning. Feed into succession planning and internal mobility.
Run the assessment across the workforce and produce a capability map by team or business unit. Identify roles where the dimension-required-vs-dimension-actual gap is largest. Inform strategic workforce planning. Feed into succession planning and internal mobility.
Run the assessment across the workforce and produce a capability map by team or business unit. Identify roles where the dimension-required-vs-dimension-actual gap is largest. Inform strategic workforce planning. Feed into succession planning and internal mobility.
Bryq's framework vs other AI-skills frameworks
Honest cross-reference. Where Bryq's framework aligns with other published frameworks, we say so. Where Bryq adds something the others do not, we say that too.
UNESCO AI Competency Framework, extensive on cognitive and ethical dimensions, lighter on applied workflow integration. Bryq adds the Workflow Integration and AI Task Strategy dimensions for workplace use.
SFIA v9 is strong on level structure and proficiency progression. Bryq adapts the level structure and adds AI-specific behavioural descriptions.
OECD AI capability research, strong on cross-country and longitudinal measurement; less prescriptive on individual-level scoring. Bryq operationalises individual scoring while preserving the cross-role applicability.
LinkedIn AI Aptitude and similar commercial frameworks, proprietary and often focused on skill-counting rather than applied competency. Bryq measures applied capability, not skill inventories.
Implementation guide
Implementation guide
A typical four-phase rollout for a competency-based AI programme:
A typical four-phase rollout for a competency-based AI programme:
A typical four-phase rollout for a competency-based AI programme:
1.
1.
Baseline measurement. Run the assessment across the in-scope population. Establish a current-state capability map.
Baseline measurement. Run the assessment across the in-scope population. Establish a current-state capability map.
Baseline measurement. Run the assessment across the in-scope population. Establish a current-state capability map.
2.
2.
Gap analysis. Identify the dimensions with the largest gap-to-required across the in-scope roles. Prioritise based on business impact.
Gap analysis. Identify the dimensions with the largest gap-to-required across the in-scope roles. Prioritise based on business impact.
Gap analysis. Identify the dimensions with the largest gap-to-required across the in-scope roles. Prioritise based on business impact.
3.
3.
Targeted intervention. Design training, tooling changes, or hiring adjustments to close the priority gaps. Avoid generic AI training; the data tells you what specific dimensions need attention.
Targeted intervention. Design training, tooling changes, or hiring adjustments to close the priority gaps. Avoid generic AI training; the data tells you what specific dimensions need attention.
Targeted intervention. Design training, tooling changes, or hiring adjustments to close the priority gaps. Avoid generic AI training; the data tells you what specific dimensions need attention.
4.
4.
Re-measurement. Run the assessment again after 6–9 months. Measure progress. Adjust the programme.
Re-measurement. Run the assessment again after 6–9 months. Measure progress. Adjust the programme.
Re-measurement. Run the assessment again after 6–9 months. Measure progress. Adjust the programme.
Most teams complete phase 1 in two to four weeks. Phases 2–3 vary widely; phase 4 should be on an annual or biannual cycle.
Most teams complete phase 1 in two to four weeks. Phases 2–3 vary widely; phase 4 should be on an annual or biannual cycle.
Most teams complete phase 1 in two to four weeks. Phases 2–3 vary widely; phase 4 should be on an annual or biannual cycle.
Customer evidence
Major businesses run the framework for capability mapping at infrastructure scale. Other clients use it for government-tech competency baselining. An AI-native customer applies it for L&D programme design. Across the 140+ teams using Bryq globally: 3x improvement in quality of hire, 47% lower attrition, 2x faster hiring.
Results measured across Bryq customer engagements. Individual outcomes vary by role, industry, and baseline hiring maturity.
Get started
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Book a demo to see the assessment and a sample dimension-level output
Book a demo to see the assessment and a sample dimension-level output
Book a demo to see the assessment and a sample dimension-level output
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Talk to a Bryq I/O psychologist on the team if you want a deeper conversation on framework design and validation
Talk to a Bryq I/O psychologist on the team if you want a deeper conversation on framework design and validation
Talk to a Bryq I/O psychologist on the team if you want a deeper conversation on framework design and validation
Ready to Measure AI Proficiency?
Book a 30-minute demo. We’ll build your first AI Proficiency profile on the call, for a role you're hiring or a team you want to assess.
Ready to Measure AI Proficiency?
Start hiring based on
real data.
Ready to Measure AI Proficiency?
Book a 30-minute demo. We’ll build your first AI Proficiency profile on the call, for a role you're hiring or a team you want to assess.
FAQ
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GDPR
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AICPA SOC
CERTIFIED