Research & Benchmarking Policy

Effective Date: 16 July 2026

1. Purpose

AIQScore™ is committed to advancing AI literacy, workforce readiness, education, and responsible AI adoption through evidence-based research and benchmarking.

This Research & Benchmarking Policy explains how AIQScore™ may use anonymized and aggregated assessment data to generate research insights, industry benchmarks, statistical reports, and AI readiness indices while protecting the privacy and confidentiality of individuals and organizations.

Our objective is to contribute to better decision-making by learners, employers, educational institutions, governments, policymakers, and industry through trusted AI capability intelligence.

2. Scope

This Policy applies to data collected through:

  • AIQScore™ assessments
  • AIQ8™ competency evaluations
  • AI readiness assessments
  • Enterprise benchmarking
  • Institutional benchmarking
  • AI certification programs
  • Learning pathways
  • Research surveys conducted by AIQScore™

3. Types of Data Used for Research

AIQScore™ may use the following categories of information for research and benchmarking:

Assessment Metrics

  • AI Quotient (AIQ)
  • AI Literacy Score (ALS)
  • AI Application Score (AAS)
  • AI Governance Score (AGS)
  • AIQ8™ competency level
  • Assessment completion statistics
  • Domain-specific competency scores
  • Learning progress indicators

Demographic Categories

Where appropriate and lawful, we may analyze broad demographic information such as:

  • Age group
  • Educational level
  • Industry sector
  • Job function
  • Career stage
  • Geographic region (city, state, country)
  • Organization size
  • Institution category

This information is analyzed only at an aggregated level.

Usage Metrics

We may also analyze:

  • Assessment participation trends
  • Completion rates
  • Learning pathway engagement
  • Certification adoption
  • Platform usage statistics
  • Skill demand trends

4. Anonymization

Protecting user privacy is fundamental.

Before research or benchmarking activities are conducted, AIQScore™ removes or transforms personal identifiers wherever appropriate.

Research datasets are designed to avoid direct identification of individual participants.

Examples of information excluded from research datasets include:

  • Name
  • Email address
  • Phone number
  • Government identification numbers
  • Exact residential address
  • Payment information

5. Aggregated Benchmarking

AIQScore™ may publish aggregated benchmarking reports, including but not limited to:

  • National AI Readiness Index
  • State AI Readiness Rankings
  • Industry AI Benchmark Reports
  • Enterprise AI Readiness Reports
  • Workforce AI Skills Reports
  • University AI Readiness Rankings
  • School AI Benchmark Reports
  • Sector-specific AI adoption studies
  • AI Skills Gap Reports
  • AI Talent Landscape Reports

These reports are intended to provide insights into AI capability trends and are based on aggregated data.

6. Research Objectives

Assessment data may be used to:

  • Improve AIQScore™ methodologies
  • Enhance assessment quality
  • Validate competency frameworks
  • Identify emerging AI skills
  • Measure workforce readiness
  • Support education policy research
  • Develop industry benchmarks
  • Improve AI learning pathways
  • Identify national and regional AI capability trends
  • Advance responsible AI research

7. AIQScore™ Research Publications

AIQScore™ may publish:

  • White papers
  • Annual AI Readiness Reports
  • Benchmarking reports
  • Academic research
  • Industry insights
  • Policy papers
  • Statistical dashboards
  • Educational research
  • Workforce trend reports

These publications will generally present aggregated findings rather than individual-level information.

8. Enterprise & Institutional Benchmarking

Organizations participating in AIQScore™ benchmarking programs may receive customized reports comparing their performance against peer groups.

Such reports may include:

  • AI readiness maturity
  • Competency distribution
  • Departmental performance
  • Skill gaps
  • Benchmark percentile
  • Learning recommendations

Comparative insights are designed to preserve the confidentiality of participating organizations.

9. Academic & Research Collaboration

AIQScore™ may collaborate with:

  • Universities
  • Research institutions
  • Think tanks
  • Industry associations
  • Government agencies
  • International organizations

Where such collaborations involve data analysis, AIQScore™ will take appropriate measures to safeguard privacy and comply with applicable laws and contractual obligations.

10. Public Reports

Publicly released research reports may include:

  • National averages
  • Industry averages
  • Regional trends
  • Statistical summaries
  • Benchmark distributions
  • Longitudinal trend analysis

Individual assessment records are not intended to be published.

11. Responsible AI Research

Research activities conducted by AIQScore™ are guided by our Responsible AI Principles, including commitments to:

  • Fairness
  • Transparency
  • Privacy
  • Security
  • Accountability
  • Human oversight
  • Ethical use of AI

We strive to ensure that research outputs are evidence-based and presented responsibly.

12. User Privacy

AIQScore™ does not sell personal assessment data.

Personal information is processed in accordance with our Privacy Policy and applicable data protection laws.

Where consent is required under applicable law for specific research activities, it will be obtained before such processing.

13. Data Security

Research datasets are protected through appropriate administrative, technical, and organizational safeguards, including:

  • Access controls
  • Encryption where appropriate
  • Secure storage
  • Monitoring and logging
  • Periodic security reviews

Only authorized personnel and approved research partners may access research datasets as necessary.

14. User Rights

Subject to applicable law, users may:

  • Request access to their personal information.
  • Request correction of inaccurate personal information.
  • Request deletion of eligible personal information.
  • Object to certain processing activities where permitted by law.
  • Contact AIQScore™ regarding privacy or research-related questions.

Requests may be submitted to:

Email: pankaj@aiqscore.org

15. Policy Updates

AIQScore™ may update this Policy periodically to reflect changes in technology, research practices, legal requirements, or business operations.

The latest version will always be published on www.aiqscore.org.

AIQScore™ Research Governance Framework

Research PrincipleOur Commitment
Privacy by DesignProtect personal information through appropriate technical and organizational measures.
Anonymization & AggregationUse anonymized or aggregated data for research and benchmarking wherever appropriate.
TransparencyClearly explain how research and benchmarking data is used.
Scientific IntegrityBase reports on objective, evidence-based methodologies.
Fair BenchmarkingUse consistent benchmarking criteria and avoid misleading comparisons.
Responsible AIApply ethical AI practices when generating insights and reports.
Continuous ImprovementUse research findings to enhance assessments, methodologies, and AIQScore™ services.

Contact

Research & Benchmarking Office
AIQScore™

Email: pankaj@aiqscore.org

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