Assessment Transparency & Methodology Statement
Workforce AI Impact Snapshot — Organizational Assessment Product. Version 1.0 · August 2026 · https://realistikaid.com
Purpose of This Statement
This statement is published in the interest of transparency and to support informed decision-making by organizations, consultants, and individuals considering use of the Workforce AI Impact Snapshot. It is structured to address the five criteria for high-quality evaluation reporting identified in emerging Canadian and international AI governance guidance — specifically the principle that evaluators should provide enough information for results to be understood, trusted, and used responsibly.
Realistik AI Dynamics was built on the principle that independence, transparency, and honest limitation-reporting are not optional features of a good assessment tool — they are the foundation of one. This document reflects that commitment.
Executive Summary
The table below summarizes how the Workforce AI Impact Snapshot addresses each of the five criteria. Each criterion heading is followed by one or two plain-language sentences. Full detail follows in the body of the document.
Criterion 1 — Intent and Context of Use
The Snapshot has one purpose — to give organizations an anonymous, aggregate picture of their workforce’s AI reality at a task level, as a starting point for planning. It does not assess individuals, recommend tools, or produce compliance ratings. Realistik AI Dynamics has no commercial relationship with any AI vendor.
Criterion 2 — Methodology and Metrics
Employees self-assess their own daily tasks across three independently scored dimensions: AI task exposure, human strengths, and adaptability including tech readiness. Scores are aggregated anonymously. Sample data is drawn from real beta assessments; fictional sample organizations are always clearly labeled as such.
Criterion 3 — Instrument Specification
The assessment is a structured self-report instrument (V3.5) covering three dimensions. It assesses human workers and their tasks, not AI systems. Report generation uses a version-controlled analytical prompt applied consistently to every dataset.
Criterion 4 — Uncertainty and Limitations
Six specific limitations are disclosed, including the self-report nature of the instrument, the characteristics of the beta dataset, the approximate nature of exposure figures, organization size constraints, the time-bound nature of the assessment, and the absence to date of formal predictive validity studies. The lack of such validity studies is not unusual at an early stage of development and in no way diminishes the value of the assessment as a practical planning tool.
Criterion 5 — Selective Disclosure and Privacy
Individual reports go directly to employees and are never seen by the employer. Employers receive only anonymous aggregate data. Single-person roles are protected by grouping. No data is sold or shared with any third party.
A full explanation of each criterion follows below.
Criterion 1 of 5
Intent and Context of Use
Clearly stating the intent of the evaluation and the context(s) of use it is meant to inform.
The Workforce AI Impact Snapshot has one clearly defined purpose: to provide an organization with an anonymous, aggregate picture of where artificial intelligence realistically affects their workforce at a task level — so that leadership can make informed decisions about AI readiness, training, and strategy before committing resources.
The Snapshot is designed to be a starting point, not a conclusion. It does not:
- predict career outcomes
- recommend specific tools or training programs
- assess individual employee performance
- produce a compliance rating or certification
Its appropriate context of use is organizational planning — informing a CAO’s briefing to council, supporting a consultant’s engagement with a client, or helping leadership understand where to look first before making AI-related decisions.
The Snapshot is explicitly not appropriate as a basis for individual staffing decisions, performance management, or restructuring. This limitation is stated in every report delivered.
Realistik AI Dynamics has no commercial relationship with any AI tool, training program, or technology vendor. The Snapshot exists as a standalone product with no follow-on sale, no referral arrangement with vendors, and no financial incentive that could shape the direction of findings. This independence is structural, not incidental.
“We collect and summarize. You decide.” — This principle governs every aspect of how the Snapshot is designed, delivered, and described.
Criterion 2 of 5
Methodology, Metrics, and Evaluation Protocol
Transparently documenting the methodology, including metrics, datasets, and evaluation protocols.
Assessment Instrument
Each employee completes a structured self-assessment of their own daily work tasks. The instrument is delivered as a private digital form and takes approximately 5–7 minutes to complete. Participation is voluntary at the individual level.
The assessment is task-based, not title-based. Questions ask respondents about the specific activities they perform — not their job classification, seniority, or their employer’s expectations. This reflects the core methodology: AI affects tasks within jobs, not whole jobs. Two people with identical titles may have substantially different exposure profiles depending on what they actually do each day.
Three Independently Scored Dimensions
The assessment produces scores across three dimensions. These are always reported separately and never combined into a single composite score. Combining them would obscure the independent information each dimension carries.
1. AI Task Exposure
Measures the realistic degree to which a respondent’s daily tasks are currently or likely to be affected by AI tools. Scored across task categories on a 1–5 scale reflecting the degree of AI involvement in each task type. Total scores are summed and converted to an approximate percentage exposure band: Lower (under 25%), Moderate (25–49%), and Elevated (50%+). Percentage figures represent approximate midpoints within scoring bands and should be interpreted as indicative ranges, not precise measurements.
2. Human Strengths
Measures workplace execution capabilities that AI does not replicate: judgment, communication, coordination, adaptability, technology comfort, and leadership responsibility. Each category is scored 1–5 based on respondent self-assessment. Scores are reported as distribution profiles across the workforce aggregate and never as individual ratings.
3. Adaptability and Tech Readiness
Measures the respondent’s self-assessed readiness to respond to change and their current comfort with technology. Tech comfort is scored and reported separately within this dimension because it moves independently of general adaptability and has distinct practical implications for workforce planning. Scored 1–5 per category.
Aggregate Calculation and Reporting
Individual scores are aggregated across all respondents. The team average task exposure figure is calculated as the arithmetic mean of each respondent’s approximate exposure midpoint. Distribution bars show how many employees fall into each scoring band across the three dimensions. These are reported as firm counts (e.g., 7 of 11) rather than percentages to avoid false precision in small organizations.
Intersection analysis — examining combinations across dimensions (e.g., elevated exposure with moderate tech comfort) — is included in the Practical Considerations section. These intersections are the most actionable findings in the report and reflect patterns in the aggregate data, not assessments of named individuals.
Basis in Beta Assessment Data
Sample reports and illustrative figures published by Realistik AI Dynamics are drawn from real, anonymized beta assessments completed by actual workers across a range of occupations and sectors during product development. Where sample organizations are fictional (such as the District of Cedar Hollow), this is stated explicitly and prominently. The beta dataset currently reflects a self-selected group of early participants and skews toward higher technology comfort than a general workforce population. This limitation is disclosed in Criterion 4.
Criterion 3 of 5
Assessment Instrument Specification
Specifying the model or system configurations being tested.
This criterion, as formulated in AI model evaluation guidance, refers to the specification of AI systems under test. The Workforce AI Impact Snapshot is a workforce assessment instrument, not an AI model evaluation tool — it assesses human workers and their work tasks, not the performance or configuration of AI systems. The criterion is addressed here in the analogous sense applicable to workforce assessment:
- The assessment instrument is a structured self-report survey administered digitally. The current version (V3.5) covers AI task exposure across defined task categories, workplace execution strengths across six categories, and adaptability including a specific tech comfort dimension.
- The instrument was developed iteratively through beta testing with real workers across multiple occupations and refined through multiple versions. The current version reflects those refinements.
- Report generation uses a structured analytical prompt applied consistently to each dataset. The prompt architecture is version-controlled and material changes will be reflected in updated version documentation.
- The assessment does not use or evaluate any specific AI tool, model, or vendor product. Its findings reflect respondents’ self-reported experience of their own work tasks.
Criterion 4 of 5
Uncertainty, Limitations, and Potential Sources of Error
Reporting uncertainty, limitations, and potential sources of error to support appropriate interpretation.
Realistik AI Dynamics regards honest limitation reporting as a core obligation. The following limitations apply to all Workforce AI Impact Snapshot assessments and should be understood by anyone using or commissioning a report.
1. Self-report methodology
The assessment is based on each respondent’s self-assessment of their own daily tasks. Results reflect individual perception and may differ from an external observer’s analysis of the same role. Respondents may underestimate or overestimate the AI relevance of their tasks based on their current knowledge of AI capabilities.
2. Beta data characteristics
Illustrative figures and sample reports draw on a beta dataset of early-adopter participants. This population skews toward higher technology comfort and AI awareness than a general workforce population — because our beta assessment submissions happened to have a higher level of tech comfort than would be expected across a typical workforce. A broader dataset will likely produce a lesser skew depending on the data submitted. Organizations should not expect their own results to mirror published samples, particularly on adaptability and tech readiness dimensions.
3. Exposure figures are approximate ranges
Task exposure percentages represent approximate midpoints within scoring bands, not precise measurements. They should be interpreted as directional indicators (lower, moderate, elevated) rather than precise quantitative predictions.
4. Organization size constraints
In organizations with very small teams (fewer than ten staff), aggregate distributions may be less meaningful due to sample size. Single-person roles may be difficult to protect from indirect identification even in aggregate. The Snapshot applies additional protections in these cases (see Criterion 5), but very small samples limit statistical interpretation.
5. Snapshot in time
The assessment reflects the state of AI capabilities and the respondent’s task profile at the time of completion. AI capabilities are evolving rapidly. A Snapshot completed today reflects today’s landscape and should be revisited as circumstances change. Realistik AI Dynamics recommends reassessment when significant AI tool deployments occur or when organizational roles change substantially.
6. No predictive validity testing
The Snapshot has not been subject to formal predictive validity studies — longitudinal research comparing assessment findings to actual workforce outcomes over time. This is not unusual for a product in early development and does not diminish the value of the assessment as a practical planning tool. It is grounded in established workforce assessment principles and refined through beta testing. Formal validation studies are an expected next step as the dataset and client base grows.
Criterion 5 of 5
Selective Disclosure and Privacy Protection
Practicing selective disclosure — withholding sensitive details where sharing them could enable misuse, compromise safety, or undermine evaluation validity.
The privacy architecture of the Workforce AI Impact Snapshot is structural, not policy-based. It is built into the design of the product, not added as a statement of intent.
1. Individual reports are always private
Each employee’s individual assessment responses and personal report are delivered directly to that employee. They are never shared with the organization, the employer, or any third party. This is an unconditional protection with no exception.
2. Employers receive aggregate data only
The Workforce AI Impact Snapshot received by an organization contains only anonymous, aggregate information — distribution profiles, intersection analyses, and practical considerations derived from the full dataset. No individual’s data, score, or response is included.
3. Single-person role protection
In live organizational reports, any role held by only one person is grouped into a broader functional cluster rather than reported individually. This prevents indirect identification of individuals through role-specific data, regardless of organization size.
4. Minimum participation threshold
Realistik AI Dynamics will not generate an organizational Snapshot from a dataset so small that meaningful anonymization cannot be achieved. The specific threshold is applied case by case based on organizational size and role distribution.
5. No data sold or shared
Assessment data is not sold, shared with third parties, used for advertising, or provided to AI vendors, training companies, or technology providers. The independence of Realistik AI Dynamics — with no commercial relationships with AI product or service vendors — means there is no incentive to share data with such parties.
6. Prompt architecture confidentiality
The specific technical configuration of the report generation system is not publicly disclosed. This is consistent with standard practice for assessment instruments where disclosure of the full scoring logic could enable gaming of the assessment. The methodology described in Criterion 2 provides sufficient information for results to be understood and trusted without requiring disclosure of the complete technical specification.
Alignment with Canadian AI Governance Guidance
This statement is structured to address the five criteria for high-quality evaluation reporting identified in Canadian AI governance documentation, including the AI Strategy for the Federal Public Service 2025–2027 and related guidance on responsible AI assessment and transparency.
Realistik AI Dynamics is a private, independent product. It is not affiliated with, endorsed by, or contracted to any government body. The alignment described here reflects the design principles of the product, which were developed independently and are consistent with emerging governance best practice — because both are grounded in the same underlying values: transparency, honesty about limitations, privacy protection, and the primacy of informed human decision-making.
Organizations, consultants, and individuals who would like to discuss this statement or request additional information are welcome to contact Realistik AI Dynamics directly through https://realistikaid.com.
Assess first. Understand fully. Decide with confidence.
Donald DeGagne is a retired City Manager with 32 years in local government administration in British Columbia, Canada. He is the founder and developer of Realistik AI Dynamics. He lives in Playa del Coco, Guanacaste, Costa Rica. Contact and further information: https://realistikaid.com