How employee input becomes
an organizational picture.
The Workforce AI Impact Snapshot combines private employee input, defined analytical rules, AI-supported analysis and experienced human judgment.
Start with the work people actually do.
Participating employees provide structured information about their tasks, human-centred responsibilities, workplace strengths, adaptability and experience with technology and AI.
Findings come from that employee-reported evidence. They do not depend on assumptions about a sector, organization type or job title.
The resulting picture reflects the people who participated. Employees can help connect the aggregate findings to the work itself and explore what the patterns may mean.
Different aspects, interpreted separately.
AI Task Exposure
Task characteristics that may intersect with current AI capabilities. Exposure does not predict that a job will disappear or that staffing should be reduced.
Human Strengths
Human-centred responsibilities and reported workplace capabilities that help describe the human contribution to the work.
Adaptability
Reported capacity to adjust to changing responsibilities and ways of working.
Technology Readiness
Technology comfort, confidence in learning new technology, organizational support and experience with AI tools.
The dimensions are never combined into one overall score. Human Strengths do not mathematically reduce AI Task Exposure. The report also considers exposure alongside adaptability and technology readiness to help interpret selected patterns.
Leadership sees patterns.
Personal reports stay private.
What leadership receives
Aggregate findings across the four dimensions and, when comments are provided, an unattributed summary of their material themes and concerns.
Results are reported for the organization as a whole, without identifying individuals or breaking findings down by position, department or group.
What remains private
Individual scored responses, linked response records and personal reports are not shared with leadership.
Identifying details are removed from the participant-comment summary. Similar feedback is combined while preserving material themes and concerns.
The Snapshot shows what patterns exist, rather than who sits behind them. Employee involvement helps leadership understand those patterns and consider appropriate next steps.
Practitioner-developed.
AI-supported. Human-directed.
AI supports much of the analysis. Defined analytical instructions and rules support consistent calculations, pattern identification and interpretation.
The methodology was developed and independently challenged using multiple leading AI models. These provided complementary development and review, helping question assumptions, test consistency and identify potential problems.
Human judgment remains central. Donald DeGagne directed the development of the methodology, safeguards, interpretation and reporting approach, drawing on 32 years of local-government management experience.
Read the report’s explanation: How This Snapshot Works
The Snapshot begins with information provided by your employees about the work they actually do. Rather than relying primarily on job titles or general predictions about occupations, the assessment gathers structured information about tasks, human strengths, adaptability and workplace technology experience.
A defined methodology analyzes that information across four dimensions: AI Task Exposure, Human Strengths, Adaptability and Technology Readiness. It also examines selected relationships between dimensions to help identify patterns that may be useful to understand.
AI supports much of this analysis. Carefully developed analytical instructions and rules are used to support consistent calculations, identify patterns and help interpret what the findings may mean for the organization.
The methodology itself has been developed and independently challenged using multiple leading AI models as complementary development and review systems. They have been used to question assumptions, test consistency, identify potential problems and provide independent second opinions during development.
Human judgment remains central. The methodology, safeguards, interpretation and reporting approach were developed under the direction of Donald DeGagne, drawing on 32 years of local-government management experience. AI supports the analytical process; management experience, critical thinking and judgment guide the methodology and final interpretation.
The result is not simply a questionnaire submitted to an AI system to generate a report. It is a structured assessment process combining employee evidence, defined analytical rules, modern AI capabilities and experienced human oversight.
The detailed analytical methodology and instructions are proprietary. The purpose of this section is not to explain those internal mechanics, but to make clear what sits between the employee questionnaire and the finished Snapshot.
Your employees provide the information. The system analyzes the patterns. Leadership receives an independent organizational picture to help decide what deserves attention next.
Evidence for judgment and discussion.
The Snapshot provides an organizational picture grounded in participant responses. Those responses describe reported experience and capabilities; they do not demonstrate every aspect of performance or explain everything behind a pattern.
Interpretation is qualified where the evidence calls for it. Practical considerations and Questions Worth Exploring help leadership and employees decide what deserves further attention.
The Snapshot may identify useful areas of action or categories of expertise. It does not promote a particular tool, training program, consultant, provider or Realistik service.
The detailed analytical methodology and instructions are proprietary. This page explains the basis of the report without reproducing its internal production rules.
See the approach in a complete report.
Explore the sample Snapshot, including the findings, interpretation and practical questions.
View the Workforce Snapshot →Need More Information? →Connection to Canadian Responsible AI Guidance
The Snapshot’s emphasis on transparency, privacy protection and informed human judgment is consistent with themes in Canada’s AI Strategy for the Federal Public Service 2025–2027.
Realistik AI Dynamics developed its approach independently. This connection describes shared principles; it does not imply government endorsement, certification or a formal compliance assessment.