Illustrative survey report
AI Familiarity & Comfort Summary
A preview of how survey findings can inform learning priorities, a readiness profile and a 60–90 day plan. The examples are illustrative; respondent counts and comfort values are redacted.
Key metrics snapshot
| Metric category | What we summarize | Why it matters |
|---|---|---|
| AI usage frequency | Never, rarely, occasionally, weekly or daily use. | Establishes the starting point for training. |
| Organizational adoption | No use, informal experimentation, pilots or operational use. | Shows whether activity is individual or structured. |
| Tools and experience | Chatbots, agents, specialized tools and reported activities. | Anchors learning in familiar tools and current practice. |
| Concerns | Where to start, privacy, accuracy, time, cost and other barriers. | Directs policy, support and training priorities. |
| Priority focus areas | Processes people want to improve and preferred learning formats. | Connects learning to the team’s actual work. |
Reading the readiness profile
The report can compare a current profile with a proposed 90-day target across nine dimensions in the Conceptual, Operational and Governance lanes.
Swipe across the chart to read all nine dimensions.
How the report frames AI readiness
Each swim lane connects the team’s starting point to a proposed learning objective. Examples below describe the reporting approach.
Conceptual understanding
What we assess: Understanding of training data, output variability, bias, limitations and ethical considerations.
Example progression: From describing AI as a tool that generates text to explaining why its outputs vary and when they need verification.
Why it matters: A shared mental model helps people recognize limitations before relying on an answer.
Operational practice
What we assess: Choosing tools, writing effective prompts, checking results and applying AI in workflows.
Example progression: From trying a basic prompt to using AI for a work task with a repeatable review step.
Why it matters: Practice connects tool familiarity to tasks people need to complete.
Governance and oversight
What we assess: Policies, review practices, protection of personal information and approval of pilots.
Example progression: From naming risks to applying organizational policies and verification requirements.
Why it matters: Clear boundaries help people use AI without exposing information or accepting unchecked output.
A 60-90 day plan for AI literacy
Survey findings guide the starting point and use cases. This example sequence and its targets are adapted after the results are reviewed.
Conceptual foundation
Build a shared vocabulary and mental model for how AI works. Address the “don’t know where to start” gap with plain-language foundations.
Typical activities: A 60-90 minute fundamentals session on capabilities, limitations, training data, output variability, bias and organizational context.
Illustrative success measure: 70% of participants advance one RUDI level in conceptual understanding.
Operational skills
Practice the priority use cases identified in the survey. Connect AI use to the team’s real tasks.
Typical activities: Three or four 45-60 minute modules on workflows such as administration, compliance documentation, communications, data insights or grant writing.
Illustrative success measure: 50% of participants use approved AI templates weekly with verification protocols.
Governance implementation
Turn individual experimentation into practice guided by clear policies and review requirements.
Typical activities: A one-page Responsible Use guide, a pilot rubric with approval steps and success measures, and ongoing support.
Illustrative success measure: 100% compliance with the organization’s personal-data policies and verification protocols.
Choose the work to improve first.
The final report turns expressed needs and concerns into priority use cases and immediate actions. The examples below show the format.
High priority
Define responsible AI use in the organization’s context.
Operational time-saversIdentify repeatable administration, reporting and documentation tasks.
Privacy and securitySet boundaries around sensitive information.
Medium priority
Stakeholder engagement, multilingual outreach and messaging.
Data insights and strategic documentationReporting, dashboards, grant writing, proposals and longer documents.
Future development
Training materials and knowledge capture, advanced workflow automation, and cross-functional integration.
Typical immediate actions
- Draft a one-page Responsible Use guide for the organization.
- Create three to five workflow templates with prompts and verification checklists.
- Plan foundation sessions with the relevant stakeholders and champions.
- Establish support through office hours, a community of practice or an escalation path.