In this sample, adoption is 96 lifetime-active users out of 120 enrolled employees. The fixed example ends 9 September 2026 and contains a full year of synthetic history. Active users, prompts, platforms and use cases are filtered to the selected 30-day period. Every chart and table uses the same records. The smaller worked example further down the page is a separate teaching sample.
Average usage time uses 40,375.7 minutes of synthetic active-tab duration from 80 users, divided by those contributors and normalized to a week over the selected 30-day period. This is not time saved or an average across all enrolled employees. Prompt counts and active-tab duration are separate measurements; neither represents unique conversations or security events.
High-risk prompts have a synthetic security or privacy score of at least 0.7 on a 0–1 scale. Associated Risk uses the higher of each use case’s average security and privacy scores: High above 0.7, Medium from 0.4 through 0.7, otherwise Low. These invented scores describe sample prompt content, not an intrinsic rating of the task or evidence of a policy block.
Reconstructed from the current global-admin interface. Synthetic data, not a product screenshot or live employee activity. Simplified controls; no account connection.
Scope to confirmOnly covered employee activity is shown. Recorded use is not a measure of productivity.
Coverage and deployment details
Adoption analytics reflect the deployed collection scope and enrolled population, not every employee or unknown tool.
Activity does not establish time saved, work quality, ROI or employee performance.
Review group sizes, reporting periods and metric definitions together. No recorded activity can also warrant a collection check.
Built for your decision
Find your next AI rollout decision.
Find the team, tool or rollout question behind the activity. Choose where to look next.
IT directors
Measure AI adoption by department
One department has less recorded AI activity than another.
Synthetic covered population · same period
Finance3 of 4 enrolled
Operations1 of 4 enrolled
Keep in viewCompare the same period and collection coverage.
Scenario details
Inspect
Active users
Enrolled population
Groups view
Next decision
Choose where to investigate access, training or workflow fit.
Use the Groups view to compare activity across enrolled teams. Check both the active-user count and the group population: a busy department and a well-covered department are not necessarily the same thing. A lower figure is a reason to discuss access, training or workflow fit, not a verdict on employee performance.
AI rollout owners
Understand which AI tools and use cases stick
Teams bring different tasks to their AI tools.
Synthetic observed workflow labels
AI writing toolDrafting
AI chat toolSummarising
Use observed tasks to focus enablement, not to rate work.
Keep in viewRecorded use does not establish work quality or productivity.
Scenario details
Inspect
Platform usage
Use Cases view
Recurring tasks
Next decision
Focus the next training session on the work people do.
Review platform usage alongside the tasks people bring to AI. A team using AI for drafting may need different guidance from one using it to summarise information. Ground enablement in those observed workflows before expanding a pilot or recommending another tool.
CIOs and programme sponsors
Track AI adoption through the rollout
Your next review needs more than an organisation-wide adoption figure.
Review comparison basis first
Selected periodSame review window
Covered populationSame enrolled group
Overview, Groups and Trends are different views, not a single adoption measure.
Keep in viewLifetime adoption and period-active users are different measures.
Scenario details
Inspect
Overview
Groups
Trends
Next decision
Choose which team, tool or use case to revisit.
Review Overview, Groups, Use Cases and Trends with the same collection scope. Lifetime adoption, period-active users and active-tab usage time answer different questions. None of them alone establishes time saved, output quality or return on investment; those decisions need evidence from the work itself.
From evidence to a decision
How to measure AI adoption by department.
Compare the people behind the percentages. A useful department review combines active users, group size and collection coverage before deciding where to investigate access, training or workflow fit.
Department comparisonSynthetic example
11 Aug–9 Sep 2026 · Same covered population
4 / 8active · 50%
Finance
75%
3 active / 4 enrolled users
Operations
25%
1 active / 4 enrolled users
Combined population
4 of 8 enrolled users active · 50%
Department comparison
Reduced motion · choose a step
The decision behind the data
Start the conversation with Operations.
Confirm coverage, then ask about access, relevant tasks and training.
Recorded activity is not a performance ranking. Missing collection can look like low adoption.
How this department comparison is calculated
The example uses the same eight enrolled users as the dashboard above: three of four Finance users and one of four Operations users are active. That gives 75% and 25%; combined, four of eight users are active (50%). These are invented populations, not customer adoption results.
The current Groups calculation uses active members divided by total members. Its meaning depends on the selected period and collection scope. Do not substitute the Overview tile’s lifetime-adoption figure or treat AI usage time as time saved.
Before comparing departments, check group membership, enrolled devices and the reporting period. Discuss access, relevant tasks and training with Operations: its lower recorded rate does not establish which of these explains the difference.
Agree a targeted follow-up, then compare an equivalent period and population. Establish work quality and business impact separately. Group-rate formula: Active group members ÷ total group members × 100.
Bring the teams you want to compare and the rollout decision you need to make.
Collection depends on the supported tool, device and workflow.
Only supported, covered activity is collected.
01 / 03
Global adminIllustrative example
AI Adoption · Groups
Last 30 days
4 / 8active / enrolled users
12recorded prompts
Finance9
Operations3
Prompt activity, not a measure of productivity.
Compare the same period and population.
02 / 03
IT + rollout teamIllustrative example
AI Adoption · Review inputs
Your next rollout review
Team & collection coverage
AI tools in use
Recurring use cases
Human review, not a productivity score.
03 / 03
Workflow details
01 / Browser plugin + desktop app
Establish collection coverage
Identify the employees, devices and supported AI interactions included in the deployment. Activity from a device without endpoint coverage is not included in the dashboard.
02 / Global admin · AI Adoption
Review the right view
Use Overview for a baseline, Groups for team comparisons, Use Cases for tasks and Trends for change over time. Check the selected period before comparing figures.
03 / Your next rollout review
Choose an informed follow-up
Bring a specific observation to the team: an adoption gap, a recurring use case or a change in platform mix. Agree on a targeted action and compare the same scope at the next review.
Make the demo useful
What to check in an AI adoption dashboard demo
Bring one rollout question and the teams you want to compare. A useful demo should show where the numbers come from, not simply display a larger activity total.
Bring to the conversation
01The teams to compare
02One rollout question
03A consistent review period
01Adoption versus active usersWhich denominator does each tile use?
What to inspect
Lifetime-active and period-active populations are different measures.
In your cloud, on your premises or on Aona-managed servers. Choose backend hosting separately from where Aona processes prompts, then agree operating responsibilities, storage, retention and supported integrations.
Yes. Aona prompt-processing options are the user device/on-edge, customer cloud or on-premises, and Aona-managed servers. Confirm the supported configuration, controls, file paths and telemetry for your rollout; the options do not imply identical capabilities or that all existing clients already use on-edge processing. The destination AI provider's data handling remains separate.
Start with lifetime adoption, active users in the selected period, group coverage, platform mix and use cases. Where duration telemetry is available, review average usage time separately. These measures describe recorded activity, not employee performance or productivity.
Average usage time uses recorded active-tab activity from users with duration data, shown as a weekly average. It is not prompt count, time saved or an average across all enrolled employees. The hero dashboard uses a synthetic 120-person organisation with a year of example history. Changing the period recalculates duration, contributors and the weekly average from the matching records.
Check employee enrolment, endpoint collection coverage, the chosen period and the selected view first. Then discuss access, training and workflow fit with the team. An empty view does not prove that no AI was used outside the covered deployment.
The current adoption tile uses lifetime-active users, while active users reflects the selected period. Changing the period should not be read as changing the lifetime measure. Review the enrolled population and collection scope alongside both figures.
Group views help compare adoption within the covered workforce. Use the same reporting period and review group sizes alongside the figures.
No. Activity shows recorded use; it does not establish time saved, work quality or employee performance.
This page focuses on adoption within a defined rollout. For an initial inventory of observed AI tools, see Shadow AI Discovery.
Your use case. Your demo.
Make your next AI rollout decision clearer.
Bring the teams and tools in your rollout. We’ll explore the adoption views, explain the metrics and focus on the questions you need to answer next.