How to Measure AI Adoption: 5 Metrics and a Worked Example
Learn how to calculate AI adoption, frequency, retention and task use, with clear definitions, a worked example and a practical reporting checklist.

Orchard blog
Practical guides to understanding how work happens, finding what needs attention, and deciding what to improve.
Learn how to calculate AI adoption, frequency, retention and task use, with clear definitions, a worked example and a practical reporting checklist.
Learn six workforce analytics metrics, how to calculate them, and what they mean, with a worked example covering staffing, training, tool use, and output.
Compare team workload with available capacity using clear formulas, a fictional worked example, skill constraints, and spreadsheet-ready worksheet columns.
32 articles
Keep SOPs current as work changes. Compare written steps with real tasks, resolve mismatches, test revisions and use a practical update record.
Hand off project work when source files are restricted. Use a practical checklist, a worked action brief and a recipient check to keep context and permissions clear.
Find out why employees aren’t using your AI tools. Walk through a real task, identify the barrier and choose a useful change—or keep the current method.
Choose a useful AI pilot from actual team work. Compare three candidate tasks, check whether a test is practical, and write a clear selection brief.
Learn how to distinguish flexible schedules from extra work, uncover unplanned support commitments, and check whether your workload plan depends on additional hours.
Reconcile conflicting workforce reports by checking definitions, dates and people. Includes a headcount example and a copyable reconciliation record.
Compare team workload with available capacity using clear formulas, a fictional worked example, skill constraints, and spreadsheet-ready worksheet columns.
Learn how to calculate AI adoption, frequency, retention and task use, with clear definitions, a worked example and a practical reporting checklist.
Learn six workforce analytics metrics, how to calculate them, and what they mean, with a worked example covering staffing, training, tool use, and output.
Scope desktop discovery, investigate repeated work, and validate opportunities against privacy requirements and a measured baseline.
A practical approach to studying desktop activity, finding repetitive tasks, and assessing where automation may help.
Compare APIs and screen scraping through data access, authorization, reliability, security, and maintenance.
Define an automation inventory, risk tiers, approvals, monitoring, and clear ownership for citizen development.
Build a runbook with clear triggers, named owners, escalation rules, and measures for handling exceptions.
Evaluate integrations and desktop automation, then scope a pilot around a specific small-business workflow.
Select AI workflow opportunities, establish a baseline, and measure costs and outcomes before expanding.
Set ownership, intake, monitoring, change control, and review practices for an automation program.
Compare RPA, intelligent automation, and hybrid workflows through input quality, exceptions, and governance.
Assess APIs, desktop automation, and hybrid approaches against the capabilities a workflow actually needs.
Identify repetitive handoffs between systems, measure manual effort, and evaluate a scoped automation pilot.
Measure task time savings and estimate labor capacity value while keeping it separate from reduced spending.
Explore Excel data-entry approaches, from structured inputs and Power Query to workflow automation.
Understand where people initiate or supervise automation and what each operating mode requires.
Place review, approvals, and escalation points within desktop automation so responsibility stays clear.
Match Windows automation approaches to task requirements, application access, and operational constraints.
Define the responsibilities, intake process, and governance practices of an automation center of excellence.
Evaluate recurring project updates, handoffs, and reporting as candidates for a focused automation pilot.
Compare desktop task observations with process event logs to choose the right evidence for a workflow problem.
Plan for workflow changes with impact assessment, pilot feedback, communication, and clear ownership.
Assess repeatable procedures through documented steps, responsibilities, decision points, and exception handling.
Build an automation business case with explicit costs, benefit assumptions, and a distinction between capacity and cash savings.
Prioritize repeated work across finance, HR, and IT, then define a baseline and scope an initial pilot.
From reading to understanding
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