A practical way to decide what to tackle first.

When staff need help, they know where to go, what is urgent gets treated as urgent, and requests do not disappear into a queue.

If your usual technical person left or became unavailable, another qualified person could understand and support your systems.

Recurring staff frustrations are reviewed for patterns and fixed at the source, not just closed one ticket at a time.

Leadership can see upcoming technology needs, vendor issues, and budget impacts before they become urgent surprises.

You are confident the right people, and only the right people, can access important email, files, finance, CRM, AMS, or business systems.

Your staff, computers, email, sign-ins, web browsing, and security awareness are protected as one managed baseline, not a set of disconnected tools.

You know what important data is backed up, how recovery would work, and whether recovery has actually been tested.

Leadership can understand security status, open actions, and owners without needing a technical translation.

You have a clear picture of where staff are already using AI, including public tools, built-in app features, meeting notes, browser assistants, or workarounds.

Staff know which AI tools are approved, what data is off-limits, and who to ask when a use case is unclear.

You are confident AI will not expose shared files, email, CRM or AMS records, finance data, donor/member/client data, or staff data to the wrong people.

Your first AI pilot is narrow enough to test safely: a clear owner, a small user group, allowed data, success measure, and stop/go decision.

AI learning is more than one training session: staff practice on real work with champions, cohorts, office hours, or role-based support.

There is a way to collect, compare, and approve AI ideas based on value, risk, data readiness, effort, and who will own the change.

The work you want AI to improve is understood well enough to redesign and measure, not just described as "make us more efficient."

For agentic or custom AI, you have a specific workflow candidate such as customer or member service, document intake, or internal operations, with known data sources, handoffs, human review, and an owner.