Foundation-First AI Readiness Assessment

Five questions. Two minutes. Tells you whether your data foundation is ready for AI or where it's blocking you.

When your team makes a key operational decision, is the relevant data actually being captured, or do you
rely on exports, spreadsheets, or tribal knowledge?

When your team makes a key operational decision, is the relevant data actually being captured, or do you rely on exports, spreadsheets, or tribal knowledge?

A

We rely heavily on manual exports, spreadsheets, or institutional memory

B

Some systems capture data automatically, but coverage is inconsistent

C

The data we need for most decisions is captured systematically

How confident is your team that the data you use is clean and trustworthy, and not just available?

A

Data quality issues are a recurring problem; trust is low

B

Data is mostly usable but requires regular cleanup or validation

C

We have reliable processes that keep data clean and consistent

Where do operational decisions actually get made in your organization?

A

In conversations, meetings, or people's heads; nothing lands in a system

B

Some decisions use data, but inconsistently across teams

C

Key decisions are driven by defined systems with clear data inputs

How would you describe your team's readiness to adopt new AI-powered workflows?

A

Change is slow; new tools often fail to stick

B

Some appetite for automation, but change management is a recurring challenge

C

The team actively adopts and iterates on tools that solve real problems

If you brought in an AI initiative today, who would own it after the consultant leaves?

A

No one; we lack the internal capability or ownership structure

B

Someone could, but it would be a stretch role or secondary priority

C

We have a clear owner with the skills and mandate to drive it