Decision and value
A bounded use case, operating decision, intended benefit, stop condition, and accountable sponsor.
LA Global Institute Leadership decision tool · Updated August 27, 2026
An AI readiness assessment built around the decisions leadership must resolve.
Use this no-signup checklist before procurement, integration, or rollout. It helps a leadership team identify whether one proposed AI use case has a defensible purpose, accountable owner, fit-for-purpose data, human review, risk controls, and a measurable operating path.
Six connected decision areas
Readiness belongs to a use case—not to an organization in the abstract.
A team can be ready to test one bounded internal workflow and unready to automate a consequential decision. Review the exact use case, affected people, data, system, and operating context together.
Ownership and people
The people who approve, operate, review, experience, challenge, and stop the system.
Data and access
Minimum inputs, permitted sources, quality limits, access rules, retention, privacy, and security.
Workflow and technology
The current process, system fit, dependencies, failure path, and point of human review.
Governance and risk
Purpose limits, prohibited uses, applicable requirements, testing, incidents, and retirement.
Measurement and monitoring
A baseline, benefit and harm signals, review window, operating cost, and decision date.
Private in-browser worksheet
Resolve the first open decision—not an abstract maturity score.
Mark each statement as resolved only when leadership can point to evidence and an owner. Mark it open when the decision still needs work. Unmarked items remain unreviewed.
Source boundary
Use public frameworks as evidence—not as a badge.
The National Institute of Standards and Technology describes its AI Risk Management Framework and Playbook as voluntary resources organized around Govern, Map, Measure, and Manage. The U.S. Government Accountability Office organizes its AI accountability framework around governance, data, performance, and monitoring. Those sources informed the categories above; neither agency created, endorsed, reviewed, or certified this worksheet.
Questions leadership asks
Know what the checklist can—and cannot—settle.
What is an AI readiness assessment?
It is a structured review of whether a specific proposed use case has the decision clarity, people, data, technology, governance, and measurement needed to proceed responsibly. This page is a planning aid for leadership; it is not a scored certification or professional compliance determination.
Does every item need to be resolved before any experiment?
No universal sequence applies to every organization or use case. The purpose is to expose material unknowns, assign owners, and decide what must be resolved before a bounded, low-risk test. A high-consequence use case may require stronger evidence and independent review.
Is this the NIST AI Risk Management Framework?
No. NIST's voluntary AI RMF organizes risk work around Govern, Map, Measure, and Manage. This LA Strategy Institute worksheet uses those public principles and the GAO accountability themes as source context, then translates them into six practical leadership decision areas. It is not an official NIST or GAO tool.
What should leadership do with an open item?
Name the exact decision, evidence needed, accountable owner, approval boundary, and review date. If the organization cannot resolve a material data, rights, security, professional-review, or human-oversight question, pause the use case rather than hiding the gap inside a vendor selection.
Does completing the checklist mean the organization is AI-ready?
No. A recorded answer is not proof. Readiness depends on the use case, operating context, evidence, risk tolerance, applicable obligations, and what happens after deployment. Reassess when the model, vendor, data, workflow, people, or external requirements change.