AI Readiness Scorecard
A practical scoring model for deciding which AI use case should be assessed, piloted, deferred, or rejected before budget is committed.
What the asset is
A structured scorecard that rates business value, process clarity, data availability, cloud readiness, security posture, governance needs, integration effort, stakeholder readiness, and pilot feasibility.
Who it is for
CXOs, operations leaders, IT/cloud leaders, data leaders, legal/compliance teams, and business owners considering a first AI initiative.
Business problem supported
Too many AI ideas compete for attention without a clear way to compare value, risk, data readiness, and delivery feasibility.
What the buyer learns
Which use case is ready, what gaps must be closed, what controls are required, and whether a 45-day pilot is realistic.
How DigiScience uses it
The scorecard anchors discovery, helps qualify opportunities, and becomes the first section of the readiness or pilot proposal.
AI readiness questionnaire: 12 decision questions
Use these questions to decide whether a proposed AI workflow is ready for discovery, a bounded pilot, or more foundational work. It is a practical questionnaire, not an automated score or promise of value.
Business value
What decision, service, or workflow will improve? Who owns the outcome? What baseline will show whether the work helped?
Workflow fit
Is the workflow repeatable enough to map, and where must a person remain accountable?
Data readiness
Which data is needed, who can approve access, and what evidence shows it is representative and permitted?
Risk and governance
What could go wrong, who can accept the risk, and what human review, audit, privacy, or residency controls apply?
Architecture fit
Can the current applications, cloud, network, identity, and observability support the proposed workflow safely?
Delivery feasibility
Can the team supply a defined scope, a sponsor, representative samples, acceptance criteria, and a pilot decision within a practical timeframe?
A Solution Assessment turns those answers into a recommended next step: workflow redesign, conventional automation, a bounded AI pilot, platform modernization, or a decision not to proceed yet.