Tirion AI Decision System

AI Decision System

A decision model for leadership teams that need to turn AI ideas into investable use cases, controlled pilots or deliberate stops.

Request scorecard Best starting point: AI Kickstart

Tirion AI Decision System

Framework overview

The AI Decision System separates AI ideas from investable initiatives. A use case is ready for budget or pilot only when business outcome, owner, data access, risk, evaluation, security and operations are jointly reliable.

Architecture model

The Decision Logic

The framework puts AI initiatives into a sequence leadership can actually govern: clarify value, limit risk, check data, define evaluation and plan operations before a tool debate takes over.

01Business Value

What measurable business value appears and why does this use case matter now?

02Control Boundary

Which risks, approvals and human oversight points must stand before a pilot?

03Operating Readiness

Which data, metrics, owners and operating processes are needed after the first test?

Scorecard logic

Each dimension is scored from 0 to 3. A high score does not make the decision for leadership, but it shows whether the use case is investable, pilot-ready or needs to be rescoped.

25 to 30 points

Investable. The use case can move toward budget, pilot or implementation.

19 to 24 points

Pilot-ready, with gaps to close before production.

13 to 18 points

Rescope. Target, data or controls are still too unclear.

0 to 12 points

Stop or solve manually.

Readiness dimensions0-3

Business Outcome

Is the desired business value measurable?

0-3

Owner

Is there a business owner with decision authority?

0-3

Repeatability

Is the task frequent or strategically important enough?

0-3

Data Access

Are the needed sources allowed and reachable?

0-3

Data Quality

Are freshness, completeness and gaps known?

0-3

Risk

Is the use case classified by risk?

0-3

Human Oversight

Are review, escalation and stop mechanisms defined?

0-3

Evaluation

Are test set, metrics and negative tests available?

0-3

Security

Are least privilege, logging and secrets clarified?

0-3

Operations

Are owner, monitoring, feedback and incident process defined?

0-3

Hard stop criteria

No accountable business owner.
No legitimate or secured data access.
R3/R4 risk without human oversight.
External communication or mutating actions without approval process.
No way to measure output quality.

Short checklist

Problem described in one sentence.
Target process and current effort known.
Data sources, gaps and exclusions documented.
Risk class and controls defined.
Test set and success measurement available.
Operating model and stop decision clarified.

Where to use this framework

Prioritize an AI use-case portfolio

Compare several AI ideas with the same criteria before teams commit budget.

Cut the pilot scope

Show which parts of a use case are viable for phase 1 and what stays deliberately out of scope.

Prepare a leadership decision

Translate technical debate into value, risk, controls and the next approval point.

Executive FAQ

Author: TirionReviewed by: Tirion Advisory Framework

When is an AI use case investable?

When value, owner, data access, risk, evaluation, security and operations are at least sufficiently clarified. High potential alone is not enough.

What happens with a mid-range score?

The use case can often be piloted, but the gaps are made explicit and assigned to an owner before production.

Does the scorecard replace a workshop?

No. It creates decision structure. In AI Kickstart, it becomes a prioritized portfolio and 30/60/90 roadmap.

Start now

Need this translated into a real decision?

Use the score to identify the strongest AI, cloud or governance leakage before choosing a next step.

Start score