Assessment Framework
AI initiatives often appear rigorous on paper—detailed architectures, impressive metrics, confident projections. Yet many fail not because of poor engineering, but because risk is assessed too late, or through the wrong lens.
What This Assessment Is (and Is Not)
This Is
- An independent risk assessment of AI investments
- Focused on capital protection and decision clarity
- Designed for board-level Go/No-Go and Continue/Stop decisions
This Is Not
- A technical design review
- A model optimization exercise
- A consulting engagement to "fix" the system
The role is strictly assessment, not advocacy.
Two Decision Moments This Framework Serves
Before Capital Commitment (Go/No-Go)
Used when:
- A new AI initiative is proposed
- Funding approval is required
- Strategic narratives are strong but evidence is uneven
Does this investment have a defensible probability of delivering real business value?
After Project Initiation (Continue/Stop)
Used when:
- Capital is already deployed
- Progress is slow or ambiguous
- Metrics look acceptable but outcomes remain unclear
Is continued investment justified, or are we compounding risk?
Stopping a project is treated as risk containment, not failure.
The Assessment Lens
The framework evaluates AI initiatives across four risk dimensions that commonly remain implicit:
1. Problem Framing Risk
- Is the AI system solving the right problem?
- Are business objectives translated into operational terms?
- Are constraints explicit or assumed?
2. Learning & Incentive Risk
- What exactly is the system being rewarded for?
- Could it optimize metrics while undermining business logic?
- Are incentives aligned with real-world outcomes?
3. Evaluation & Evidence Risk
- Do reported metrics reflect reality or laboratory conditions?
- Are failure modes visible—or systematically hidden?
- Is performance robust across regimes and scenarios?
4. Governance & Control Risk
- Who owns intervention decisions?
- Are stop-losses, overrides, and rollback mechanisms defined?
- Is there clarity on when the project should stop?
The Assessment Process
The assessment proceeds through structured review stages, each producing explicit findings rather than recommendations.
At each stage:
- Evidence is examined
- Assumptions are surfaced
- Risk exposure is articulated in decision language
The output is not a technical score, but a decision-grade risk narrative.
What the Board Receives
The final assessment provides:
- Clear articulation of capital risk drivers
- Identification of structural failure modes
- Explicit Go/No-Go or Continue/Stop rationale
- Early warning indicators for future review cycles
No technical deep dives are required to interpret the findings.
Why This Framework Exists
Most AI failures are only obvious in hindsight.
This framework exists to surface those risks before momentum and sunk cost make them invisible.
It is designed for:
- Independent Directors
- Board members
- CEOs and CFOs responsible for capital stewardship
Boundary Conditions
To preserve independence:
- No implementation responsibility is accepted
- No success fees are linked to outcomes
- No pressure exists to justify continuation
The assessment stands on its own.
"Are we investing in learning—or in an illusion of progress?"