This diagram breaks down a single COMPEL lifecycle stage into its constituent elements: defined inputs that trigger the stage, key activities performed during execution, outputs and deliverables produced, and quality gate criteria that must be satisfied before advancing. The visual flow from inputs through activities to outputs shows how each stage transforms organizational capability, while gate criteria ensure governance rigor is maintained throughout the transformation journey without sacrificing delivery momentum.
Stage 5 of 6
Evaluate
Conduct comprehensive reviews of KPIs, control performance, adoption, incident and risk indicators, and ROI to determine transformation effectiveness and pinpoint improvement areas. Operationally, execute KPI reviews, control-effectiveness audits, adoption surveys, incident analysis, ROI calculations, and cross-framework conformity assessments — producing gate review decision records for every active AI operation.
Strategic Objective
Conduct comprehensive reviews of KPIs, control performance, adoption metrics, incident/risk indicators, and ROI to determine transformation effectiveness and areas for improvement.
Operational Objective
Execute KPI reviews, control performance audits, adoption assessments, incident analysis, and ROI calculations to produce evidence-based evaluation of all active AI operations.
-
Inputs
- from produce: Deployed Models
- from produce: Monitoring Instrumentation
- from produce: Operational Controls and Evidence
- Evaluation Metric Definitions
- Red Team Playbook
- Bias Testing Protocol
-
Activities (17)
- Gate Review execution
- Audit center management
- Re-attestation triggers and cycles
- Risk acceptance reviews
- Governance scorecard assessment
- Model retirement evaluation
- Stakeholder validation reviews
- Benchmarking against success criteria
- Bias and fairness testing
- Business value validation
- Regulatory conformity assessment
- Internal audit execution
- Audit preparation and support
- Agent performance monitoring and trust score tracking
- Agent behavior drift detection and compliance assessment
- Vendor performance monitoring and supply chain audit
- AI-BOM review and supplier maturity assessment
-
Quality Gate — Gate E
- Audit complete
- Gate reviews passed
- Risk acceptance documented
- Conformity assessment complete for applicable regulations
- Compliance evidence collected and verified
- Regulatory documentation package complete
- Cross-framework alignment validated
-
Outputs (13)
- Gate review decisions and action items
- Audit findings and remediation plans
- Re-attestation records
- Risk acceptance register
- Transformation effectiveness scorecard
- Bias and Fairness Testing Report
- Business Value Validation Report
- Conformity Assessment Record
- COMPEL Governance Scorecard
- Stakeholder Approval Register
- Agent trust score report and incident review
- Vendor performance report and supplier maturity scorecard
- Supply chain audit report with AI-BOM verification
-
Handoffs
- → Learn: Evaluation reports
- → Learn: Incident logs
- → Learn: Drift findings
- → Learn: Audit findings and gate decisions
What Are the Inputs for the Evaluate Stage?
External inputs (3)
-
Evaluation Metric Definitions
The success metrics and KPIs established by Calibrate transformation success criteria. Evaluate uses these to benchmark whether the program is delivering the outcomes leadership signed up for.
NIST AI RMF (Measure function)ISO/IEC 25059 -
Red Team Playbook
The standard adversarial testing methodology for AI systems. Evaluate uses the playbook to run repeatable red team exercises and to compare results across systems and time.
MITRE ATLASOWASP LLM Top 10NIST AI RMF Manage 2.1 -
Bias Testing Protocol
The standard fairness and bias testing methodology. Evaluate uses the protocol so bias assessments are consistent across models and defensible to auditors.
NIST SP 1270IEEE 7003EU AI Act Article 10
Handoff inputs from prior stages (3)
-
Deployed Models
from ProduceThe production AI systems handed over from Produce. Evaluate runs gate reviews, conformity assessments, and performance audits against these live deployments.
COMPEL Stage — Produce -
Monitoring Instrumentation
from ProduceThe telemetry, dashboards, and alerts wired up during Produce. Evaluate uses this data feed to compute trust scores, drift signals, and audit evidence without manual collection.
COMPEL Stage — Produce -
Operational Controls and Evidence
from ProduceThe control library and evidence repository produced during Produce. Evaluate maps audit findings and conformity assessments back to these controls.
COMPEL Stage — Produce
What Activities Occur During the Evaluate Stage?
- → Gate Review execution
- → Audit center management
- → Re-attestation triggers and cycles
- → Risk acceptance reviews
- → Governance scorecard assessment
- → Model retirement evaluation
- → Stakeholder validation reviews
- → Benchmarking against success criteria
- → Bias and fairness testing
- → Business value validation
- → Regulatory conformity assessment
- → Internal audit execution
- → Audit preparation and support
- → Agent performance monitoring and trust score tracking
- → Agent behavior drift detection and compliance assessment
- → Vendor performance monitoring and supply chain audit
- → AI-BOM review and supplier maturity assessment
What Are the Outputs of the Evaluate Stage?
- ✓ Gate review decisions and action items
- ✓ Audit findings and remediation plans
- ✓ Re-attestation records
- ✓ Risk acceptance register
- ✓ Transformation effectiveness scorecard
- ✓ Bias and Fairness Testing Report
- ✓ Business Value Validation Report
- ✓ Conformity Assessment Record
- ✓ COMPEL Governance Scorecard
- ✓ Stakeholder Approval Register
- ✓ Agent trust score report and incident review
- ✓ Vendor performance report and supplier maturity scorecard
- ✓ Supply chain audit report with AI-BOM verification
Key Questions
- ? Are we meeting our transformation objectives?
- ? What audit findings need remediation?
- ? Are stage transitions proceeding as planned?
- ? What is our current governance maturity score versus the baseline?
What Are the Gate Criteria for Evaluate?
- ⚠ KPI review completed for all deployed systems
- ⚠ Control performance audit completed with findings documented
- ⚠ Adoption review shows trends against targets
- ⚠ Incident and risk review completed with categorized findings
- ⚠ ROI calculation completed for each active use case
- ⚠ Gate E review passed with decision recorded
Related Articles (170)
Articles from the Body of Knowledge that are tagged to the Evaluate stage or are lifecycle-wide and apply here.
- M1.1The AI Transformation Imperative
- M1.1Defining AI Transformation vs. AI Adoption
- M1.1The Enterprise AI Maturity Spectrum
- M1.1Introduction to the COMPEL Framework
- M1.1The Four Pillars of AI Transformation
- M1.1AI Transformation Anti-Patterns
- M1.1The Business Value Chain of AI Transformation
- M1.1Stakeholder Landscape in AI Transformation
- M1.1AI Transformation and Organizational Culture
- M1.1Ethical Foundations of Enterprise AI
- M1.2Evaluate: Measuring Transformation Progress
- M1.2Stage Gate Decision Framework
- M1.2The COMPEL Cycle: Iteration and Continuous Improvement
- M1.2Mapping COMPEL to Your Organization
- M1.2Integration with Existing Frameworks
- M1.2Evaluating Agentic AI: Goal Achievement and Behavioral Assessment
- M1.2Agent Learning, Memory, and Adaptation: Governance Implications
- M1.2Transformation Enablers
- M1.2Mandatory Artifacts and Evidence Management Across the COMPEL Cycle
- M1.2The COMPEL Operating Model: Roles, RACI, and Decision Rights
- M1.2Entry and Exit Criteria: Stage Gate Readiness Across the COMPEL Cycle
- M1.2Creating the AI Operating Model Blueprint
- M1.2Producing the Readiness Assessment Report
- M1.2Building the Control Requirements Matrix
Which Knowledge Domains Apply to Evaluate?
- AI Governance & Compliance64 articles
- AI Strategy & Vision52 articles
- Transformation Design & Program Architecture45 articles
- Value Realization & ROI26 articles
- Framework Interoperability & Standards21 articles
- Organizational Change & Culture20 articles
- Enterprise Operating Model & Portfolio Leadership20 articles
- Risk Management & AI Ethics16 articles