Framework overview
GAMM™ is the enterprise maturity model that turns fragmented AI governance into measurable control, decision, and runtime readiness across platforms, governance, and operating systems—applied through the repeatable Giggle AI Audit™ framework.
GAMM™ (Giggle AI Maturity Model) gives enterprises a clear, defensible way to measure AI readiness across data, platform, governance, and operating models while exposing control gaps without sharing proprietary scoring logic. The Giggle AI Audit™ applies GAMM™ consistently, producing decision-grade signals that guide investment, risk, and sequencing.
Orchestration-first: evaluates the control system that produces outcomes, not isolated pilots.
Evaluation discipline: consistent scoring and thresholds that expose decision gaps and keep accountability measurable.
Governance caps: maturity signals constrained by risk, compliance, and accountability so compliance is not mistaken for control.
Platform-level lens: assesses enablement and lifecycle readiness, not just use cases.
Decision-aligned outputs: built for executive, risk, and portfolio governance needs.
GAMM™ describes system-level maturity without disclosing scoring logic while surfacing the control, decision, and runtime gaps that stall scale. Each dimension reflects a foundational capability required for AI to scale safely and sustainably across enterprise environments.
Evaluates whether data assets are accessible, governed, and owned in a way that supports reliable, cross-team AI operations.
Assesses whether platforms support secure, observable, and maintainable AI delivery at enterprise scale.
Examines how risk is identified, governed, and monitored across legal, ethical, and regulatory obligations.
Looks at how teams are structured, enabled, and supported to build, deploy, and maintain AI systems responsibly.
Considers how AI capabilities are integrated into products and services, including ownership, iteration, and long-term accountability.
Maturity signals are constrained by governance caps so readiness reflects real-world accountability, risk obligations, and regulatory expectations—because compliance is not control.
This prevents high-performing pilots from being misread as enterprise readiness when platform, compliance, or operating controls are still immature.
The output is defensible signal, not exposed scoring mechanics.
GAMM™ defines AI maturity across the full enterprise system, capturing control, decision, and runtime readiness—not just model performance.
Giggle AI Audit™ is a named, repeatable framework that applies GAMM™ consistently over time.
Outputs provide decision-grade signals for investment, governance, and portfolio prioritization.
Assessment is platform-aware, linking technology, operations, and risk in one view.
Repeatability enables longitudinal tracking as regulation and operating models evolve, so control gaps stay visible.
The Giggle AI Audit™ applies GAMM™ as a repeatable framework for enterprise use.
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