Framework overview

What is GAMM™

GAMM™ is the enterprise maturity model that makes AI readiness measurable 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, platforms, governance, and operating models. The Giggle AI Audit™ applies GAMM™ as a repeatable framework, producing decision-grade signals that guide investment, risk, and sequencing without exposing proprietary scoring logic.

What GAMM™ measures

Orchestration-first: evaluates the system that produces outcomes, not isolated pilots.

Evaluation discipline: consistent scoring and thresholds for repeatable insight.

Governance caps: maturity signals constrained by risk, compliance, and accountability.

Platform-level lens: assesses enablement and lifecycle readiness, not just use cases.

Decision-aligned outputs: built for executive, risk, and portfolio governance use.

Evidence of rigor

  • Structured maturity dimensions covering data, platform, governance, operating model, and product integration
  • Standardized scoring and weighting across dimensions for comparability over time
  • Clear separation between exposed signals and internal scoring mechanics
  • Designed for regulated, multi-entity enterprise environments
  • Built to integrate into existing governance, risk, and portfolio processes

Maturity dimensions

GAMM™ describes system-level maturity without disclosing scoring logic. Each dimension reflects a foundational capability required for AI to scale safely and sustainably across enterprise environments.

Data foundations and ownership

Evaluates whether data assets are accessible, governed, and owned in a way that supports reliable, cross-team AI operations.

Platform and infrastructure readiness

Assesses whether platforms support secure, observable, and maintainable AI delivery at enterprise scale.

Governance, compliance, and risk controls

Examines how risk is identified, governed, and monitored across legal, ethical, and regulatory obligations.

Operating models and team enablement

Looks at how teams are structured, enabled, and supported to build, deploy, and maintain AI systems responsibly.

Product integration and lifecycle maturity

Considers how AI capabilities are integrated into products and services, including ownership, iteration, and long-term accountability.

Why governance caps matter

Maturity signals are constrained by governance caps so readiness reflects real-world accountability, risk obligations, and regulatory expectations.

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.

What GAMM™ enables

GAMM™ defines AI maturity across the full enterprise system, 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.

Access GAMM™ in practice

The Giggle AI Audit™ applies GAMM™ as a repeatable framework for enterprise use.

Start the Giggle AI Audit™

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