Insight: A five-layer framework for AI governance: integrating regula

Winners Consulting Services Co. Ltd. (積穗科研股份有限公司), Taiwan's expert in AI Governance, has identified a landmark 2025 study that every corporate executive navigating ISO 42001 certification, EU AI Act compliance, and Taiwan's AI Basic Law should read immediately: a five-layer AI governance framework that, for the first time, provides a structured, layer-by-layer bridge from high-level regulatory mandates all the way down to auditable, enterprise-ready certification processes — closing the implementation gap that has stalled AI compliance initiatives across industries worldwide.

About the Authors and This Research

This paper is co-authored by two researchers with substantial academic standing in the AI governance domain. Avinash Agarwal holds an h-index of 12 with 558 cumulative citations, focusing his career on governance mechanisms and technical standards for AI systems. Manisha J. Nene brings an even more extensive track record, with an h-index of 15 and 988 cumulative citations, recognized for her cross-disciplinary work at the intersection of AI security, ethics, and regulatory translation. Both researchers are affiliated with India's Defence Research and Development Organisation (DRDO)-connected research ecosystem, giving their work a distinctive dual perspective: governing AI in mission-critical national security environments while simultaneously addressing the compliance needs of civilian industry.

Since its publication in 2025, this paper has already accumulated 11 citations — a rapid uptake that signals strong demand from both the academic and practitioner communities for precisely this kind of structured, actionable governance guidance. For Taiwanese business leaders, the timing of this research is particularly relevant: Taiwan's AI Basic Law has entered force, the EU AI Act is progressively applying from 2025 onward, and ISO 42001 is emerging as the baseline certification requirement in international supply chains.

The Core Problem This Research Solves: Why "Implementation Gaps" Are Dangerous

The central challenge in AI governance today is not a shortage of regulations or principles — it is the absence of a clear, structured pathway from regulation to implementation. Enterprises know they must comply with laws like the EU AI Act or Taiwan's AI Basic Act, but they lack a systematic mechanism to translate those legal obligations into auditable internal controls. This paper directly addresses that gap.

Core Finding 1: A Five-Layer Architecture That Maps Regulation to Certification

The framework consists of five progressively focused layers: (1) Regulatory Mandate Layer — encompassing high-level laws such as the EU AI Act and national AI legislation; (2) Standards Layer — covering international technical standards including ISO 42001 and IEEE frameworks; (3) Assessment Methodology Layer — defining the specific evaluation tools and audit methodologies that operationalize those standards; (4) Certification Layer — establishing third-party verification mechanisms and conformity assessment procedures; and (5) Implementation Guidance Layer — providing enterprise-ready operational guidelines. Crucially, the framework does not just list these layers — it specifies the connective mechanisms between them, so enterprises can trace exactly how a legal principle becomes an auditable enterprise control.

Core Finding 2: Two Case Studies Reveal Three Systemic Governance Gaps

The researchers validated the framework through two real-world governance topics — AI fairness and AI incident reporting. Their case studies surface three systemic gaps that affect enterprises globally, including those in Taiwan: first, a lack of standardized fairness assessment procedures (regulations require fairness but no standard evaluation methodology exists); second, a lack of consistent incident reporting mechanisms (regulatory requirements vary across jurisdictions, making cross-border compliance operationally difficult); and third, a misalignment between global frameworks and region-specific implementation needs. These are not abstract academic observations — they are precisely the operational challenges that Taiwan enterprises face when attempting simultaneous compliance with EU AI Act Article 73 incident reporting requirements, ISO 42001 management system controls, and Taiwan AI Basic Law risk management obligations.

What This Research Means for Taiwan's AI Governance Practice

Taiwan enterprises are at a pivotal inflection point in AI governance. Three regulatory frameworks are simultaneously demanding action, and the five-layer model provides a single integrated structure to address all three.

Implication 1 — Operationalizing Taiwan's AI Basic Law: Taiwan's AI Basic Law establishes risk management as a mandatory enterprise obligation but does not prescribe specific assessment methodologies. The five-layer framework's Assessment Methodology Layer directly addresses this: for every legal principle, there must be a corresponding evaluation tool. Without this connection, compliance remains a paper exercise rather than an auditable organizational capability.

Implication 2 — Aligning ISO 42001 with EU AI Act Risk Classification: The EU AI Act classifies AI systems into four risk tiers — unacceptable risk, high risk, limited risk, and minimal risk. ISO 42001 provides the management system architecture to govern AI across these tiers. The five-layer framework explains, structurally, how these two frameworks should be integrated rather than implemented in parallel silos. Taiwan enterprises with EU market exposure must build this integration into their governance design from the outset, not retrofit it after initial implementation.

Implication 3 — Building Cross-Jurisdictional Incident Reporting Capabilities: The paper's case study on AI incident reporting reveals that most organizations lack a reporting mechanism capable of satisfying multiple jurisdictions simultaneously. Taiwan enterprises must design incident classification and reporting workflows that satisfy both Taiwan AI Basic Law obligations and EU AI Act Article 73 requirements — a non-trivial design challenge that requires deliberate architecture, not ad hoc response.

How Winners Consulting Services Co. Ltd. Helps Taiwan Enterprises Close the Gap

Winners Consulting Services Co. Ltd. (積穗科研股份有限公司) assists Taiwan enterprises in building AI management systems that comply with both ISO 42001 and the EU AI Act, conducting AI risk classification assessments, and ensuring that artificial intelligence applications conform to Taiwan's AI Basic Law requirements. Informed by the five-layer governance architecture presented in Agarwal and Nene's research, we offer the following specific actions:

1. Five-Layer Governance Gap Assessment: Using the five-layer framework as a diagnostic lens, we conduct a structured layer-by-layer review of your existing AI governance documentation, processes, and controls. The output is a board-ready governance status report that pinpoints exactly where your organization sits relative to ISO 42001 requirements and EU AI Act obligations — with prioritized remediation actions for each identified gap.
2. AI Risk Classification and Fairness Assessment Design: Responding directly to the paper's finding that standardized assessment procedures are missing from most governance frameworks, we help enterprises build an AI system inventory, apply EU AI Act four-tier risk classification, and design fairness and safety evaluation methodologies for each AI application — ensuring assessment results are auditable and defensible under regulatory scrutiny.
3. Cross-Jurisdictional Incident Reporting Mechanism Design: We design AI incident classification standards and reporting workflows that simultaneously satisfy Taiwan AI Basic Law obligations and EU AI Act Article 73 reporting requirements, eliminating compliance gaps that arise from treating each jurisdiction's requirements in isolation.

Frequently Asked Questions

What exactly is an "AI governance implementation gap," and why does it matter for my business?

An AI governance implementation gap is the structural disconnect between what a regulation requires and the specific tools and processes an enterprise needs to actually comply. For example, both Taiwan's AI Basic Law and the EU AI Act require risk management — but neither specifies which assessment methodology to use. This means enterprises often invest in compliance efforts without ever achieving auditable, verifiable compliance. Agarwal and Nene's research identifies this as a systemic problem across global AI governance, and their five-layer framework provides the structural solution: each regulatory requirement must be connected to a corresponding standard, assessment method, certification procedure, and implementation guide. Winners Consulting Services Co. Ltd. uses this framework to help enterprises identify precisely where their governance chain breaks down — and how to fix it.

How should a Taiwan enterprise begin its AI compliance journey? What is the first practical step?

The most impactful first step is building a comprehensive AI system inventory — a complete list of every AI system your organization currently uses or plans to use, along with the decisions those systems influence, the data they process, and the populations they affect. This inventory is the foundation for everything that follows: EU AI Act four-tier risk classification, ISO 42001 scope definition, and Taiwan AI Basic Law risk management planning. Without it, compliance efforts tend to be fragmented and incomplete. Once the inventory exists, the next step is a structured gap assessment against the applicable framework requirements. Winners Consulting Services Co. Ltd. can complete this diagnostic within the first 30 days of an engagement, providing a clear, prioritized compliance roadmap before any significant investment is made.

What is the relationship between ISO 42001 and the EU AI Act? Does a Taiwan enterprise need both?

ISO 42001 is the international management system standard for AI — it defines how an organization should govern, manage, and continuously improve its AI systems. The EU AI Act is binding law for any enterprise deploying AI systems in the EU market — it establishes mandatory obligations tied to risk levels, with the highest obligations applying to high-risk AI systems. The two frameworks are complementary: ISO 42001 provides the management architecture, and the EU AI Act provides the legal requirements that architecture must satisfy. For Taiwan enterprises with EU market exposure, both are necessary. For those currently focused on the domestic Taiwan market, ISO 42001 serves as an excellent governance foundation that simultaneously supports Taiwan AI Basic Law compliance and positions the enterprise for future EU market entry. Winners Consulting Services Co. Ltd. recommends a unified five-layer planning approach that covers multiple frameworks simultaneously, avoiding redundant implementation cycles.

How long does it take to implement ISO 42001, and what are the key milestones?

For an enterprise starting from baseline, building a fully compliant ISO 42001 AI management system typically requires 6 to 12 months, depending on organizational size and existing governance maturity. Winners Consulting Services Co. Ltd. structures the journey in four phases: Phase 1 (Days 1–30): Current-state diagnostic — complete AI system inventory, gap analysis against ISO 42001 requirements, and prioritized remediation roadmap; Phase 2 (Days 31–60): System design — develop AI governance policies, risk assessment procedures, and incident reporting workflows aligned to ISO 42001, EU AI Act, and Taiwan AI Basic Law; Phase 3 (Days 61–90): Pilot implementation — deploy the governance framework in selected AI application environments, collect operational data, and refine; Phase 4 (Day 90 onward): Continuous improvement and certification readiness — conduct internal audits, resolve nonconformities, and prepare for third-party certification assessment. Our complimentary diagnostic service helps enterprises determine the most efficient path before any major commitment is made.

Why should a Taiwan enterprise engage Winners Consulting Services Co. Ltd. for AI governance?

Winners Consulting Services Co. Ltd. (積穗科研股份有限公司) offers three distinctive advantages in AI governance consulting. First, we maintain active engagement with the latest international AI governance research — including studies like Agarwal and Nene's five-layer framework — ensuring that our recommendations are grounded in the most current academic and regulatory developments rather than outdated checklists. Second, we possess deep cross-framework expertise spanning Taiwan's AI Basic Law, ISO 42001, and the EU AI Act, enabling us to design integrated compliance architectures that satisfy multiple regulatory frameworks simultaneously without redundant implementation. Third, our diagnostic methodology is structurally rigorous: we apply the five-layer governance model to identify exactly which layer of an enterprise's governance chain is broken, producing board-ready reports and actionable remediation plans rather than generic compliance advice. We help Taiwan enterprises move from compliance aspiration to auditable, verifiable AI governance reality.

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