June 2026

alexandracar.substack.com · Mar 19, 2026 · Curated 4 weeks ago

The Last Mile of the Human Driver: Navigating AI Governance in Autonomous Systems

This article from The Responsible AI Review, curated by Alexandra Car, Chief AI Officer at Breeple.ai, delves into the critical implications of AI governance, safety, and sustainability as autonomous systems, particularly in driving, become more prevalent. For audit and assurance professionals, this highlights the escalating need for robust frameworks to assess the risks and ethical considerations associated with AI-driven technologies, especially as human control diminishes. Understanding these challenges is crucial for developing effective audit strategies and ensuring responsible AI deployment.

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alexandracar.substack.com · Mar 27, 2026 · Curated 4 weeks ago

The AGI Governance Gap: Why Oversight Lags Behind AI Capability

This article highlights a critical disconnect between the rapid advancement of Artificial General Intelligence (AGI) capabilities and the lagging development of robust governance frameworks. For internal audit and assurance professionals, this signals an urgent need to proactively assess and address the emerging risks associated with AGI deployment, focusing on the practical implementation of governance from policy to code. The absence of adequate governance creates significant control gaps and potential for unforeseen consequences, demanding immediate attention to ensure responsible and secure AI integration within organizations.

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alexandracar.substack.com · Apr 15, 2026 · Curated 4 weeks ago

AI's Goliath vs. Law's Paper Shield: Why Current Legal Frameworks Fail to Govern Autonomous AI

This article argues that existing 20th-century legal frameworks are inadequate for governing 21st-century autonomous AI systems. For internal audit and assurance professionals, this highlights a critical and growing risk landscape where traditional compliance and regulatory oversight mechanisms may be insufficient. Understanding this gap is crucial for developing robust AI governance strategies and ensuring organizational accountability in an evolving technological and legal environment.

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zhaomichelle.substack.com · Jun 24, 2026

AI Regulation: What Auditors Need to Know About Emerging Enforcement and Testable Compliance

This article provides a critical look at the evolving landscape of AI regulation and its practical implications for auditors. It highlights that AI risk is no longer theoretical, with real-world enforcement actions emerging from various regulatory bodies and legal challenges. For internal audit and assurance professionals, understanding these developments is crucial for identifying and mitigating organizational exposure to AI-related legal and reputational risks, particularly concerning data governance, continuous monitoring, and the trustworthiness of AI system records.

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radicalcompliance.com · Jun 22, 2026 · Curated 4 weeks ago

Prediction Markets: Navigating the Murky Waters of Employee Misconduct and Compliance Risk

This article delves into the complex compliance implications of employees participating in prediction markets, particularly when confidential company information is involved. It highlights the challenge for audit and assurance professionals in distinguishing between ethical breaches, privacy violations, and direct compliance risks that could lead to significant regulatory scrutiny or financial harm for the organization. The piece emphasizes the need for clear policies that address the misuse of confidential information, while also cautioning against unintended consequences of such policies.

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normanmarks.wordpress.com · Jun 22, 2026

Is Corporate Risk Appetite Truly Relevant for Business Decisions?

This article challenges the conventional wisdom surrounding corporate risk appetite statements, arguing that they often fail to directly influence day-to-day business decisions. For internal audit and assurance professionals, this perspective is crucial for re-evaluating the practical utility and focus of risk appetite frameworks within their organizations, prompting a shift towards more granular, context-specific risk analysis rather than broad, abstract statements.

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zhaomichelle.substack.com · Jun 21, 2026

Navigating the AI Regulatory Landscape: A Crucial First Step for Internal Audit

Internal audit professionals must prioritize understanding the evolving global AI regulatory landscape before auditing AI systems. This proactive approach allows auditors to identify and mitigate significant regulatory risks, which often carry the most substantial financial and reputational consequences for organizations. By aligning audit strategies with emerging laws and frameworks, internal audit can guide their organizations toward robust AI governance and compliance, avoiding costly reactive measures.

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richardchambers.com · Jun 21, 2026

Business Continuity Management: A Critical Risk Internal Audit Must Address

New research reveals a significant gap between organizations' confidence in their business continuity plans and their actual performance during disruptions. Internal audit professionals must recognize that traditional approaches to BCM are insufficient in today's complex risk landscape, which includes escalating third-party dependencies and emerging AI-related challenges. This article urges internal auditors to critically evaluate BCM programs, focusing on integrated capabilities, realistic testing, and a deep understanding of interdependencies to ensure organizational resilience.

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linkedin.com · Curated 5 weeks ago

Requirements vs. Controls: Clarifying the 'What' and the 'How' in GRC

This article clarifies the crucial distinction between 'requirements' and 'controls' within Governance, Risk, and Compliance (GRC). It emphasizes that requirements define the desired outcomes, while controls are the specific actions and safeguards implemented to achieve those outcomes and mitigate risk. Understanding this difference is fundamental for effective GRC programs.

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zhaomichelle.substack.com · Jun 19, 2026

Auditing AI: Bridging the Gap Between Governance Claims and Verifiable Assurance

This article highlights the critical and growing need for robust AI auditing as organizations rapidly deploy AI systems. It argues that while AI governance budgets are increasing, a significant gap exists between having policies and implementing effective, verifiable assurance functions. Internal audit professionals are uniquely positioned to address this gap by leveraging existing risk management skills and adapting them to the probabilistic and complex nature of AI, focusing on independent evidence and understanding distinct AI failure modes.

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