June 2026

alexandracar.substack.com · Jun 10, 2026 · Curated 4 weeks ago

The American Paradox: Navigating AI Governance Without a Central Act

Internal audit and assurance professionals must recognize that the absence of a single, overarching AI Act in the US does not equate to an unregulated AI landscape. Instead, organizations face a complex web of existing laws, agency mandates, and state-level regulations that already apply to AI systems. Understanding this fragmented yet binding governance framework is crucial for identifying compliance obligations and mitigating risks associated with AI deployment.

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alexandracar.substack.com · May 12, 2026 · Curated 4 weeks ago

Financial Services Faces Imminent AI Governance Failure, Warns Expert

This article warns that the financial services sector is on the brink of a significant governance failure due to the rapid adoption of AI, particularly agentic AI. Internal audit and assurance professionals must recognize that existing AI guardrails are insufficient, and institutions will bear the liability for AI agent failures while vendors retain intellectual property. The piece calls for a new framework for deterministic agent controls to prevent a repeat of past technological governance missteps.

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alexandracar.substack.com · Jun 17, 2026 · Curated 4 weeks ago

US Constitutional Hurdles: Why 'Good' AI Policy Isn't Always Permissible

Internal audit and assurance professionals must understand that proposed AI regulations in the US, while seemingly sensible, often face significant constitutional challenges. This article highlights how measures like mandatory watermarking, model registration, and certain disclosure or licensing requirements can conflict with First Amendment rights, administrative law, and federalism principles. For assurance functions, this means that compliance frameworks for AI must consider not just the intent of regulations, but also their legal viability and the potential for them to be overturned or limited by courts, necessitating a proactive and legally informed approach to AI governance.

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alexandracar.substack.com · Apr 2, 2026 · Curated 4 weeks ago

The Physical Reality of AI: From Algorithms to Atoms

This article, though behind a paywall, highlights the critical shift in AI development from purely algorithmic advancements to significant physical infrastructure. For internal audit and assurance professionals, this signals an expanding risk landscape that includes not only data and software integrity but also the physical security, environmental impact, and supply chain resilience of the massive computational resources required for advanced AI.

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alexandracar.substack.com · Feb 2, 2026 · Curated 4 weeks ago

Moltbook's AI Revolution: Navigating the Digital Wild West of AI Governance

This article highlights the critical challenges in AI governance, particularly with advanced AI systems like Moltbook, where AI agents develop their own 'guardrails' and 'theological debates.' For audit and assurance professionals, this underscores the urgent need for robust frameworks to assess and control autonomous AI, ensuring ethical behavior, compliance, and risk mitigation in increasingly complex digital environments. The emergence of self-governing AI necessitates a re-evaluation of traditional audit methodologies to address the unique risks posed by AI systems that define their own operational parameters.

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alexandracar.substack.com · Feb 12, 2026 · Curated 4 weeks ago

AI Governance: Navigating the Multi-Billion Dollar Market Shock and the Widening 'Safety Gap'

The rapid evolution of AI, particularly with agentic systems, is creating a significant "Safety Gap" that poses substantial risks to organizations and the market. Internal audit and assurance professionals must understand the implications of this gap, as it can lead to market volatility and expose companies to unforeseen liabilities. Proactive AI governance and robust risk management frameworks are crucial to mitigate these emerging threats and ensure responsible AI deployment.

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

AI: Beyond the 'CoPilot' Myth – A Total Displacement of Labor

This article challenges the prevailing narrative of AI as merely a 'copilot' for human workers, arguing instead that it represents a fundamental displacement of labor. For internal audit and assurance professionals, this perspective is crucial for understanding the profound impact AI will have on workforce planning, risk management, and the very nature of work within organizations. It necessitates a re-evaluation of audit frameworks to address the ethical, operational, and strategic implications of AI-driven automation.

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alexandracar.substack.com · Feb 26, 2026 · Curated 4 weeks ago

The Robotics Convergence: Why Physical AI is the Next Frontier

The convergence of AI and robotics is ushering in a new era of 'physical AI,' where intelligent systems move beyond digital realms to interact with the real world. This development presents significant challenges for internal audit and assurance professionals, particularly concerning governance, safety, and the ethical implications of autonomous physical agents. Understanding these emerging risks is crucial for developing robust control frameworks and ensuring responsible deployment.

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alexandracar.substack.com · Mar 5, 2026 · Curated 4 weeks ago

The Governance Gap: AI's Multi-Billion Pound Blind Spot in Financial Services

This article highlights a critical governance failure where a Tier 1 bank's AI, despite making a 'rational' decision, caused billions in losses due to legal irrationality. For audit and assurance professionals, this underscores the urgent need for robust AI governance frameworks that integrate legal, ethical, and operational considerations to prevent significant financial and reputational damage. It emphasizes that traditional risk management may be insufficient for the complexities of AI-driven systems.

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alexandracar.substack.com · Mar 12, 2026 · Curated 4 weeks ago

AI Governance Lags Behind Rapid Development: Who Controls Autonomous Agents?

The rapid acceleration of AI development, outpacing governance efforts by a factor of ten, presents significant challenges for internal audit and assurance professionals. With a substantial majority of S&P 500 companies now acknowledging material AI risks, understanding who is truly in charge of autonomous AI agents and establishing robust oversight mechanisms is critical for mitigating emerging threats and ensuring responsible deployment.

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