Algorithmic Consent, Liability, and Corporate Governance: How Kuwait Financial Institutions Must Make AI Work with Law

Executive Summary

Autonomous artificial intelligence (AI) is no longer an experimental tool in banking and securities activities; it has become core infrastructure. From high-frequency trading and robo-advisors to automated credit decisions, AI now influences transactions, risk assessments, and client outcomes in real time. As autonomous AI systems increasingly perform actions that resemble legal consent, often through processes that may not be fully observable or intelligible, a critical question emerges: How can the law determine whose consent is being given, and who bears responsibility for the consequences of an AI-driven decision?

This article examines the regulatory framework in Kuwait, draws on emerging international practice, and offers boards, general counsel, and CMA-licensed firms a practical roadmap for allocating AI liability and establishing effective governance.

Introduction

AI is rapidly moving from pilot projects to full-scale deployment in the finance and banking industries, which changes how decisions are made and executed. In the securities market, AI drives automated trading and portfolio management-executing trades in milliseconds according to market signals and predictive analytics. Robo-advisors, such as those qualified under Book 19 of the Kuwait Capital Markets Authority’s (CMA) bylaws, automatically rebalance portfolios according to the risk profiles of their clients. High-frequency algorithms process big datasets to optimize buy and sell decisions independently of human judgment.

In banking, AI is equally disruptive. Credit decisions and loan approvals are increasingly automated, and AI models make judgments based on creditworthiness using income, spending patterns, and alternative data such as utility payments. An automated underwriting system can approve or disapprove a loan application instantly, reducing processing time from days to minutes. AI also forms the backbone of fraud detection and risk management, since it monitors millions of transactions in real time for any abnormality and intercepts fraud. Predictive analytics further identify potential defaults or market risks, well before they become a reality, and enable proactive intervention.

Under this wave of automation, the critical legal question arises regarding who provides consent for transactions executed by an AI system, and who will be liable for its acts concerning banking and securities activities.

This is a question that goes to the heart of contract law, regulatory compliance, and corporate governance. While autonomous AI systems appear to give consent by the performance of actions-such as the acceptance of offers, or execution of trades-just as entities with vested legal personality would, the legal landscape is shifting. Liability no longer stops at one point but also diffuses horizontally across operational layers and vertically through governance structures, increasing exposure under contractual obligations.

First, we outline the legal capacity of autonomous AI systems and associated risks, then review available options to protect financial institutions and CMA licensed persons.

1) AI systems with legal personality

AI systems increasingly perform tasks such as accepting offers, executing trades, and rebalancing portfolios-functions traditionally associated with legal consent. This emerging concept has been referred to in various ways, but perhaps the most common term is “algorithmic consent.” Does algorithmic consent grant rights and impose liabilities by giving AI systems legal personality? The answer would appear self-evident at first blush: AI cannot be a legal person. However, judicial and regulatory positions are shifting, and, in many respects, are more subtle than may be expected.

Certain foreign courts in civil law jurisdictions have begun to examine whether autonomous AI systems can produce legally binding outcomes, thereby raising complex issues of accountability, consent, and enforceability in the digital era.

The concept of “algorithmic consent” is new, and there is no definition in the law for it yet. This would refer to a situation when an autonomous AI system performs certain contractual actions, such as accepting an offer, executing a trade, or negotiating terms. Some advanced platforms can even modify contract terms automatically before finalization.

This brings us to an important question: can artificial intelligence be regarded as having legal personality, such that a legal person might seek to disclaim liability by arguing that damage was caused by an AI system rather than its own acts or omissions? This question is particularly relevant where harm arises from hallucinations, where the system generates false information or inference errors, where the system misinterprets input and produces an incorrect outcome

The answer is no. Legal personality is conferred only for natural persons and on legal entities expressly recognised by law, such as companies and government institutions. The Kuwaiti Civil Code requires capacity, consent, and clarity for a valid contract – requirements that an AI system cannot satisfy. , There is no third legal category under Kuwaiti law that would permit artificial intelligence to hold rights or bear obligations independently of the legal person deploying it.

For instance, Article 3-2-2 of Book 19 of CMA Bylaws categorizes Digital Financial Advisory business models into two categories:

• Fully Digital Model: Very limited or no human interface with customers except for the technical support.
• Hybrid Model: The customers can discuss automated investment advice and suggestions with the employees.

At first glance, this might appear to imply that the CMA recognises  some form of legal personality for AI systems under the Fully Digital Model. This is not the case. Article 3-2-1 states the following: “The Digital Financial Advisor service provider analyzes the registered data using algorithms created for this purpose and, after analyzing the data entered, recommends the type of investment portfolio suitable for the Client.”

Therefore, under CMA, this places the ultimate responsibility with the human-based service provider, as the CMA-licensed persons and the banks, not the algorithm. AI is used as a tool and not as a legal actor. Consent and liability remain with the legal person fully in line with Kuwaiti Civil Code principles.

Although certain foreign courts in civil law jurisdictions have begun to acknowledge AI’s involvement in commercial transactions and explore whether AI might, in the future, be accorded a “sui generis legal status”, such recognition remains speculative. At present, these courts do not confer upon AI the status of an independent legal person. Contracts concluded by AI are valid, but only insofar as they are considered a continuation of the legal person deploying the AI – not because AI itself possesses legal capacity. They are introducing the concept of “delegated authority”,  meaning that when a legal person deploys AI, it delegates some decision-making authorities to the AI system, and the legal person remains legally responsible.

Furthermore, certain foreign courts in civil law jurisdiction issued some decisions that contracts negotiated by autonomous systems may be treated as valid, provided “appropriate safeguards” are in place. This is of particular importance in financial markets, where everyday thousands of transactions are negotiated by AI systems. In that respect, Courts accept outcomes produced by AI but treat them as actions attributed to the deploying human/legal person. AI systems are not regarded as having a legal personality, meaning they cannot hold rights nor bear liabilities. However, they undertake actions likely to expose the person that deployed them to legal responsibility.

Another risk that is increasingly visible in practice concerns cross-border AI systems provided by foreign vendors. Many financial institutions rely on models hosted, trained, or updated outside Kuwait. This raises complex questions of vendor liability, applicable law, and enforceability of contractual protections. When an AI model fails or produces a harmful decision, recourse against foreign providers may be limited unless institutions negotiate robust indemnities, audit rights, and service-level obligations. As AI supply chains become more globalised, the allocation of liability between local institutions and offshore technology vendors will become a defining governance challenge.

This reality brings us to an essential question: how should legal persons especially the CMA licensed persons, the banks and the insurance companies mitigate this risk?

Fundamentally, this is a matter of governance that needs to be adequately addressed by CMA-licensed entities, banks and insurance companies. Strong governance frameworks ensure that the “appropriate safeguards” ordered by some judicial authorities for legal persons deploying AI systems take real effect. With such governance, AI systems can fully realize their potential in operational efficiency while ensuring that legal certainty and client protection are not undermined.

2) Corporate Governance

Contract law, tort law, and corporate governance frameworks were built on the assumption that all legally relevant actions stem from human judgment. Autonomous AI systems break this link. They generate outputs whose internal logic is often opaque even to their designers, creating a structural mismatch between technological capability and the legal doctrines assigned to interpret it. Recognizing this conceptual gap is essential for developing regulatory and contractual mechanisms capable of attributing responsibility in a predictable manner.

Furthermore, explainability, the ability to understand and show how an AI system reached a particular outcome, is increasingly a supervisory expectation, and Kuwait may follow international standards. In the international financial sector, this requirement is closely tied to fairness, client protection, and demonstrating compliance. Institutions can no longer depend on opaque “black-box” models that cannot be explained. Whether in credit decisions, automated trading, or risk scoring, firms may soon be required to document the reasoning behind AI-driven outcomes. Explainability has therefore shifted from a technical feature to a core legal and governance obligation.

Corporate governance frameworks must now evolve to reflect the realities of AI-driven decision-making. International regulatory trends consistently place responsibility for AI risk at the level of the board and senior management. This means that AI-related risks must be treated with the same seriousness as credit, operational, and cybersecurity risks.

To meet emerging expectations, and mitigate the risks of AI use, financial institutions, CMA-licensed persons, and insurance companies will have to establish or review their AI policies and governance frameworks. Boards of Directors should assess whether their current oversight mechanisms provide sufficient protection against AI risks. Board of directors of financial institutions and CMA licensed persons must:

• establish an AI committee;
• maintain sufficient technical expertise to understand its AI systems;
• verify that models operate within approved risk appetites;
• implement robust model-risk management policies, including validation and periodic testing;
• renegotiate outsourcing contracts for cross-border AI providers to include indemnities, audit rights, model-validation requirements, and clear liability allocation;
• oversee documentation, auditability, and explainability;
• challenge management regularly on AI exposures and the effectiveness of oversight mechanisms;
• ensure staff training enhances resilience; and
• consider AI-specific insurance to cover AI risks and mitigate exposure

Clear policies, documented audit trails, and consistent monitoring are no longer optional. They form the basis of accountability and demonstrate that the institution understands—and controls—the AI systems it relies on. As AI becomes embedded in core business functions, governance obligations will continue to expand, making proactive oversight essential.

As AI becomes more autonomous, Kuwait’s regulatory framework may evolve to address model governance, explainability standards, outsourcing risks, and liability allocation for AI-driven decisions. Future regulatory initiatives may include sector-wide guidance on model validation, mandatory documentation standards, and clearer expectations for board oversight. Institutions can prepare by reviewing governance practices now to ensure early alignment with emerging supervisory expectations.

Conclusion:

AI is transforming financial services, but the legal framework remains firmly grounded in human accountability. Institutions that deploy AI without clear governance structures risk operational disruption, compliance breaches, and reputational harm. The first significant AI-driven dispute in the region is a matter of when—not if.

As regulatory expectations evolve in Kuwait and globally, financial institutions will need governance frameworks that ensure explainability, documentation, and clear allocation of responsibility. Those that invest early in these safeguards will be better prepared to demonstrate compliance, respond to supervisory inquiries, and maintain the confidence of clients and regulators.

Effective AI governance is no longer a technical challenge—it is a strategic and legal priority. Institutions that take proactive steps today will be best positioned to navigate future regulatory developments and preserve their resilience in an increasingly automated financial landscape.

Key Takeaways:

• AI systems are increasingly embedded in financial decision-making, but Kuwaiti law assigns responsibility solely to the institution deploying the AI—not the AI system itself.
• Liability from AI use can diffuse across departments and governance layers, making robust internal controls essential.
• Explainability, documentation, and auditability are becoming legal requirements in financial services, not just technical preferences.
• Cross-border AI service providers pose jurisdictional, contractual, and enforcement risks that require careful vendor-management strategies.
• Boards and senior management are now expected to exercise active oversight of AI risk, similar to credit, operational, and cybersecurity risks.
• Institutions that strengthen AI governance today will be far better positioned for upcoming regulatory developments and supervisory expectations in Kuwait.