As AI systems increasingly assume roles traditionally reserved for human professionals in high-stakes domains such as medicine, law, and finance, the absence of formal licensing frameworks exposes society to unprecedented risks.

AI agents, capable of providing medical diagnoses, legal counsel, or financial advice, hold the potential to enhance professional capabilities significantly. However, without proper regulation, these systems also pose substantial dangers.

As these systems take on more significant roles, a crucial question arises: How do we responsibly integrate AI into professions where human lives, rights, and well-being are on the line?

This article argues for creating a comprehensive AI licensing system that mirrors the rigorous standards applied to licensed human professionals. Through a review of scenarios from the medical, legal, and financial sectors, we explore the risks associated with unlicensed AI agents and propose a structured framework for training, certifying, and holding them accountable.

Note: By definition, an AI agent is like a digital helper that can think and act on its own or with a bit of guidance. It observes what’s happening around it, makes smart choices, and takes action to get things done.

The role of AI in professional domains

Traditionally, professionals such as doctors, counselors, attorneys, and other licensed experts have been entrusted with immense responsibility and power. These roles demand not only deep technical expertise but also a strong ethical foundation, professional judgment, and unwavering commitment to societal standards.

To earn the privilege of practice, human professionals undergo years of rigorous training, are bound by codes of ethics, and must obtain licenses that hold them accountable to the individuals and communities they serve. This system ensures that those operating in high-stakes domains are qualified, ethical, and answerable for their decisions.

Now, consider the emergence of AI agents offering medical diagnoses, legal counsel, or therapeutic support. In many respects, these systems are stepping into roles traditionally filled by human practitioners. However, unlike their human counterparts, AI systems do not take an oath to “do no harm.”

They are not held to the same rigorous ethical or accountability standards, and most importantly, they are not licensed. This creates a critical gap in oversight and responsibility. This paper delves into the urgent need for a framework that holds AI agents to the same level of responsibility as human professionals when they perform tasks on their behalf.

Use cases — Medical, legal, and financial AI agents

1. Medical AI Agents

Imagine an AI system acting as a medical agent, analyzing patients’ symptoms and reviewing their health records. This “doctor agent” sifts through vast medical databases, cross-referencing medical literature, patient histories, and similar cases to suggest a diagnosis and treatment options.

For a busy healthcare provider, this AI system appears to be a game-changer — streamlining diagnoses, offering evidence-based recommendations, and potentially catching rare conditions that could otherwise be overlooked.

However, now consider the scenario in which this AI provides an incorrect diagnosis. Perhaps the system failed to recognize a rare disease or misinterpreted an atypical symptom due to biases in its training data. The consequences of this mistake could be severe — the patient might receive ineffective or harmful treatment, or a life-threatening condition might go unnoticed.

In this scenario, determining accountability becomes murky. Is it the human doctor who relied on the AI system? The developers who trained it? Or the healthcare institution that implemented the technology without sufficient oversight?

Without a structured licensing framework, the responsibility may diffuse, leaving the patient vulnerable with no clear path to justice or recourse. Licensing AI agents in healthcare would ensure that these systems operate under the supervision of licensed practitioners, who remain accountable for their decisions, preserving the integrity and trust essential in medical practice.

2. Legal AI agents

Consider a different context — a legal one. An individual, unfamiliar with legal intricacies, consults an AI-powered legal assistant for advice regarding a dispute with an employer. The “attorney agent” scans through labor laws, case precedents, and the specifics of the client’s employment contract. Within minutes, the AI system provides a suggested course of action: Negotiate a severance package and if necessary, pursue litigation.

To the user, this AI advice appears authoritative, fast, and significantly cheaper than hiring a human attorney. However, the AI may have overlooked critical state-specific laws, or its recommendations might be based on outdated or incomplete legal precedents. If the individual follows this advice and loses the case, the financial losses could be significant, and the damage to the career could be long-lasting.

In such instances, who should be held accountable? The AI developer, for creating a flawed system? The employer, for using the system without proper safeguards? Or, no one at all, because the AI isn’t formally licensed?

This case illustrates the ethical and legal gray areas that arise without a licensing framework for AI agents in law. Licensing AI legal agents would impose a standard of accountability, ensuring that these systems can be trusted to provide accurate, responsible counsel while remaining under human oversight.

3. Financial AI agents

Now, imagine a scenario where an individual seeks advice on important financial decisions — whether to buy a house or continue renting; retire now or work longer; or have children sooner or later.

A “financial agent” AI system collects all of their financial data — savings, 401(k), mortgage or rent details, investments, tuition payments, car loans, as well as personal details such as age, marital status, geographic location, and employment status. Based on this vast pool of data, the AI offers tailored financial advice, suggesting optimal paths for wealth management or life planning.

While this sounds ideal — receiving quick, personalized advice without the costs of a human financial advisor — what happens if the AI overlooks crucial market trends or miscalculates risk factors? An incorrect recommendation could lead to serious financial repercussions, like purchasing a home at the wrong time or depleting retirement savings prematurely.

In this scenario, trust in the AI’s decisions becomes critical, yet without a human advisor to validate the AI’s suggestions and take responsibility for the outcomes, public trust may wane. A licensing framework for AI in financial services would ensure that these systems undergo rigorous scrutiny and are held to industry standards, providing peace of mind that the advice is sound and responsibly generated.

The need for licensing AI agents

The case studies above reveal a fundamental truth — while AI agents offer invaluable assistance, their increasing role in sensitive, high-stakes domains like medicine, law, and finance requires a responsible framework for oversight.

As AI systems continue to take on tasks that directly impact human lives, rights, and financial security, the absence of formal regulation becomes a significant risk. Without clear accountability, the consequences of AI errors could lead to life-threatening outcomes, legal misjudgments, or severe financial losses.

This paper advocates for the establishment of a licensing system specifically designed for AI agents that operate in professional capacities typically held by licensed human practitioners. Much like the rigorous licensing processes for doctors, lawyers, and financial advisors, AI agents must also undergo thorough testing, ethical evaluations, and certifications to ensure they meet the standards of their respective industries.

The goal of this framework is to create a system where AI enhances human potential without compromising the bedrock principles of safety, competence, and ethics that have long governed these professions. By linking AI licenses to human oversight, we ensure that AI remains a tool that amplifies human capabilities rather than replaces ethical accountability.

Licensed human professionals would serve as the ultimate safeguard, responsible for the actions and decisions generated by AI systems under their supervision.

In this way, we can foster innovation in AI while maintaining public trust in the professions that depend on accuracy, ethical conduct, and accountability. A formal licensing framework for AI agents not only protects individuals and society at large but also solidifies AI’s role as a responsible and reliable partner in high-stakes fields.

Proposed licensing framework

A licensing framework would parallel the standards applied to human professionals, ensuring that AI agents meet the necessary levels of competence, ethics, and accountability. Below are the key components of this proposed licensing framework:

1. Training and certification

AI agents must undergo a rigorous training and certification process, akin to the licensing requirements for human professionals. This would involve extensive testing of the AI’s decision-making capabilities, problem-solving approaches, and adherence to ethical standards. The training phase would assess the AI’s proficiency in handling complex, real-world scenarios relevant to its field—whether that be medical diagnoses, legal consultations, or financial advice.

Certification would only be granted once the AI has demonstrated competence in key areas, including ethical decision-making, accuracy, transparency, and reliability, similar to the way human professionals are certified by boards or regulatory bodies.

Example: A medical AI agent must pass comprehensive tests designed by medical boards that evaluate its ability to diagnose diseases, recommend treatments, and flag ambiguous cases for human review. The certification process could also involve practical simulations to assess the AI’s real-time decision-making under high-stakes conditions.

2. Accountability and oversight

While AI agents can operate independently to some extent, they must always be under the supervision of licensed human professionals who are ultimately responsible for the AI’s actions.

This supervisory role includes regular audits of the AI’s performance, reviewing its decision-making processes, and having the authority to intervene when necessary. The system would also include an audit trail, allowing for the tracking and assessment of decisions made by the AI, especially in cases where errors occur.

Example: In hospital settings, a licensed doctor would review the diagnoses made by an AI system. If an incorrect diagnosis is identified, the doctor would be responsible for correcting it and ensuring that the patient receives proper care, while the AI’s decision-making process is audited for further improvement.

3. Ethical standards

AI agents must strictly adhere to established ethical standards, prioritizing the well-being of the individuals they serve. These standards should be aligned with the ethical guidelines of the profession in which the AI operates.

AI systems must incorporate fail-safes that require human intervention when the AI encounters uncertainty or high-risk situations. Additionally, the system must operate transparently, providing clear explanations for its decisions to both professionals and the individuals impacted by those decisions.

Example: A legal AI agent advising a client on sensitive employment matters would be required to follow ethical guidelines similar to those governing human attorneys, including confidentiality and the avoidance of conflicts of interest. If the AI is unsure about state-specific regulations, it would flag the case for human review rather than making a recommendation.

4. Compliance

AI agents operating in regulated industries must comply with all applicable industry-specific regulations. This includes well-established laws such as the Gramm-Leach-Bliley Act (GLBA) for financial institutions, the Sarbanes-Oxley Act (SOX) for corporate governance, and the Health Insurance Portability and Accountability Act (HIPAA) for healthcare.

In addition, AI systems must adhere to emerging regulations such as the EU AI Act and maintain compliance with cybersecurity frameworks like the National Institute of Standards and Technology (NIST) Cybersecurity Framework. These compliance measures ensure that AI systems operate within the boundaries of the law and prioritize the security and privacy of sensitive data.

Example: An AI financial advisor would need to comply with GLBA regulations on protecting sensitive financial information while also following the NIST Cybersecurity Framework to safeguard its algorithms and data against cyber threats. Regular audits would ensure the AI’s continued compliance with these standards.

5. Continuous improvement

The licensing framework must be dynamic and adaptable, evolving alongside technological advancements and emerging challenges. AI agents should undergo periodic re-certification to ensure that they are operating according to the latest standards and best practices.

Furthermore, the framework should encourage ongoing collaboration between technologists, ethicists, industry professionals, and regulators to refine and update the system as AI technologies advance. Continuous learning processes should be built into AI systems, allowing them to improve their performance over time while staying within the ethical and regulatory boundaries established by the framework.

Example: A licensed AI medical agent could be updated annually with the latest medical research and guidelines, ensuring that its diagnosis and treatment plans reflect the most current medical knowledge. Re-certification processes could include testing on newly discovered conditions or recently established treatment protocols.

Conclusion

This isn’t just a theoretical exercise — it is an urgent and vital conversation about the future of professional practice and the ethical application of technology in domains that directly impact human lives, rights, and well-being.

The rapid deployment of AI in critical fields demands that we take a balanced approach — one that embraces innovation while safeguarding the trust, accountability, and ethical standards that have long defined our most respected professions. Licensing AI agents is not simply a matter of ensuring safety and competence — it is about preserving the very integrity of the professions they are designed to assist.

As AI continues to evolve, it must operate within a framework that upholds the values on which these professions are built. By holding AI agents to the same ethical and professional standards as their human counterparts, we can ensure that technological progress enhances — not undermines — society’s trust in healthcare, law, finance, and other critical fields.

Ultimately, licensing AI agents is about fostering responsible innovation that protects the public while enabling professionals to leverage the full potential of AI.

References:

1. Artificial Intelligence in Healthcare: Ethical Considerations and Applications – Journal of Medical Ethics, 2022.

2. AI in Legal Practice: Opportunities and Challenges – Harvard Law Review, 2023.

3. The Role of AI in Transforming Professional Services – McKinsey and Company, 2022.

4. Ethical Implications of AI in High-Stakes Domains – Stanford University Press, 2023.

5. AI Accountability: A Framework for Responsible AI Use – The AI Now Institute, 2022.

About the Authors:

Shivanku Misra serves as the VP and Enterprise Head of Advanced Analytics and AI at McKesson, a Fortune 10 legacy healthcare business.

Xin “Cindy” Tu serves as the Director of IT & Data Audit at Discover Financial Services. Misra, Turley, and Tu serve on the CDO Magazine Global Editorial Board.