AI and Professional Liability: Managing the Emerging Risks in Your Practice

Artificial intelligence (AI) is a hot topic these days. Briefly, here is what the literature tells us about AI:

• AI involves computational systems and machines performing tasks associated with human intelligence, such as learning, solving problems, and making decisions.
• Some goals of AI include reasoning and developing logical solutions; mathematical and operations research optimization; reasoning and perception; formal logic; artificial neural networks; and other cognitive tasks.

Think of AI this way: The roots of AI can be traced, in part, to World War II, when a team of British cryptanalysts at Bletchley Park, including Alan Turing, developed machines to help break the German Enigma cipher and gather intelligence. This accomplishment contributed significantly to the Allied war effort, but the technology was designed for a specific purpose. Since then, we have continually developed reprogrammable digital computers capable of performing increasingly complex functions.

AI has pushed this frontier forward, becoming the next step in the evolution of the digital mind. Unlike the programmable computers of the past, which operated within specifically designed, narrowly defined tasks and instructions, AI moves the frontier forward through automated and increasingly autonomous reasoning.

Some consider AI to be the next industrial revolution, using vast amounts of information and continuous analysis at extraordinary speeds to identify and solve problems that humans may not foresee. Potential applications range from assisting with earlier cancer detection to helping researchers develop new chemical compounds for medical treatments.

However, AI also has a downside. Machine learning can produce biased results when systems learn from biased data or algorithms. AI can also be misused by rogue nations, terrorist organizations, and other malicious actors to develop dangerous technologies, including lethal molecules, drones, and autonomous battlefield systems.

Pro-Tip

Let’s talk about how AI affects a social worker’s practice.

According to Rough Notes (August 2026), AI is already embedded in records handling, fraud detection systems, and client service operations. AI can be a double-edged sword. While it can improve efficiency and enhance practice intelligence, legal liability may arise when AI contributes to biased outcomes, inaccurate disclosures, cybersecurity weaknesses, or poor autonomous decisions.

Courts, licensing boards, regulators, and plaintiffs’ attorneys increasingly focus not only on whether appropriate clinical and practice management processes were followed, but also on the resulting outcomes. Even a practitioner who demonstrates procedural compliance may still face a lawsuit when a client alleges harm.

Look inward at your practice and define your value proposition. Then look outward and ask:

1. Who in my sector is using AI successfully?
2. What problems are they solving for their practices and clients?
3. What are the measurable benefits?

Consider how your value proposition and practice processes can evolve to better serve your clients and improve your practice’s effectiveness.

Because AI is developing at such a rapid pace, many regulatory standards remain unsettled. AI governance still lacks widely accepted standards in many areas, leaving practitioners to navigate an environment of evolving expectations and potential liability exposures.

The following statistics illustrate notable trends in liability:

• A threefold increase in liability lawsuits during the past four years.
• A doubling of lawsuit awards and indemnity settlements.
• A tripling of internal practice investigation costs.
• A 50% increase in insurance premiums in high-risk medical malpractice sectors.
• One in three practices faces some form of negligence or dissatisfaction claim annually.

Pro-Tip

The more autonomy you grant AI, the greater the need for effective oversight and controls. Outsourcing AI does not necessarily outsource your liability.

Consider obtaining appropriate indemnification provisions from AI vendors, defining compliance standards, and establishing clear oversight and performance controls.

The hidden costs of AI-related liability to your practice may exceed the most obvious expenses. Liability insurance premiums, lawsuit settlements, and legal fees are only part of the potential financial exposure.

Other costs may include time diverted to investigations and testimony, responding to regulators, compliance remediation, forensic analysis of clinical practices, and disruptions to the financial management of your practice. Your professional reputation may also be at risk, potentially creating additional costs associated with restoring trust and credibility.

Pro-Tip

Do not rely on an insurance carrier to assume all AI-related risks. AI is more than a passing technology trend. It represents a structural shift in how practices operate, make decisions, manage information, and interact with clients.

AI also introduces a faster-paced environment into professional practice. This means practitioners should strengthen their overall practice oversight, including the oversight of employees, contractors, vendors, and AI tools. Practices should also consider developing an incident response plan in advance so they are prepared to respond quickly if a problem arises.

Being proactive can help reduce the risk of losses and growing liability allegations. Most importantly, establish thorough and effective documentation standards and processes. Documentation is often a critical component of professional negligence allegations and can play an important role in defending the decisions and actions taken by a practitioner.