Why Your Organization Needs an AI Safety and Compliance Policy—Now
In today’s fast-evolving technology landscape, AI is at the center of countless innovations, transforming industries across the board.
Sentiment Analysis for HR and Employee Wellness:
Companies are increasingly using AI to monitor employee communications (like emails and chat messages) to assess workplace sentiment. AI can flag potential issues like burnout, declining morale, or toxic work environments, helping HR teams address problems early before they escalate.
3. AI-Enhanced Financial Auditing:
Accounting firms are leveraging AI to audit financial records more efficiently. AI systems can sift through vast amounts of transactional data, detect anomalies, and flag potential areas of concern in real time. This improves accuracy, speeds up the audit process, and helps uncover potential fraud or compliance issues that might otherwise go unnoticed.
4. AI in Real Estate Investment:
AI and LLMs are being used to analyze vast amounts of property market data to make investment recommendations. These systems can predict future real estate trends, identify undervalued properties, and even generate detailed reports on prospective investment opportunities based on market conditions, neighborhood changes, and economic indicators.
5. AI for Creative Product Design:
Companies in industries like fashion, furniture design, and consumer electronics are using AI to assist with creative tasks. AI can help generate innovative design ideas by analyzing current trends and past product successes. This is particularly unexpected in areas traditionally thought of as exclusively human-driven, like design and aesthetics.
Yet, despite AI’s potential, many organizations remain ill-prepared to handle the unique challenges it brings. If your firm or business is operating without a comprehensive AI Safety and Compliance policy, you may be putting your organization—and your clients—at risk. AI is not simply a tool for efficiency; it introduces complex ethical, legal, and operational concerns demanding careful oversight. Once a liability event occurs, various Executive Orders, local (and eventually federal) rules will be activated and the expectation is that any organization developing or using AI systems will have been testing, evaluating and storing data regarding those systems all along.
Introduction and Purpose
The adoption of AI across sectors presents numerous overlapping challenges for both non-governmental organizations and government agencies. These challenges include ethics, legal obligations, and project-specific requirements that must align with the ever-evolving technological landscape. Policies like this should address AI risks and ensure AI deployment adheres to the organization’s ethical, legal, and operational guidelines. By formalizing a set of clear principles, these policies will promote the safe and ethical use of AI within an organizations and also help minimize safety issues and liability.
Scope and Applicability
These policies would ideall cover two primary areas:
(1) the internal use of AI within the company and;
(2) the use of AI within the products and services offered to clients.
A key part of this AI system governance is identifying the systems affected and ensuring that both the internal and external application of AI technologies are safely managed.
Guiding Principles
Several guiding principles form the backbone of emerging laws, regulations and executive orders underlining AI Safety and Compliance policy:
• Non-Discrimination: AI systems must not perpetuate or exacerbate existing biases. To mitigate this risk, a solid policy should require measures identifying and addressing potential biases in the input and output data, algorithms, and decision-making processes employed by AI tools.
• Equity: The policy highlights the need to ensure that AI technologies provide equal access and serve diverse populations fairly, without favoring any particular group.
Transparency and Explainability
The emerging regulatory environment tis heavy on transparency. Governmental organizations and various interest groups are focused on ensuring that AI systems are designed and deployed in ways that are understandable to humans. Explainability is key—AI-driven decisions should be accompanied by clear documentation, allowing stakeholders to understand how the technology operates. Moreover, openness about the development, deployment, and impacts of AI systems is essential. Companies must maintain a willingness to share information about their AI capabilities, limitations, and goals with clients and the public when appropriate. From a liability standpoint, litigation in this area will always insist that the data behind AI system use be made available in discovery.
Accountability
Finally, accountability is crucial in the ethical deployment of AI. Your policy should ensure your organization takes responsibility for the AI systems it develops. Whether it’s ensuring fairness in decision-making or providing clear documentation of AI’s impact, companies must be fully accountable for their use of this powerful technology.
This post is non-exhaustive summary of AI Safety and Compliance policies I have been developing for various clients. Hopefully, this provides some food for thought for you in your practice and the clients you serve to ensure they are deploying AI systems with the foreknowledge of what should be done from the start to minimize liability going forward.