According to recent data, nearly 60% of employees are either using or about to use AI in the workplace. However, just over 20% of employers actually have policies around its use.
Company leaders and boards are asking the imperative question of whether to implement AI policies within their organization. If they are, how loose or restrictive should they be? How would they realistically be enforced? Here are four considerations for companies as they weigh internal policies that maximize generative AI’s potential while minimizing both known and unknown risks.
- Permissive Versus Restrictive. This goes to the heart of a company’s business: Is it in a regulated industry such as financial services or life sciences? This will impact how restrictive an AI policy needs to be. It will also vary based on whether they use AI for business-to-business or business-to-consumer applications. These and other factors will drive how much and how widely a company can use AI tools, both internally and in any externally facing products or services.
- General Versus Specific. Some companies want a more tailored policy, addressing allowable functions and use cases within specific departments, while others are adopting a more general policy that allows more flexibility and experimentation as AI rapidly evolves. While developing a policy, companies are seeking client or customer feedback, factoring in their expectations and requirements. Some companies may want a policy to be very prescriptive and enumerate specific use cases, resulting in limitations upon which departments can utilize generative AI solutions and how employees can use them.
- Approved AI Tools? There are many considerations that go into which generative AI tools should be deployed internally. An approved tool list can be difficult to enforce as the work lines blur between laptop and mobile, and home and office.
- Is there Actual, Meaningful Use? AI is one of the most innovative pieces of technology that we're seeing for businesses right now. There is an important distinction between adopting generative AI because everyone else is and adopting generative AI because it offers meaningful business use case potential. The desire to invest the time and the cost is also an important component of any policy consideration.
These insights are from our recent multi-part webinar, AI Advancements Part II: Navigating Obstacles for In-House Counsel - A Ground-Floor View. All five sessions are available on-demand for CLE credit.
For more information on crafting an AI policy, please reach out to Jennifer Stanley, intellectual property partner and technology transactions practice area lead, or visit our AI + Machine Learning Resource Hub for additional insights.