A data visualization call out card stating that 96% of business leaders believe artificial intelligence and machine learning can significantly improve decision making.
Given this steep upward trajectory in AI adoption, it is equally necessary to address the risks brands face when there are no clear internal AI use guidelines set. To effectively manage these risks, a company self employed data ’s AI use policy should center around three key elements:
Vendor risks
Before integrating any AI vendors into your workflow, it is important for your company’s IT and legal compliance teams to conduct a thorough vetting process. This is to ensure vendors adhere to stringent regulations, comply with open-source licenses and appropriately maintain their technology.
Sprout’s Director, Associate General Counsel, Michael Rispin, provides his insights on the subject. “Whenever a company says they have an AI feature, you must ask them—How are you powering that? What is the foundational layer?”
It’s also crucial to pay careful attention to the terms and conditions (T&C) as the situation is unique in the case of AI vendors. “You will need to take a close look at not only the terms and conditions of your AI vendor but also any third-party AI they are using to power their solution because you’ll be subject to the T&Cs of both of them. For example, Zoom uses OpenAI to help power its AI capabilities,” he adds.
Mitigate these risks by ensuring close collaboration between legal teams, functional managers and your IT teams so they choose the appropriate AI tools for employees and ensure vendors are closely vetted.
AI input risks
Generative AI tools accelerate several functions such as copywriting, design and even coding. Many employees are already using free AI tools as collaborators to create more impactful content or to work more efficiently. Yet, one of the biggest threats to intellectual property (IP) rights arises from inputting data into AI tools without realizing the consequences, as a Samsung employee realized only too late.