– 2023 is being called the year of AI, with AI-powered tools being widely used in the workplace
– Many workers use AI tools not supplied by their business, leading to ethical, legal, privacy, and practical challenges
– Most organizations lack internal policies on generative AI
– Developing policies and standards now can prevent future issues
– There is a disconnect between adoption of AI and formal policies, with many workers perceiving AI usage as safe
– Common risks and challenges include overconfidence in AI capabilities and security and privacy concerns with accessing personal data
– Organizations must ensure they are using vetted AI tools that meet data security standards.
Many have described 2023 as the year of AI, and the term made several “word of the year” lists. While it has positively impacted productivity and efficiency in the workplace, AI has also presented a number of emerging risks for businesses.
For example, a recent Harris Poll survey commissioned by AuditBoard revealed that roughly half of employed Americans (51%) currently use AI-powered tools for work, undoubtedly driven by ChatGPT and other generative AI solutions. At the same time, however, nearly half (48%) said they enter company data into AI tools not supplied by their business to aid them in their work.
This rapid integration of generative AI tools at work presents ethical, legal, privacy, and practical challenges, creating a need for businesses to implement new and robust policies surrounding generative AI tools. As it stands, most have yet to do so — a recent Gartner survey revealed that more than half of organizations lack an internal policy on generative AI, and the Harris Poll found that just 37% of employed Americans have a formal policy regarding the use of non-company-supplied AI-powered tools.
While it may sound like a daunting task, developing a set of policies and standards now can save organizations from major headaches down the road.
AI use and governance: Risks and challenges
Developing a set of policies and standards now can save organizations from major headaches down the road.
Generative AI’s rapid adoption has made keeping pace with AI risk management and governance difficult for businesses, and there is a distinct disconnect between adoption and formal policies. The previously mentioned Harris Poll found that 64% perceive AI tool usage as safe, indicating that many workers and organizations could be overlooking risks.
These risks and challenges can vary, but three of the most common include:
- Overconfidence. The Dunning–Kruger effect is a bias that occurs when our own knowledge or abilities are overestimated. We’ve seen this manifest itself relative to AI usage; many overestimate the capabilities of AI without understanding its limitations. This could produce relatively harmless results, such as providing incomplete or inaccurate output, but it could also lead to much more serious situations, such as output that violates legal usage restrictions or creates intellectual property risk.
- Security and privacy. AI needs access to large amounts of data for full effectiveness, but this sometimes includes personal data or other sensitive information. There are inherent risks that come along with using unvetted AI tools, so organizations must ensure they’re using tools that meet their data security standards.
AI Eclipse TLDR:
The article discusses the challenges and risks associated with the rapid adoption of generative AI tools in the workplace. It highlights the need for businesses to implement robust policies and standards surrounding the use of these tools to address ethical, legal, privacy, and practical concerns. The article cites a Harris Poll survey commissioned by AuditBoard, which found that roughly half of employed Americans currently use AI-powered tools for work, but almost half of them enter company data into AI tools not supplied by their business. This lack of formal policies and standards poses risks and challenges for organizations. The article emphasizes the importance of developing policies and standards now to avoid future complications. It also discusses two common risks associated with AI usage: overconfidence and security/privacy concerns. Overall, the article emphasizes the need for businesses to effectively manage and govern the use of AI tools to mitigate potential risks.