The use of generative AI as shadow IT is becoming a growing concern in global enterprises. While shadow IT already poses several risks, the adoption of generative AI apps is exacerbating the problem and raising new security, privacy, and legal issues.
Shadow IT refers to the use of unsanctioned or unauthorized technology within an organization. It may involve employees using their personal devices or software without the approval or knowledge of the IT department. This can lead to decreased control over sensitive data, an increased attack surface, risk of data loss, compliance issues, and inefficient data analysis. These risks have been well-documented in various studies.
However, what sets generative AI apart from other shadow IT tools is its incredible growth and adoption rate. Some experts compare it to the early days of the internet, with the potential for unparalleled global growth. Companies offering AI opportunities are receiving significant attention, and adoption rates are skyrocketing. For example, ChatGPT, a popular generative AI app, recently reached 100 million users, with 1.6 billion visits to its website in June 2023. This level of adoption is unprecedented and could have game-changing implications.
The rapid adoption of generative AI raises genuine concerns among IT leaders, especially regarding security. Executives are becoming increasingly aware of the potential implications of using free generative AI tools. While these tools may offer convenience and productivity benefits, they also bring along licensing, copyright, legal, intellectual property, and misinformation concerns. Therefore, organizations must consider the risks associated with these tools and develop appropriate strategies to mitigate them.
Managing end-user behavior has always been a challenge for IT leaders. They have been striving to support enterprise end users while also securing sensitive data. However, generative AI apps like ChatGPT present new challenges in this regard. These applications offer compelling reasons for employees to bypass enterprise-authorized applications and use unsanctioned tools for completing business tasks.
To address these concerns, organizations need to implement robust security measures and educate employees about the risks associated with generative AI and shadow IT. This includes raising awareness about licensing and copyright issues, potential legal implications, and the importance of safeguarding intellectual property. Additionally, enterprises should consider deploying AI-specific security solutions to monitor and control the use of generative AI tools within their networks.
Furthermore, collaboration between IT departments and business units is crucial to strike a balance between data security and enabling employee productivity. IT leaders should work closely with business leaders to understand their needs and concerns regarding generative AI. By doing so, they can develop policies and guidelines that address the unique challenges presented by these tools while ensuring data protection and compliance.
In conclusion, the use of generative AI as shadow IT introduces new risks to global enterprises. While shadow IT already poses several challenges, the rapid adoption of generative AI apps amplifies these risks. IT leaders and executives must be proactive in understanding and addressing the security, privacy, and legal implications of using unsanctioned generative AI tools. By implementing robust security measures, raising awareness, and fostering collaboration between IT and business units, organizations can mitigate the potential dangers associated with generative AI as shadow IT.