Artificial intelligence is reshaping how we work and it\u2019s doing so at an incredible pace. In fact, 72%<\/a> of businesses use AI for at least one business function. From writing tools to data analysis, AI is woven into daily tasks without a second thought.<\/p>\n\n\n\n
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75%<\/a> of generative AI users aim to automate workplace tasks and utilize generative AI for work-related communications.<\/p>\n <\/div><\/div><\/div><\/div>\n\n\n\n
When asked about the speed of AI, fear dominates. According to survey data from JumpCloud\u2019s Q3 SME IT Trends<\/a>, 61%<\/strong> of organizations agreed that AI is outpacing their organization\u2019s ability to protect against threats.<\/p>\n\n\n\n
The first step in conducting an AI risk assessment is understanding what AI tools are in use across your organization. This requires a comprehensive inventory of all AI-related accounts and applications employees might be using\u2013whether they are IT-approved or not.<\/p>\n\n\n\n
Without this visibility, businesses risk unapproved SaaS applications slipping into daily workflows, leading to security and compliance gaps. There are a few ways for IT teams to approach SaaS discovery and find AI tools. These include:<\/p>\n\n\n\n
After identifying which AI tools are in use across your organization, the next step is to evaluate each vendor\u2019s approach to security and privacy. AI applications often handle sensitive data, making it critical to understand the practices of each vendor to prevent potential breaches and data misuse.<\/p>\n\n\n\n
When evaluating AI vendors and SaaS applications that use third-party GenAI for their services, IT and security leaders should consider the following key factors:<\/p>\n\n\n\n
These core questions give you a structured way to evaluate the security and privacy practices of each vendor, helping you ensure that only trustworthy tools are adopted within your organization.<\/p>\n\n\n\n
According to Splunk\u2019s latest security report, 91%<\/a> of security teams are utilizing generative AI, yet 65% admit they lack a full understanding of the implications.<\/p>\n\n\n\n
Key areas to consider include:<\/p>\n\n\n\n
Mapping these connections can uncover vulnerabilities, such as overly broad access scopes or unencrypted data exchange, and helps you ensure that only vetted, secure pathways are used for AI integrations.<\/p>\n\n\n\n
The final step into assessing AI risks in your organization is to look at how employees interact with AI tools daily. Clear communication and education are vital to making sure they understand the acceptable use of these tools, including which AI applications are approved and how to use them safely.<\/p>\n\n\n\n
Without a clear communication, employees may unknowingly bypass IT guidelines or engage in risky AI usage, potentially exposing your organization to security risks.<\/p>\n\n\n\n
To improve communication around AI use, consider the following factors:<\/p>\n\n\n\n
You can also add niche or newly launched AI tools to your inventory manually even before they are detected, ensuring full coverage. Then, IT administrators can easily manage access and report on usage.<\/p>\n\n\n\n
Ready to see how JumpCloud SaaS Management simplifies IT? Try it for free<\/a> to see it for yourself.<\/p>\n","protected":false},"excerpt":{"rendered":"