This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
This Website Uses Cookies By closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
Although artificial intelligence (AI) has been around for quite some time, the adoption and evolution of AI-related technologies has dramatically advanced over the last year. One area that seems ready to benefit from AI is third-party risk management — that is, if AI can offer organizations an easier way to manage third-party vendor and supplier risks and ensure compliance with a complex regulatory landscape.
Organizations increasingly rely on third parties to deliver a wide range of goods and services, because it’s far more efficient and cost-effective than producing everything in-house. Unfortunately, this practice also increases vendor and supplier risk. Complex global supply chains make it incredibly difficult to have clear visibility into the security and risk management practices of a growing number of third parties. And how do security professionals mitigate risks they have zero visibility into? It’s a difficult but important task, because cyber criminals are increasingly attacking third parties in the supply chain to steal sensitive data and disrupt operations.