The use of artificial intelligence is becoming essential for companies to increase visibility and growth.
Security professionals, identity managers and IT operations teams are under increasing pressure to make quick decisions based on an endless alert, report and initiative to keep the company active and secure. According to a recent Cloud Security report, 59% of IT professionals surveyed say they receive more than 500 public cloud security alerts per day and 38% receive more than 1,000 per day. In addition, nearly half report that more than 40% of their warnings are false positives.
Companies are therefore increasingly turning to artificial intelligence (AI) and machine learning to address these challenges. It is not intended to replace valuable and scarce skills, but to enhance it using algorithms as a springboard to support overworked security analysts, identity management professionals and responders.
Gain visibility and efficiency with AI
In terms of identity management, companies ultimately want to do two things: reduce risk through better visibility and increase efficiency through automation. Through AI and machine learning, companies can gain new visibility and insight into the specific risks associated with user access. The powerful combination of AI and machine learning will have a significant impact on how organizations manage, control and secure all identities (human and non-human).
Use case for AI and machine learning
Conversely, using machine learning, organizations can gain more visibility into how employees are accessing resources and then regularly mapping them to “policy-based” work functions and organizational alignment. If security analysts detect abnormal activity, that activity and user can be flagged immediately and “sandboxed” to isolate any potentially malicious behavior that could constitute an incident or breach.
This visibility and analysis helps determine which process can be safely automated. For example, a newly hired professional in the accounting department will be given access to a specific application and resources. Policies can be developed to provide quick and efficient access to similar functions as defined by HR and enabled by IT. This is a very common use case for automation and a real-world example of how AI-driven identification can help in predictive analysis across organizations to reduce risk and make better use of rare security resources.
AI-powered identity gives customers the visibility and insight needed to understand and act on specific risks related to their user identity and access. Equipped with this capability, security, operations and IT teams can work together to create and scale enterprise-wide governance controls that will enable greater visibility and faster action. This reduces the overall risk. In addition, AI and machine learning can enable successful automation of important but “less risky” functions. The result? Less “work time” for technical resources and improved productivity for the company as a whole.
Thanks to AI and machine learning offered by the publisher’s IGA solution, companies can automatically adapt to changing environments and stay one step ahead of security issues. Artificial intelligence makes it possible for companies to secure and promote optimized production and better visibility.