Artificial intelligence, an opportunity for companies.
The use of artificial intelligence is becoming essential for companies to gain visibility and growth.
Security professionals, identity managers and IT operations teams are under increasing pressure to make quick decisions based on an endless stream of alerts, reports and initiatives aimed at activate and protect the company. According to a recent cloud security report, 59% of IT professionals surveyed said they receive more than 500 public cloud security alerts per day, and 38% receive more than 1,000 per day. . Additionally, nearly half report that more than 40% of their alerts are false positives.
As a result, organizations are increasingly turning to artificial intelligence (AI) and machine learning to meet these challenges. It is not intended to replace valuable and minimal expertise, but rather to augment it by using algorithms as a springboard to support overworked security analysts, identity management professionals, and responders.
Have visibility and efficiency in AI
When it comes to identities management, companies ultimately want to do two things: reduce risk through better visibility and increase efficiency through automation. With AI and Machine Learning, organizations gain new visibility and insight into specific risks associated with user access. The powerful combination of AI and Machine Learning will have a huge impact on how organizations manage, control, and secure all identities (human and non -human).
Use case for AI and Machine Learning
Customers use machine learning to improve their identity risk management posture. Through examples such as peer group analysis and machine learning -based processes, organizations can begin to gain visibility into identity -based anomalies, whether from the perspective of permissions or user activity rules that ” not in the policy. “
Conversely, by using machine learning, companies can have more visibility into how employees access resources and then regularly map them to “job-based functions. in policy ”and organizational alignment. If security analysts discover unusual activity, that activity and the user can be immediately flagged and “sandboxed” to isolate any potentially malicious behavior that could be an incident or violation.
This visibility and analysis helps determine which processes can be safely automated. For example, a newly hired professional in the accounting department will be given access to a specific set of applications and resources. Policies can be created to quickly and efficiently grant access to anyone performing a similar function 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 -enabled identification can help predictive analytics across the organization to reduce risks and better utilize scarce security resources.
AI-driven identity gives customers the visibility and insights they need to understand and act on specific risks associated with user identity and access. With this capability, security, operations, and IT teams can work together to create and measure enterprise-wide management controls that will allow greater visibility and faster action. This reduces the overall risk. Additionally, AI and Machine Learning can enable successful automation of critical but “low risk” functions. Results? Less “work time” for technical resources and improved productivity for the entire organization.
Thanks to the 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 problems. Artificial intelligence makes it possible to secure companies and also promotes optimized production and better visibility.