Today, most identity security strategies are heavily dependent on static, manual techniques that involve human effort and skill. However, as risk becomes more dynamic, traditional methods won’t be able to keep up. The complex nature of multi-cloud environments makes manual authorization and remediation of identity security issues impossible to scale.
AI-driven cyberattacks are using machine learning algorithms to identify security vulnerabilities, predict patterns, and exploit weaknesses at scale. Even malicious hackers with limited skill can leverage AI to conduct credential-based attacks, craft phishing emails, and enhance pretexting to create digital personas that masquerade as legitimate users.
We wanted to know: How are companies embedding emerging capabilities such as AI in their identity security strategies? To find out, we surveyed 1,800 IT (Information Technology) and security decision-makers across 21 countries, representing companies with over 500 employees in a wide range of industries. The results of our global identity security survey can help you compare your current identity security posture to your peers and prioritize investments as you develop your roadmap for the future.
There are many potential reasons organizations may rely on human skills, static policies, and manual processes for identity security.
Regardless of the reason, the reliance on human effort is likely providing organizations with a false sense of confidence. Some may not fully understand the evolving nature of identity-based attacks and underestimate cybercriminals' capabilities.
Those who haven’t experienced significant incidents may wrongly assume that their current manual security measures are sufficient. Focusing exclusively on human behavior may cause organizations to overlook the greater risk of machine identities that often operate without effective governance.
We found that there is a growing cultural shift towards embracing AI to surface information and save time, supported by human oversight to ensure accuracy and effectiveness. Most respondents expect to leverage AI in their identity security strategies in some fashion.
Because AI can quickly analyze large amounts of data from different sources, it can identify anomalies humans would never be able to detect and respond faster than manual methods. In addition, AI can automate repetitive tasks and avoid the common errors that humans are likely to make.
As we move forward, identity security programs should look to integrate AI for key use cases, such as:
It’s not enough to secure identities but also their interactions at every point in the identity attack chain, particularly in the cloud. By dynamically adjusting access privileges based on users' activities or contextual factors, you can respond promptly to emerging security threats and anomalies.
This approach reduces the risk of overprovisioning access rights and helps you make better use of IT resources. Most importantly, this approach avoids the costly repercussions of identity-related attacks experienced by most organizations worldwide.
The impetus toward automation in cybersecurity isn’t new. AI has simply accelerated it. The only thing that can slow it down is access to data. Data-hungry machine learning algorithms are only as intelligent as the information they can access.
For teams that are currently reliant on human effort and skill, the shift toward AI will require change management and trust. IT and security decision-makers will need to be comfortable with the accuracy, recency, and context of the data that AI uses to make recommendations before they hand over the reins for kinetic action. That said, it’s only a matter of time before dynamic, intelligent controls become table stakes for any identity security program.
For more detailed findings and analysis, download the complete results of Delinea’s 2024 global survey:
2024 State of Identity Security in the Age of AI.