A Practical Approach to Managing Modern Identity for a Stronger Security Posture

Despite its limitations, AI can be used today to strengthen an organization’s security posture. Here are a few best practices to help you get started immediately.

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Strengthening an organization’s security posture requires managing user identity effectively. Across devices, applications, networks, and more, ensuring the right person is accessing the right resources has become incredibly complex, and the rapid advancement of artificial intelligence (AI) technologies introduces both opportunities and challenges. Initially, the promise of AI in identity management conjured images of highly automated, secure systems that could recognize individuals through complex patterns of behavior and biometrics. That’s not where we are. While biometric adoption is on the rise in organizations, nearly eight in ten still require password-based systems for some resources.

Given AI’s current limitations and adjusting our expectations downward from futuristic visions to practical applications, organizations looking to bolster security protocols and improve user experience can’t ignore the complexities of data privacy and ethical considerations. Nor can they ignore that AI is often wrong. An error rate of 15% may not look terrible on paper, but when dealing with sensitive data like PII it may be catastrophic.

Organizations looking to enhance security measures through AI will need to approach new initiatives through thoughtful application and a strategic approach. 

AI’s capability to analyze vast datasets and identify patterns offers significant advantages in detecting anomalies and potential security threats. For example, AI can monitor user behaviors, such as login patterns and application usage, to detect deviations that may indicate a security breach. However, the efficacy of such systems varies, and the technology is still largely in its infancy in many aspects of enterprise computing.

The deluge of information and the need to process and make sense of billions of data points highlight the complexity of transforming raw data into actionable intelligence. Moreover, the reality of AI solving all security challenges is so far out as to not even be on the horizon. There are specific areas where AI can significantly contribute, such as automating routine tasks, enhancing natural language processing for better user interfaces, and refining anomaly detection mechanisms. However, achieving these requires careful planning, customization, and ongoing management to ensure the systems remain effective and do not inadvertently compromise user privacy or data security.

Improving security through AI today

Despite its limitations, there’s no question that AI can be used today to strengthen an organization’s security posture, even if it’s nowhere close to the science fiction future we’d imagined. Below are a few best practices to get started today.

Implement (or keep) multi-layered security measures: Relying solely on AI for security—for now—is a recipe for disaster. Organizations should adopt a multi-layered approach that includes traditional security measures such as multi-factor authentication (MFA), encryption, and regular security audits, with support from AI-driven tools in areas like data analysis or compliance.  At this stage, AI is best considered a tool to augment—not replace—existing security tools.

Customize AI solutions: Given the unique needs and challenges of each organization, customizing AI solutions to fit specific requirements is essential. Start by training AI models on small sets of organization-specific data to accurately recognize normal behaviors and detect anomalies. Eventually, organizations can refine AI tools to align with their IT infrastructure and user patterns, improving or enabling features like adaptive authentication and risk assessment.

Prioritize data privacy and governance: As AI systems process vast amounts of sensitive data, organizations must prioritize data privacy and adhere to regulatory requirements. This includes implementing data anonymization techniques, ensuring secure data access protocols, and considering local data processing to minimize the risk of data breaches and ensure compliance with data protection laws.

Foster AI literacy and ethical use: Educating the workforce about AI capabilities, limitations, and ethical use is crucial. This involves training IT staff and users on the benefits and risks associated with AI-driven identity management, promoting an ethical AI usage culture, and establishing guidelines for responsible AI implementation. Seek out industry resources and consider forming an AI ethics committee for maximum oversight and guidance.

Stay agile and informed: The AI and cybersecurity landscapes are rapidly evolving. We’re not putting the genie back in the bottle, so organizations should remain agile, ready to develop or adapt their AI strategies in response to new threats, technological advancements, and regulatory changes. Engaging with the cybersecurity community, participating in industry forums, and investing in continuous learning can help IT teams stay ahead of emerging security challenges.

By adopting these best practices, organizations can effectively manage modern identity using AI, enhancing their security posture while navigating the complexities of technological and regulatory environments.

Joel Rennich

Joel is the VP of product strategy at JumpCloud. Prior to JumpCloud, Joel was the director of Jamf’s Mac authentication and account management solution, Jamf Connect. Rennich joined Jamf as part of the company’s acquisition of his company Orchard & Grove and his open source application NoMAD. Before Jamf, Rennich spent a decade as an enterprise systems engineer manager at Apple and founded AFP548.com, the eminent website on Apple products and the mainstay of Apple system administrator education during the early years of macOS X.


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Joel Rennich

Joel is the VP of product strategy at JumpCloud. Prior to JumpCloud, Joel was the director of Jamf’s Mac authentication and account management solution, Jamf Connect. Rennich joined Jamf as part of the company’s acquisition of his company Orchard & Grove and his open source application NoMAD. Before Jamf, Rennich spent a decade as an enterprise systems engineer manager at Apple and founded AFP548.com, the eminent website on Apple products and the mainstay of Apple system administrator education during the early years of macOS X.