1 week Ago
Arun Shrestha , BeyondID CEO & cofounder, has 20+ years in enterprise software with leadership roles at Oracle, Sun, SeeBeyond & Okta. getty Zero trust has long been a foundation of cybersecurity, built on the principle of never assuming trust and always verifying. As AI-powered threats grow more sophisticated, organizations must evolve beyond conventional perimeter-based security to an identity-first zero-trust model—one that continuously verifies users, detects anomalies in real time and leverages AI to automate security decisions.
Legacy security architectures rely on static rules and predefined perimeters. However, cybercriminals no longer play by those rules. AI-powered cybercriminals now bypass firewalls, manipulate trust signals and weaponize stolen credentials to infiltrate networks undetected.
The numbers don’t lie: Studies show that 90% of breaches stem from identity-based attacks, and AI-powered phishing scams have increased by 135% year over year. Traditional security methods—like VPNs, firewalls and one-time authentication—are proving ineffective against AI-driven threats that adapt in real time. This is why an AI-driven, identity-first zero-trust strategy is no longer optional.
For too long, identity and data security have been treated as separate disciplines. That divide has created blind spots, allowing attackers to exploit gaps between access management and data protection. A single compromised credential, if left unchecked, can escalate into a full-scale breach.
Deepfake technology has made social engineering attacks more convincing than ever, with AI-generated voices and video impersonations fooling even the most experienced security professionals. Traditional security methods often rely on static authentication—verifying a user at login and then granting broad access for the rest of the session. But AI-powered threats are fluid, capable of mimicking legitimate users and adapting in real time.
This is where AI-driven identity security makes a difference. An identity-first zero-trust model powered by AI continuously assesses risk and dynamically adjusts access. If an employee logs in from their usual location but an access attempt is detected in another country minutes later, AI can instantly trigger additional verification or block access altogether.
Unlike traditional multifactor authentication, which only checks identity at the start of a session, AI-driven continuous authentication monitors behavior throughout, flagging anomalies before they escalate into full-blown breaches. Microsegmentation is another crucial aspect of AI-driven zero trust. By isolating different parts of the network, it limits an attacker’s ability to move laterally after breaching an account.
AI can automatically detect high-risk access attempts and quarantine affected systems, preventing an isolated breach from escalating into a full-scale incident. AI-powered identity-first security is crucial, yet many organizations face challenges transitioning from outdated systems. Legacy infrastructure often struggles to support real-time identity verification, and enhancing security can frustrate users if poorly implemented.
Relying solely on internal teams or viewing cybersecurity as a one-time investment also creates vulnerabilities. To succeed, organizations must adopt strategic approaches. A hybrid deployment strategy allows phased implementation of zero-trust models, minimizing disruption.
AI-driven behavioral analytics can detect unusual activity in real time, reducing friction for trusted users while increasing scrutiny when needed. Microsegmentation and least privilege access further limit potential damage by restricting movement within networks. Meanwhile, ongoing threat intelligence updates help organizations stay ahead of evolving risks.
Success requires viewing security as a continuous investment. Combining adaptive AI technologies with proactive strategies ensures both protection and a seamless user experience. By blending thoughtful planning with modern tools, organizations can build a secure, resilient identity-first security framework.
The security perimeter is gone, and AI-powered threats evolve faster than traditional defenses can respond. Security teams are inundated with alerts, often drowning in false positives while struggling to detect real threats. AI-powered Managed Identity Solutions address this challenge by automating identity verification, streamlining security workflows and eliminating manual bottlenecks.
By integrating identity, device and network security into a unified framework, organizations can achieve real-time threat mitigation and significantly reduce breach risks. The key to staying ahead is an adaptive zero-trust model that continuously verifies identity, detects behavioral anomalies and automates responses before breaches occur. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives.
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