Securing The Future How Ai And Zero Trust Are Reshaping Enterprise

Bonisiwe Shabane

-Oct 28, 2025, 9:35 AM

securing the future how ai and zero trust are reshaping enterprise

As enterprises migrate more of their infrastructure to the cloud, the stakes for security and compliance have never been higher. Traditional models of perimeter defense are no longer sufficient in a world where remote work, hybrid cloud, and AI-driven automation define daily operations. Organizations today are embracing Zero Trust architectures and AI-powered threat detection as the new standard for resilience. Sulakshana Singh, a Senior IEEE member and an editorial board member at the International Journal of Emerging Trends in Computer Science and Information Technology, has been at the forefront of this shift. With expertise spanning enterprise security, compliance automation, and scalable cloud services, she has consistently demonstrated how technical innovation can align with business impact. Across industries, the adoption of Zero Trust has accelerated, driven by the realization that legacy, perimeter-based approaches cannot contain modern cyber threats.

Gartner estimates that by 2027, more than half of enterprises will have adopted Zero Trust strategies as the backbone of their security programs. Singh’s work reflects this transformation. At IBM, she contributed to the Security and Compliance Center (SCC)—a product designed to centralize and automate compliance across the IBM Cloud platform. Her contributions included developing new features for microservices, deploying them across disaster recovery regions, and addressing vulnerabilities to align with OWASP standards. By upgrading services from JDK8 to JDK11 and optimizing infrastructure, Singh helped reduce operational cloud usage costs by an estimated $50 million annually, while simultaneously strengthening resilience. “This wasn’t just a cost-saving exercise,” she explains.

“It was about building a platform that could protect enterprises at scale—without slowing them down.” Kris Lahiri is Co-founder and Chief Security Officer at Egnyte, responsible for the company's security, compliance and core infrastructure. In the rapidly evolving landscape of cybersecurity, zero-trust architecture has emerged as a critical framework for protecting digital assets and sensitive information. As organizations struggle with increasingly sophisticated cyber threats and stringent data protection regulations, integrating artificial intelligence (AI) into zero-trust models has become a game changer. As distributed networks expand, endpoints are becoming increasingly critical within zero-trust architectures, requiring stronger security controls. AI is being integrated into zero-trust architectures to enhance security enforcement and threat detection, making access controls more dynamic.

Let’s examine the challenges and opportunities at this complex intersection of technology and regulation. The integration of AI into zero-trust frameworks represents a significant evolution in cybersecurity strategies. AI enhances zero-trust models by providing advanced threat detection, response and decision-making capabilities. This leads to a stronger overall security posture of organizations. One key area where AI is making a substantial impact is continuous authentication and authorization. AI-powered continuous authentication and authorization are integral to modern zero-trust architecture.

These systems utilize AI to analyze user behavior, device security posture and network conditions in real time, thereby making context-aware access decisions. By leveraging AI, organizations can implement dynamic authentication processes that go beyond traditional methods. For instance, AI can monitor user behavior patterns and flag any deviations from normal activity, triggering additional verification steps when necessary. This approach ensures that access permissions are continuously verified and updated. On a Wednesday afternoon in February 2024, much of America’s healthcare system ground to a halt. Doctors’ offices couldn’t process insurance claims.

Pharmacies were unable to supply prescriptions. Even military bases worldwide faced disruptions in providing essential medications. The cause? A ransomware attack on Change Healthcare, a subsidiary of America’s largest health insurer, UnitedHealth Group. One year on, the true scale of the attack has become clear: 190m Americans had their medical data stolen, and losses were estimated at US$2.87bn1 2 in the largest breach of health records in... This landmark moment in cybersecurity illustrates a troubling reality: even large organisations with significant resources remain vulnerable to cyber-attacks that exploit security gaps, and no organisation is immune.

Furthermore, attackers increasingly deploy artificial intelligence (AI) to increase their chances of breaching defences. “Most CEOs I talk to now view cyber-risk as the largest risk—even greater than geopolitical risk or natural disasters,” says Jay Chaudhry, chief executive of Zscaler, Inc., a cloud security firm. But defenders are not standing still. A new era of cybersecurity is here, one that combines Zero Trust architecture—in which every user and device must be continuously verified—with AI-powered defences to fight fire with fire. AI adoption is accelerating rapidly, and security is racing to keep up with the changes it introduces. While AI can transform employee productivity and workplace efficiency, it also amplifies existing data security challenges (which have often been deferred or neglected) and introduces some new ones.

Generative AI applications aren’t like traditional ‘deterministic’ applications that do the exact same thing every time you run them. Asking Generative AI image generation models to repeatedly “draw a picture of a kitten in a security guard uniform” is unlikely to generate the exact same picture twice (though they will all be similar). This dynamism creates new value for businesses. However, it also introduces new types of security risks and makes existing static security controls less effective against this AI generation of applications. This article will explore how organizations can leverage the symbiotic relationship between Zero Trust and AI to mitigate evolving security risks while still responsibly reaping the benefits of AI-powered innovation. The views and opinions expressed are those of Kishore Vutukuri and do not reflect the views of any organization or publication.

With users, devices, and workloads everywhere, the traditional security perimeter is disappearing. Emerging in its place are new boundaries defined by data access, context, and continuous validation. Now, autonomous AI agents are accelerating this shift, creating novel security challenges and demanding a far more sophisticated approach to identity and access management. Kishore Vutukuri, Enterprise Architect and CoE Head at Ernst & Young, has spent his career executing these very transformations. With a background at firms like Brillio, Netcracker Technology, and CSG, his developing perspective was only crystallized by a series of events in 2020: the formalization of Zero Trust Architecture in a NIST white... For Vutukuri, the experience made it clear to him that Zero Trust is an architectural mandate, not a buzzword.

"Zero Trust Architecture is about determining who can access the data, from where, from which devices, why, for how long, and how frequently. Based on those factors and the data's sensitivity, a policy must be in place to grant the right data to the right device, resource, user or agent." Zero Trust Architecture asserts simple but unforgiving... Ideally, the system would make doing the wrong thing difficult by design, he explains. But the arrival of AI introduces a critical new complication. New user in town: Modern security leaders must address an entirely new user category. "We traditionally had internal users, external users, and system users.

Now we have agents: a new user category," Vutukuri says. In the rapidly evolving landscape of healthcare, AI promises to revolutionize patient care, but it also brings significant risks. From algorithmic bias to data privacy breaches, the stakes are high. Effective AI governance is essential to harness the benefits of these technologies while safeguarding patient safety and ensuring compliance with regulations. This article delves into the critical challenges healthcare systems and pharmaceutical companies face, offering practical solutions and best practices for implementing trustworthy AI. Discover how to navigate the complexities of AI in healthcare and protect your organization from potential pitfalls.

At Trustible, we believe AI can be a powerful force for good, but it must be governed effectively to align with public benefit. Introducing the Trustible AI Governance Insights Center, a public, open-source library designed to equip enterprises, policymakers, and consumers with essential knowledge and tools to navigate AI’s risks and benefits. Our comprehensive taxonomies cover AI Risks, Mitigations, Benefits, and Model Ratings, providing actionable insights that empower organizations to implement robust governance practices. Join us in transforming the conversation around trusted AI into tangible, measurable outcomes. Explore the Insights Center today!

Securing The Future How Ai And Zero Trust Are Reshaping Enterprise

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