In an interview with TimesTech, Girish Hirde, Global Delivery Head at InfoVision, highlights how the company is leveraging artificial intelligence to transform cybersecurity. From redefining Zero Trust to combating sophisticated malware and addressing cloud-native challenges, Girish shares how AI-driven solutions enable proactive defense, regulatory compliance, and innovation. His insights shed light on how enterprises can build resilient, secure, and scalable digital ecosystems in today’s evolving threat landscape.
Read the full interview here:
TimesTech: AI is becoming a powerful enabler in cybersecurity. How is InfoVision leveraging AI to enhance cloud security resilience in the face of today’s evolving threat landscape?
Girish: At InfoVision, we see AI as an essential enabler in building resilient cloud security, especially as threats become more complex and persistent. We’ve made AI the backbone of our cloud security strategy, embedding it across our managed detection and response systems to deliver intelligent automation, real-time threat visibility, and rapid response. Our NextGen MDR platform empowers us to predict and neutralize risks across multi-cloud and hybrid environments, learning from behavior patterns, usage anomalies, and threat intelligence signals to stay several steps ahead of potential breaches. We’re not just detecting known threats; we’re identifying the unknowns, the subtle deviations that hint at insider attacks or sophisticated malware. Our AI power cyber solutions continuously evolve, allowing us to dynamically enforce Zero Trust policies without disrupting user experience. We’ve also integrated AI with our containerized and cloud-native security tools, giving our clients flexibility and speed without compromising protection. This approach allows us to deliver cloud environments that are not only secure and scalable, but also adaptable—enabling innovation while keeping critical assets safe.
TimesTech: The Zero Trust model has become a key pillar of modern security frameworks. In what ways is AI redefining Zero Trust—especially in dynamically validating identities and user behaviors?
Girish: Zero Trust has become a strategic foundation for modern security, and artificial intelligence is redefining how this model operates in real-world enterprise environments. We rely on AI to move from rigid identity checks to a more fluid and responsive validation process that adapts to user context in real time. Rather than simply checking credentials at the point of login, our systems continuously assess factors like device health, access history, location, and behavioral signals to determine whether a user should maintain access. If someone behaves differently than usual or accesses resources from an unexpected device or region, AI helps in applying stricter controls or trigger alerts without slowing down trusted users. This continuous evaluation allows us to scale Zero Trust intelligently while maintaining user experience and operational efficiency. This helps us protect assets proactively while supporting the agility businesses need in today’s dynamic and hybrid digital environments.
TimesTech: Traditional malware detection tools often fall short against emerging threats. How is InfoVision using AI and machine learning to detect and mitigate sophisticated or previously unknown malware strains?
Girish: Today’s evolving cyber threats require quicker, smarter responses than traditional malware detection tools can provide. That’s why we’ve made artificial intelligence and machine learning the cornerstone of our strategy to detect and stop advanced threats using our NextGen EDR, APT, and MDR solutions. Rather than depending on outdated static signatures, our technology examines behavior across files, memory, and network traffic to catch even the most elusive threats, including fileless and polymorphic malware. Our AI-powered platforms continuously adapt by learning from global threat trends and leverage predictive models to detect irregular activity in real time. For instance, we can identify ransomware attacks in their early stages by spotting unusual encryption patterns and swiftly isolating compromised systems. Our deep learning models also track subtle changes across devices and user behavior to uncover stealthy attacks that typically slip past traditional security tools.
TimesTech: There’s a shift in the industry from reactive to proactive cybersecurity. Can you share how AI-driven systems are helping organizations predict and prevent security incidents rather than just respond to them?
Girish: Proactive cybersecurity is reshaping how organizations defend their digital ecosystems, and we are harnessing the full potential of AI-driven systems to enable this shift from reactive to anticipatory defense. Our AI power cyber solutions continuously ingest and analyze Organization-wide logs including user behavior, network logs, device telemetry and threat intelligence feeds to detect patterns that indicate emerging risks. For example, if a legitimate user suddenly accesses sensitive systems outside their usual hours from a new device the AI flags this anomaly and initiates an automated response such as limiting access or requiring step-up authentication. In another scenario if an endpoint begins executing scripts that mimic known attack kill chains our system can isolate the device before the malware spreads. These capabilities are not dependent on predefined signatures but are powered by machine learning algorithms that evolve over time. We also simulate attack scenarios using AI to stress-test environments against future threats which helps prioritize fixes and close security gaps. This kind of predictive defense enables businesses to address threats before they materialize, which enhances operational continuity and ensures long-term resilience in today’s ever-evolving threat landscape.
TimesTech: With the growing adoption of cloud-native architectures and AI workloads, what new challenges are emerging for cloud security—and how is InfoVision addressing these with integrated solutions?
Girish: We are increasingly dealing with a cloud ecosystem that is not just dynamic but also algorithmically intensive, where AI workloads introduce entirely new dimensions of risk. The ephemeral nature of cloud-native architecture, combined with the complexity of distributed computing, brings forth challenges like inconsistent visibility, ungoverned data flows, container escape vulnerabilities and exposure of machine learning models to adversarial manipulation. What we have done is architect a security framework that treats these variables not as exceptions but as the new normal. We employ AI not only for defense but also for understanding context in real time. For instance, our systems can trace lineage and behavior of containers, scan IaC templates pre-deployment, and flag anomalies in data sets feeding AI power cyber solutions. We also reinforce identity boundaries through adaptive access models, use federated learning to preserve privacy while improving detection, and integrate tightly with DevSecOps pipelines to catch misconfigurations before they’re ever deployed. This enables us to secure innovation without slowing it down.
TimesTech: With your vast experience across standards like PCI DSS, HIPAA, and ISO 27001, how do you balance regulatory compliance with the implementation of cutting-edge technologies like AI in enterprise security ecosystems?
Girish: We understand that regulatory compliance and innovation must move in tandem, not at odds. Our experience across standards like PCI DSS, HIPAA, and ISO 27001 allows us to architect enterprise security ecosystems that are not only resilient but also audit-ready. As we integrate advanced AI-driven solutions, we embed compliance as a native layer within our security architecture. This means every AI model we deploy, whether it is for threat detection, behavior analysis, or identity validation, is developed and governed through secure data pipelines that respect privacy mandates and data residency requirements. We ensure continuous control validation, automate evidence collection for audits, and apply policy-as-code frameworks to enforce compliance at scale. At the same time, AI enables us to enhance compliance by identifying misconfigurations, unauthorized access patterns, or unencrypted sensitive data in real time, thus improving both security posture and regulatory alignment. This strategic alignment of AI innovation with regulatory rigor allows enterprises to modernize securely while staying fully compliant.
