In this exclusive interview with IT Voice, Dipesh Kaura, Country Director – India & SAARC at Securonix, shares his insights on India’s widening cybersecurity talent gap, the rise of burnout among security leaders, and how next-gen AI—including Agentic AI—is set to redefine the future of cyber defense, governance, and resilience.
IT Voice – How is India’s cybersecurity sector grappling with the growing talent shortage and burnout among professionals, and what role can AI, automation, and proactive organizational strategies play in bridging this gap and retaining top talent?
Dipesh Kaura- India is currently facing a major cybersecurity talent shortage, with an estimated gap of over 1.5 million professionals needed to meet the growing demand. This shortfall is being driven by the rapid pace of digital transformation across industries, which is increasing the need for skilled cybersecurity experts. (Source: multiple reports).
At the same time, burnout among cybersecurity professionals—especially Chief Information Security Officers (CISOs)—is becoming a serious concern. Recent data from Sophos shows that 83% of cybersecurity and IT professionals in India report experiencing burnout and fatigue. Contributing factors include limited resources to support cybersecurity functions, the repetitive and high-pressure nature of the role, constant alert fatigue from tools and systems, and the relentless pace of emerging threats.
To address these challenges, organizations need to take a more proactive approach in supporting their security teams. This includes engaging in regular, open conversations with CISOs to understand their pressures, using technology, automation tools, platforms, and investing in resilience through professional development.
Technology plays a significant role in easing the burden. Automation and AI are emerging as practical solutions to help bridge the talent gap. Platforms like Securonix automates security operations by using AI-driven analytics and SOAR capabilities to streamline alert triage, threat detection, and incident response. This reduces false positives, speeds up remediation, and frees security teams to focus on strategic tasks, boosting efficiency and reducing burnout.
To retain top cybersecurity talent, organizations should prioritize continuous training and upskilling, foster a culture of recognition, offer competitive compensation and benefits, and promote work-life balance. These measures not only build stronger teams but also help ensure long-term cybersecurity resilience.
IT Voice – What is Agentic AI, how does it differ from traditional security AI models, and in what ways is it poised to transform security operations while balancing potential risks and the human-AI collaboration dynamic
Dipesh Kaura- Agentic AI represents a new wave of autonomous, context-aware, and adaptive AI systems in cybersecurity. Unlike traditional AI that handles specific tasks like anomaly detection, Agentic AI acts as a virtual analyst—reasoning, learning, and coordinating across the entire security operations lifecycle with minimal human input.
Its biggest impact lies in automating repetitive tasks like alert triage, threat enrichment, and incident response, allowing SOC teams to focus on strategic decision-making. Unlike static, rule-based AI tools, Agentic AI continuously evolves and responds in real time with tailored actions.
Platforms like Securonix are well-positioned to lead this shift by embedding Agentic AI into their SIEM and SOAR frameworks, enabling smarter alert prioritization, faster response, and scalable threat mitigation.
While Agentic AI augments human capabilities, organizations must stay cautious of risks like over-reliance, adversarial attacks, and transparency issues. With proper governance, it can become a powerful teammate—enhancing speed, accuracy, and resilience in security operations.
IT Voice – Given the rapid evolution of cyber threats, why are traditional rule-based models and legacy SIEM/SOAR tools becoming ineffective, and how can enterprises adapt using AI-driven platforms and a layered zero-trust approach?
Dipesh Kaura : Traditional signature or rule-based security models are no longer effective in today’s dynamic threat landscape. These legacy approaches rely on known patterns and predefined rules, which fail to detect modern, sophisticated attacks that evolve rapidly are often remain hidden. Threat actors have become significantly more advanced, leveraging tools such as VPNs and cloud services to exploit vulnerabilities and bypass conventional defenses. State-sponsored groups and cybercriminals are deploying stealth tactics, polymorphic malware, and insider recruitment strategies that evade static security frameworks. In many cases, attackers now automate their methods, adapt malware to disable security software, and exploit zero-day vulnerabilities, outpacing traditional defenses.
Traditional SIEM/SOAR systems struggle to keep up with today’s fast-evolving threats. They generate too many low-fidelity alerts, rely on static rules, and lack the scalability, speed, and intelligence needed to detect complex attacks—leading to analyst fatigue and delayed responses.
To move from reactive to proactive defense, enterprises must adopt cloud-native, AI-driven platforms like Securonix. With advanced analytics, machine learning, and UEBA (User and Entity Behavior Analytics), Securonix delivers high-fidelity threat detection, automated response, and real-time behavioral insights. Its scalable, cloud-native architecture enables faster detection and reduced response times.
While the zero-trust model is essential, it must be paired with intelligent tools that correlate identity, access, and behavior. Securonix helps operationalize zero trust by enhancing visibility and enabling adaptive, automated defenses.To stay resilient, organizations must combine intelligent platforms, continuous threat intelligence, and user education—creating a security posture that evolves with the threat landscape.
IT Voice- As AI continues to evolve, how will it shift cybersecurity from reactive to predictive and autonomous defense, and what implications will this have for risk governance, emerging vulnerabilities, and the future skillset of security professionals?
Dipesh Kaura- AI is poised to play a transformative role in the future of cybersecurity—not just as a reactive tool, but as a proactive force capable of predicting, preventing, and mitigating threats before they fully materialize. According to Securonix’s latest whitepaper, the shift from basic automation and AI copilots to more autonomous “agentic” AI models marks a major evolution in cyber defense. These systems will increasingly operate with greater autonomy and intelligence, reshaping how security operations are managed.
AI is reshaping cybersecurity by going beyond traditional detection and response. Through real-time analysis of telemetry, user behavior, and threat intelligence, AI can spot early indicators of compromise and forecast threats before they materialize. With predictive analytics and contextual insights, organizations can isolate vulnerable assets and take preemptive action—dramatically reducing risk exposure.
The future lies in semi-autonomous and fully autonomous defense systems, powered by agentic AI—models that learn, adapt, collaborate, and make real-time decisions without human intervention. This evolution surpasses static rule-based systems, enabling faster, smarter, and more dynamic threat management.
Platforms like Securonix are at the forefront of this shift. With its AI-driven, cloud-native SIEM and SOAR capabilities, Securonix not only detects and responds to threats in real time but also continuously learns from new data. Its use of advanced UEBA, automated response, and threat intelligence integration supports adaptive security models and proactive risk mitigation.
AI is also transforming governance, risk, and compliance by automating policy enforcement, detecting anomalies, and aligning data flows with regulations—areas where Securonix’s compliance-focused features further strengthen an organization’s security posture.
As AI reshapes the landscape, security professionals must evolve too—blending technical, data science, and ethical oversight skills. At the same time, the growing use of AI by threat actors introduces new risks, from polymorphic malware to attacks on AI models themselves.
To stay ahead, organizations must adopt intelligent platforms like Securonix, embrace zero-trust frameworks, train teams on AI tools and risks, and implement strong AI governance with a focus on ethics, resilience, and explainability.
