By Diwakar Dayal, Managing Director and Area Vice President – India & SAARC at SentinelOne
Artificial intelligence is changing not just how organisations defend themselves against cyber threats, but also what they need from the people responsible for that defence. As security tools take on more alert triage, investigation and response tasks, the role of cybersecurity professionals is shifting towards validating findings, recognising unfamiliar threats and making decisions that require context and judgement. For India, the challenge is to ensure that workforce capabilities evolve alongside this growing automation.
The scale of India’s cybersecurity talent challenge is reflected in the Data Security Council of India’s Indian Cyber Security Skilling Landscape 2025–2026. According to the report, 73% of surveyed enterprises reported limited availability of skilled cybersecurity candidates, while 63% cited gaps in candidates’ practical, hands-on capabilities. These findings highlight a critical priority: alongside adopting advanced security technologies, organisations must develop professionals equipped to manage an increasingly complex threat landscape.
Cybersecurity roles are being redefined
Security operations have traditionally relied on analysts reviewing alerts, correlating information across tools and investigating suspicious activity. AI-driven automation can now handle parts of these workflows, helping teams process large volumes of security data and prioritise potential threats more efficiently.
But automating routine tasks does not eliminate complexity. It changes where expertise is needed. When an AI system flags suspicious behaviour, a security professional must determine whether the finding represents a genuine threat, understand its potential impact and decide what action is appropriate.
When a system encounters an unfamiliar attack pattern or produces an unreliable assessment, human judgement becomes even more important.
This shift is particularly significant as enterprises adopt agentic AI. Systems that can access applications, interact with data and execute actions introduce questions around permissions, accountability and unintended consequences. Security teams must understand how these systems operate, assess whether their actions remain within authorised boundaries and intervene when behaviour deviates from expectations.
The future security professional will therefore need more than familiarity with established tools. The role will increasingly combine technical security expertise with analytical thinking, AI literacy and the ability to evaluate machine-generated findings.
From operating tools to validating decisions
The implications for workforce development are substantial. Skills in endpoint security, network defence and threat detection remain foundational, but professionals increasingly need practical experience in AI-assisted investigations, identity security, cloud environments and automated response.
They must also learn to question automated outputs rather than accept them at face value. This includes recognising false positives, identifying gaps in detection, understanding how systems reach conclusions and determining when an incident requires escalation. As automation takes on more operational responsibility, the ability to exercise sound judgement becomes a defining professional capability.
Organisations should consequently rethink how they assess cybersecurity talent. Training completion and certifications can demonstrate foundational knowledge, but they do not necessarily establish whether someone can investigate a complex incident under pressure. Practical capability must be demonstrated through realistic scenarios in which professionals interpret incomplete information, validate AI-generated findings and make defensible decisions.
Building capability requires practical experience
Enterprise leaders should begin by mapping the skills required for their specific security environments. A security operations analyst may need training in AI-assisted triage and investigation, while a security architect may require deeper expertise in AI system security, identity controls and secure integration. Professionals responsible for governance must understand the risks associated with automated decision-making, data access and accountability.
Role-based upskilling can make these investments more effective than generic training programmes. Simulated incident exercises should test whether employees can distinguish malicious activity from legitimate behaviour, investigate unfamiliar attack patterns and respond appropriately when automated systems fail or produce conflicting findings.
Organisations should also introduce controlled exposure to AI security testing, including assessments of system permissions, data handling and the potential misuse of AI-enabled workflows. Performance should be measured through demonstrated competence, such as investigation quality, decision accuracy and response effectiveness, rather than participation alone.
These programmes must be continuous. As threats and AI capabilities evolve, teams need regular opportunities to practise new techniques, review incidents and update their approach. Equally, experienced professionals should have clear career pathways that reward specialised expertise and encourage knowledge-sharing across teams.
An opportunity for India’s cybersecurity ecosystem
India’s technology services industry and expanding digital economy create an opportunity to develop cybersecurity talent capable of supporting both domestic enterprises and global operations. Achieving this requires collaboration between employers, educational institutions, industry bodies and technology providers to align learning with the demands of modern security operations.
The focus should be on combining strong technical foundations with hands-on experience in AI-enabled security. Professionals entering from adjacent fields such as software development, data science and cloud engineering can also contribute, provided they receive structured security training and opportunities to demonstrate practical competence.
For enterprises, this is a strategic workforce priority, not simply a recruitment challenge. The effectiveness of security automation will depend on whether organisations have people capable of supervising it, challenging its conclusions and taking responsibility for consequential decisions.
India’s cybersecurity future will be shaped not by how much work can be automated, but by how intelligently people and machines work together. As AI assumes more operational tasks, investing in the judgement, adaptability and practical skills of security professionals will be essential to building a workforce capable of defending an increasingly complex digital economy.