India’s digital economy is growing rapidly. This can be seen from the fact that India’s digital economy is set to grow to 20% of GDP by 2030 from the current 8%. As the digital economy expands, the attack vector has increased substantially, bringing India into the crosshairs of several international hacker groups. This surge in digital activities underscores a pressing challenge for India’s cybersecurity landscape: a shortage of skilled professionals.
This is corroborated by ISACA’s State of Cybersecurity 2023 report, which highlights that this scarcity impacts 40% of all Indian teams. A skills gap further exacerbates the problem–with expertise lacking primarily in soft skills, cloud computing and security controls emerging as standout areas. As digital advancements and cloud initiatives surge, this shortage will be amplified. The scarcity of proficient professionals to manage the burgeoning number of identities within enterprises persistently affects identity security, illustrating a significant issue. Further, expertise in critical domains such as cloud security and Zero Trust architectures remains insufficient.
Reimagining strategies to bridge these gaps and fortify India’s cybersecurity posture is essential in this context. GenAI and Machine Learning (ML) technologies are becoming increasingly integral; they can serve to upskill existing teams, addressing hiring challenges and enhancing the overall defense strategy.
The role of GenAI
To tackle these immediate challenges, organisations can embrace GenAI and ML technologies. This strategic adoption equips them with tools that not only address skill gaps but also bolster existing teams, enhance productivity through automation and reinforce defensive strategies. Robust processes and people practices underpinning GenAI and ML can potentially optimise IT operations and elevate security organisations across their operational spectrum. These technologies enable a spectrum of advancements from the sustained operation and management of daily business tasks, to scaling systems for evolving needs and even implementing innovative processes that transform operations altogether. Additionally, cybersecurity careers are elevated by relieving professionals from mundane manual duties.
Bridging Skill Gaps with GenAI and ML
In the identity security landscape, particularly in policy optimisation, risk mitigation, and threat detection, GenAI and ML offer vast potential. For example, an AI-driven system can create policies–a process that traditionally demanded a significant amount of labor. This can now be streamlined to provide prescriptive recommendations within minutes. This swift implementation empowers teams to reduce risks without needing manual analysis, significantly boosting efficiency.
In security operations centres (SOCs), ML algorithms similarly analyse vast volumes of identity-centric threat data in real time. They integrate seamlessly with security orchestration, automation, and response (SOAR) systems. This optimal integration enhances the workflow for responses, lessening the workload on human analysts, and thereby improving the overall security posture.
Further, GenAI tools facilitate graduate-level cybersecurity education, curtailing human-induced security oversights and mishaps. Organisations can promptly discern problematic user activities – before they intensify – by leveraging tools such as AI-driven user behavioral analytics (UBA). By automating system configurations to alert on anomalies, we expedite investigating and resolving potential issues.
Investing in people to elevate security
It is crucial to empower cybersecurity professionals with relevant skills. Initiatives such as lunch-and-learn sessions and online training opportunities can significantly impact this endeavor. Moreover, specialised programs like identity security courses supplement professional development and contribute directly to job satisfaction and retention.
Addressing India’s Unique Challenges
Forty percent of cybersecurity teams in India suffer from understaffing, and they lack essential soft
skills as well as expertise in cloud computing. It is, hence, imperative to invest in upskilling initiatives. Organisations must prioritize training and development to navigate the evolving threat landscape. Organisations must hence invest in the synergy of GenAI and ML technologies supported by human expertise to bolster cybersecurity efforts. This strategy bridges skill gaps, fortifies identity security programs, and reignites passion for cybersecurity professionals.
