Singapore’s conversation around AI and the future of work has shifted decisively in recent months. During his recent May Day Rally address, Singapore’s Prime Minister Lawrence Wong emphasised that AI will reshape industries and jobs, but that Singapore’s priority is to ensure workers are equipped to adapt rather than displaced by change.
That is exactly the right conversation for business leaders to be having right now. However, in cybersecurity, there is a growing assumption that AI and automation bring major operational efficiencies that reduce the need for entry-level cybersecurity roles. It is a tempting proposition for organisations under pressure to optimise costs and accelerate productivity. But in practice, removing junior roles from cybersecurity teams is one of the fastest ways to undermine the industry’s long-term resilience.
AI’s expanding cybersecurity workload
In practice, AI is not reducing cybersecurity operations but expanding them.
Consider the case of Claude Mythos Preview as an example. As it accelerates the discovery of code vulnerabilities across key systems, organisations are likely to be engaged in a patching race in the upcoming months to ensure their systems remain secure when Mythos-like capabilities eventually become available to threat actors. Governments across the globe are signalling the urgency for organisations to address this challenge, with or without access to Mythos. This is going to require additional resources across the board.
Beyond code vulnerabilities, AI tools are generally extending security monitoring capabilities, translating into much larger volumes of daily security alerts. Today, it is estimated that 40% of all security alerts go entirely uninvestigated due to a lack of capacity among security operations. While automating analysis and triage is now possible with AI agents, there need to be humans at the helm of investigations and remediation to supervise the work of those agents and make the strategic decisions where judgement is required.
The proliferation of AI is also creating new attack surfaces, accelerating the sophistication of cyber threats, and introducing entirely new governance, identity, and data protection risks. Security teams need to secure not only people, networks, and devices, but also AI models, AI-generated data flows, machine identities, and increasingly autonomous systems.
This means the work is becoming broader, faster, and more complex.
Building the cybersecurity talent pipeline
Reducing early-career hiring because AI is capable of automating certain administrative or operational tasks is a strategic mistake. The technology landscape is in perpetual evolution, and as a result, new security challenges that require human judgement and skills will continue to emerge.
Today’s junior analysts become tomorrow’s incident responders, security architects, threat hunters, and CISOs. They’re also the ones that will secure and supervise future AI models and agents. Remove those early-career opportunities, and organisations will eventually find themselves competing aggressively for a shrinking pool of experienced talent instead of developing capability internally.
Investing in the next generation of cyber talent is investing in our industry’s ability to face and overcome future challenges, especially in a world where AI’s footprint in core business operations continues to grow.
Early-career professionals are entering the workforce with a level of familiarity and comfort with AI tools that previous generations did not have. That openness to experimentation and quick adaptation matters in a field where both threats and defensive technologies are evolving continuously.
Junior employees should be given exposure to areas such as AI governance reviews, cloud security assessments, threat modelling, digital forensics, and securing AI-enabled workflows. These are disciplines where practical experience will become increasingly valuable over the next decade.
National initiatives such as SkillsFuture and investments in AI capability development recognise that long-term economic resilience depends on helping workers evolve alongside technology, not excluding them from it. Cybersecurity shouldn’t be different, and leadership teams need to think beyond short-term productivity gains.
The organisations that will thrive in the AI era are the ones that successfully combine AI-driven efficiency with strong human capability, adaptable culture, and sustainable talent development.
AI will undoubtedly transform cybersecurity operations. But it will not eliminate the need for people who understand systems, context, behaviour, and risk.
Cybersecurity remains, fundamentally, a people-first discipline. In the age of AI, protecting the talent pipeline may become one of the most important security decisions organisations make.
