Transforming operations to embrace artificial intelligence (AI) is the leading challenge for organisations in every sector right now. Arguably, urgency is even greater in the technology sector, where leaders are acutely aware of AI’s potential to boost productivity and efficiency. In the cybersecurity subset of technology, the drive is stronger still, as vendors seek to mitigate AI-accelerated cyberattacks and help customers react faster, protect better, and achieve more with the limited budgets that characterise today’s economy.
There’s a real sense of high-stakes around AI adoption, underlined by commentators such as John Chambers predicting that we will see “50% of Fortune 500 companies disappear and 50% of the executives of the Fortune 500 disappear” due to a lack of skills, understanding, and an inability to adjust to the speed of an “innovation economy driven by AI” – evolve your business or it will be replaced.
Evidence is already emerging to support this premise, as well as the contradictions it is creating. We surveyed 750 senior cybersecurity professionals in the US, UK, and Australia, who told us that the drive to adopt AI in cybersecurity is coming inexorably from the boardroom and senior executives. However, they also reported that one of the biggest blockers to deploying AI in cybersecurity is a lack of management buy-in. This paradox highlights the fact that leaders recognise the need to harness the benefits of AI, but are uncertain about its tactical applications and, therefore, hesitant to support them. This leaves those in the operational space struggling to achieve a mandate to move forward.
The shape of the AI-powered workforce: avoiding a generational divide
Assumptions about the impact of AI on employment compound this uncertainty. We’re currently seeing businesses cutting entry-level hiring on the premise that AI will make junior roles redundant. While this undoubtedly delivers short-term cost reductions, it relies on organisations retaining their senior security practitioners to play the critical role of human-in-the-loop overseeing AI systems. It also severs the pipeline of talent coming into the business, therefore creating a skills gap down the line as senior practitioners move on, losing that critical element of business context.
Rather than cutting entry-level recruitment as part of a short-term economy drive, companies must recognise the value that fresh, agile mindsets bring to the business and tailor their workforce development strategy accordingly. Digital-native technologists, unconstrained by established processes, appear to be quicker to adopt AI and use it more naturally as part of their workflow. These employees still need to learn from more experienced professionals to develop a solid security mindset, but the learning can go in the other direction; experienced team members need to be open to changing how they work, too.
Building a sustainable, skilled cybersecurity workforce will mean creating an environment where the experience of established team members and the ingenuity of new ideas from early-career entrants are equally valued, and collaboration between them is rewarded.
Evolving the SOC with AI
Alongside achieving team balance, organisations must also ensure that AI supports employees in the most appropriate use cases. Our surveyed cybersecurity professionals identified immediate use cases for AI that will answer productivity and efficiency demands. Alert triage – either fully automated or with a human in the loop – and vulnerability assessment were the most popular, reflecting the areas where SOC analysts are most under pressure from both volume and velocity of information.
Agentic AI offers strong potential to relieve this burden, meaning that the role of a Tier 1 SOC analyst will look very different in future, becoming more focused on proactive threat hunting, AI oversight, and contributing to strategic risk reduction. This will require a complementary skillset, and organisations should be prepared to invest in training – even for more experienced analysts as their role evolves.
Acting faster but looking further ahead
John Chambers says today’s Fortune 500 executives will struggle because they “were trained to move at the speed of a five-year cycle as opposed to a 12-month cycle”. But despite this focus on speed, acting fast should not come at the expense of longer-term strategic thinking that looks over the horizon at risks and opportunities to position the business for future success. Organisations must do both to succeed in the AI era.
However, boards and senior leaders must recognise that the “expertise” needed to achieve both speed and long-term sustainable value does not look the same as it once did. It isn’t decades of broad experience in finance or legal fields. Instead, it might be deep experience in a niche but relevant technology field, or innovation in an aspect of cybersecurity that is highly relevant to the organisation’s sector. There is also immense value in identifying the pain points of teams on the ground, and the human skills and training needed so that, when solutions are proposed, leaders understand the value they’ll deliver.
We need a flattening of hierarchies with greater collaboration between senior leaders and cybersecurity practitioners to overcome the leadership paradox and build cybersecurity strategies – and the correctly skilled teams to implement them – that are fit for purpose in the years ahead.
