Scott Beale
CC, Chief Executive Officer, ISC2
While AI can accelerate decisions, trust depends on secure data, strong governance and professionals who know when to challenge the technology.
Nearly nine in 10 (89%) cybersecurity professionals who use AI have experienced recommendations that led to incorrect outcomes according to ISC2’s AI Impact report. When that happens, half say their organisations ultimately hold human decision-makers accountable. AI may accelerate cybersecurity decisions, but it does not absorb the consequences.
As organisations race to adopt AI, building trust may depend less on the tools themselves and more on those responsible for using them.
AI influence in the workplace
AI is rapidly becoming part of business decisions, helping organisations analyse information, automate tasks and improve efficiency. As AI becomes more influential, questions about accuracy, accountability and trust persist.
While it can accelerate decision-making, professionals should remain cautious about AI’s reliability and when human intervention is required. Research from ISC2’s AI Impact report shows cybersecurity professionals are concerned about over-reliance on AI recommendations (62%), undetected AI errors that could scale rapidly across systems (61%) and reduced human judgement at critical decision points (56%).
Strong governance remains essential
AI systems depend on data. Inaccurate, incomplete or manipulated inputs can produce unreliable outputs and allow errors to spread at scale. Protecting data throughout its lifecycle underpins AI security, cyber resilience and digital trust.
Keeping humans in the loop
As organisations integrate AI into workflows, cybersecurity professionals remain involved in decision-making and oversight. ISC2’s AI Impact report found that 65% of cybersecurity professionals are spending more time deciding when to trust AI recommendations, while 63% spend more time reviewing or validating AI outputs.
Strong governance remains essential. Cybersecurity professionals identified understanding when to trust AI outputs (82%), when to override recommendations (80%) and establishing governance frameworks (80%) as critical priorities.
Organisations often answer technology challenges by buying more technology. However, trustworthy AI requires professionals trained to protect data, test output and know when to override the machine. Building those capabilities through education and professional development will be essential as AI adoption accelerates. Sometimes the best answer to a technology problem is not another tool, but a better-trained person.
