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Introduction

Today’ s cybersecurity teams are overloaded, understaffed and unable to address a large percentage of alerts generated by their security tools. Respondents to a recent 451 Research study indicated on average they are unable to investigate 43 % of alerts in a typical day, and about one in five( 19 %) are unable to investigate more than 75 % of alerts. The reasons for this include high volumes of low-fidelity security signals; inadequate, siloed analytical tools; and inefficient, time-consuming response processes.

Improved analytics and early benefits from coupling generative AI with classic AI / ML have resulted in some improvement, while further gains from automation could reduce the burden on security staff by streamlining repetitive tasks. More recently,

GenAI and agentic AI have introduced greater flexibility in applying technology to security workflows through the modeling of reasoning, decision-making and task execution.

Today, these technologies are converging in hyperautomation – a set of approaches that aim to reduce burdens on security analysts and minimize risks of overlooked activity, freeing security teams to focus on high-priority, strategic tasks appropriate to their level of expertise.

Average percentage of alerts that SecOps teams are unable to investigate in a typical day

• 2020 – 37 %

• 2021 – 41 %

• 2022 – 48 %

• 2023 – 54 %

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