Artificial Intelligence (AI) attack vectors will force significant upgrades to traditional security frameworks

Anyone following recent news knows that AI is here to stay. As a unique and revolutionary tool—particularly in cybersecurity—AI poses a severe disruption to traditional security frameworks.

Security organizations rely on various established frameworks, including those from the National Institute of Standards and Technology (NIST), ISO 27001, and other widely accepted standards for asset protection. However, emerging AI-enabled attacks are so sophisticated that the security controls built into these traditional frameworks cannot adequately address these advanced threat vectors, leaving most organizations significantly exposed.

These frameworks remain valuable, but they face a critical limitation: they cannot effectively detect or map AI-driven vulnerability attacks to existing control families. The controls most corporations use simply weren't designed to handle AI-based threats. As a result, IT security professionals now need extensive specialized training in AI security detection to identify these threats. Traditional systems were built to detect attacks such as:

• SQL injection

• Cross-site scripting

• Command injections

• Known attack signatures

Because defending against AI-enabled attacks requires an advanced skill set, security violations can now occur within legitimate workflows, making them harder to detect. Organizations using traditional security frameworks are finding that detection times for AI attacks are increasing significantly. Security teams lack both the proper training and the indicators within their security controls needed to identify these attacks promptly. Most teams face a knowledge gap regarding how to inventory AI components within their own environments, let alone apply AI-specific security controls that current frameworks don't require.

Organizations must develop new technical capabilities. The days of relying solely on traditional security policies to detect threats are over. Advanced monitoring tools must be developed and implemented quickly to detect these sophisticated AI threat vectors. While this will be costly, organizations will have no choice but to make these investments to protect their data.

The bigger challenge lies in understanding AI technology itself. Security teams must comprehend how AI attacks work, as traditional security certifications don't cover AI attack vectors. Although the skills gained from these certifications remain valuable, they are no longer sufficient for the AI era. Organizations should immediately hire security assessment teams with AI-specific risk assessment expertise to evaluate their overall security frameworks and identify any blind spots or gaps that could expose their networks and data. They should also consider ISO 42001 certification as a standard for running, monitoring, and assessing their AI security maturity.

Going forward, all companies—from enterprises to small businesses—will need to invest heavily in security personnel with AI training or outsource to consulting firms with this expertise. The days of relying solely on commonly adopted security control policies like NIST and ISO 27001 are ending. With AI now a permanent fixture in our digital landscape, organizations must recognize the imperative to adapt quickly from a security perspective.