Shadow Artificial Intelligence (AI) data breaches are costing companies an extra $670,000 per incident on average, states a recent report by IBM. Shadow AI refers to AI tools used without authorization by a company’s employees. These breaches carry a higher financial impact than standard ones.
Shadow AI is a rising concern in the fintech sector. Employees often turn to unauthorized tools to speed up their tasks. Yet, this exposes companies to greater security risks. Unregulated AI use can result in data breaches, leading to severe financial and reputational damage for businesses.
Indeed, IBM’s report aligns with recent data from a survey by Cybernews. The survey shows that 59% of companies have suffered data breaches due to shadow AI use.
The Real Expense of Shadow AI
The financial burden of a shadow AI data breach is immense. Companies bear an extra $670,000 on average per incident. This cost is in addition to the usual expenses related to standard data breaches, significantly increasing the total financial impact.
Several factors contribute to this increased cost. Firstly, the detection and mitigation of shadow AI breaches often need specialist skills and resources, raising operational expenses. Secondly, unauthorized AI tool use can cause more extensive data breaches, potentially impacting more customers and leading to higher compensation payouts. Lastly, the reputational harm from these breaches can result in a loss of customer trust and revenue.
These findings highlight the need for strong data security measures and strict AI tool regulation within a company. It’s vital for businesses to oversee their employees’ AI tool use and ensure they’re used securely and with authorization. This proactive strategy can safeguard companies from the expensive fallout of shadow AI data breaches.
