AI’s potential is undeniable, but the hidden security costs at the inference layer are a major concern for enterprises. Attacks targeting AI’s operational side are increasing budgets, risking compliance, and eroding customer trust, all of which impact the ROI and TCO of AI deployments.
Enterprises are excited about the insights and efficiency gains AI can offer. However, as they implement their AI models, they are realizing the challenges at the inference stage. This critical phase translates AI investment into real-time business value but is under attack, leading to unexpected TCO increases.
Security executives and CFOs are facing the consequences of defending AI systems against new attacks. Adversaries target the inference stage where AI is most valuable to businesses, resulting in high breach containment costs, compliance challenges, and trust issues. Without controlling costs at the inference stage, AI projects become unpredictable budget-wise.
AI inference is becoming a significant risk, according to technology leaders. Organizations often overlook securing the inference stage, leading to underestimated costs for monitoring systems, threat analysis, and patching mechanisms. Deploying third-party models without proper evaluation against specific threats and compliance needs can result in harmful outputs that damage brand trust.
Various threats, such as prompt injection, training data poisoning, and model theft, are actively targeting AI models. Adversaries exploit foundational security failures like leaked credentials to compromise AI systems. Implementing robust security measures and a zero-trust framework is crucial to protect AI environments from attacks.
To protect AI ROI, collaboration between CISOs and CFOs is essential. Budgeting for inference security from the start, implementing runtime monitoring, and adopting a zero-trust framework are crucial strategies. A CFO-grade ROI protection model should link security spending to TCO reduction, run cost-avoidance simulations, and quantify financial risks to justify security investments.
In conclusion, safeguarding AI investments requires a strategic approach that quantifies ROI protection, brand trust preservation, and regulatory stability. Strategic security investments at the infrastructure layer must be justified with financial metrics to ensure AI’s financial sustainability. Collaboration between CISOs and CIOs is key to effectively safeguarding modern businesses and managing the true cost of AI.
