Guide to AI data pipeline security and resilience | TechTarget
The continued rapid adoption of AI is increasing the volume of sensitive and proprietary data flowing through AI systems. This data includes customer and financial records, intellectual property, source code, employee information and operational data used to train models and power AI-driven applications. These AI pipelines have evolved from basic IT components into critical enterprise infrastructure.
Risks to data include exposure, poisoning, excessive privileges and more, making it essential for CISOs and IT leaders to ensure control, security and resilience across AI pipelines.
Let's examine how organizations can scale AI while managing the business risk created by its data infrastructure, focusing on the risks, protection strategies and leadership decisions required to secure AI pipelines.
What is an AI data pipeline, and why is its business impact so significant?
AI data pipelines are the systems and processes that collect, move, transform, store and prepare data for AI models.
Data typically...
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