Which of the following should be a PRIMARY consideration when defining recovery point objectives (RPOs) and recovery time objectives (RTOs) for generative AI solutions?

Question

Options

• APreserving the most recent versions of data models to avoid inaccuracies in functionality
• BPrioritizing computational efficiency over data integrity to minimize downtime
• CEnsuring the backup system can restore training data sets within the defined RTO window
• DMaintaining consistent hardware configurations to prevent discrepancies during model restoration

• A
  3% (1)
• B
  3% (1)
• C
  83% (30)
• D
  11% (4)

Explanation

When setting RPOs and RTOs for AI systems, especially generative AI, the critical factor is the restoration of training data and model artifacts within the recovery window. Without this, restored systems may function inaccurately or incompletely, undermining business continuity. AAISM risk management principles emphasize: Recovery objectives must align with data protection requirements for both training and inference The ability to restore large-scale training datasets is primary, since downtime without them leads to operational and compliance risks. Computational efficiency and hardware consistency are secondary considerations, but not the primary drivers of RPO/RTO definitions. Thus, ensuring backup and restore capabilities of training datasets directly within RTO is the primary requirement.

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