What are AI Key Performance Indicators (KPIs)?

• A. Metrics like accuracy, compliance adherence, and user adoption rate that monitor performance.
• B. Only CPU usage metrics.
• C. Only data transfer rates.
• D. Only number of models deployed.

Answer: (A)

AI KPIs measure how well an AI solution performs in real-world use, balancing accuracy, governance, and value to users. Accuracy shows how often the model’s outputs are correct for the task, giving a direct sense of effectiveness. Compliance adherence tracks alignment with regulatory, policy, and ethical requirements, ensuring the system operates safely and within bounds. User adoption rate indicates whether people actually use the tool and derive benefit from it, reflecting real-world impact and utility. Together, these indicators assess whether the AI delivers trustworthy results, follows rules, and is valued by stakeholders.

Other metrics like CPU usage, data transfer rates, or simply counting how many models are deployed focus on technical operation or deployment volume rather than the outcomes and governance of the AI system, so they don’t capture the full picture of AI performance and value.