Overall, it is important to remember that AI systems typically require constant monitoring and review cycles, rather than one-off deployment. This is because AI systems often combine rule-based logic with machine learning models, which evolve over time and can produce probabilistic outcomes rather than fixed decisions.
AI functions best as a sophisticated tool for uncovering hidden insights and providing tailored recommendations. To ensure clear accountability, this process must be supported by rigorous documentation, testing, and review throughout the entire AI system lifecycle.
People professionals should be involved in AI governance where it affects people. Where this crossover occurs, implementing governance systems - including training, system design and oversight - will be familiar territory for people teams. This is work already carried out across core areas of the profession.