Part 9/12:
The liability inherent in AI-generated outputs necessitates robust governance frameworks:
Establish transparency, accountability, and incident management protocols.
Decide whether to build in-house governance capabilities or leverage external expertise.
Implement frameworks around data privacy, model bias, and ethical use to ensure responsible deployment.
The Technical Dimensions: Building the Foundation for Scale
1. Data Management and Quality
Effective AI hinges on high-quality data. Organizations must:
Manage data at the source, ensuring integrity and consistency.
Invest in annotation and bias mitigation, automating where possible.
Embrace platformization to streamline deployment and monitoring.
2. Infrastructure and Platform Scalability