How do you align data policies and standards with AI objectives and outcomes?

2 Define your data policies and standards

Data policies and standards are the rules and guidelines that govern how you collect, store, access, use, share, and dispose of data. They can help you ensure data quality, security, privacy, compliance, and ethics. However, they can also vary depending on the type, source, and purpose of data and AI. Therefore, you need to define your data policies and standards clearly and consistently, based on your data maturity, AI objectives and outcomes, and relevant regulations and best practices. You also need to communicate and enforce them across your organization and stakeholders.

4 Leverage data governance tools and techniques

Data governance is the process of managing and overseeing your data policies and standards. It can help you align your data policies and standards with your AI objectives and outcomes by providing you with the tools and techniques to implement, monitor, and evaluate your data and AI activities. Some of the data governance tools and techniques that you can leverage include data catalogs, data quality tools, data lineage tools, data access controls, data audits, data ethics frameworks, and data stewardship roles and responsibilities.

5 Foster a data-driven culture

Data policies and standards are not enough to align your data and AI strategies. You also need to foster a data-driven culture, which is a mindset and behavior that values and uses data as a strategic asset and a source of insight and innovation. A data-driven culture can help you align your data policies and standards with your AI objectives and outcomes by creating a common vision and language, encouraging collaboration and learning, promoting transparency and accountability, and rewarding data excellence and impact.