Many companies already have large volumes of data, but much of it is not yet prepared for AI use. Challenges like inconsistent formats, weak traceability, and lack of ownership often hold back value, even when infrastructure is solid.

The first action is to treat data as a product, not a byproduct. This means assigning data owners, using standardized formats, implementing version control, and thinking ahead to how people downstream will use the data. When data is treated this way, it becomes reliable for AI.

Second, make observability and lineage standard practice. Organizations need clear visibility into where data comes from, how it has been transformed, and who has handled it. Without this context, trust breaks down and risks increase.

Third, embed governance from the ground up. That means policies about access, storage, classification, and quality are not just documents in a drawer but active parts of how people work. When leadership supports governance, it becomes more than compliance — it becomes part of the DNA of data culture.

Fourth, ensure data literacy is everyone’s responsibility. It shouldn’t be just data scientists who understand quality, biases, or appropriate use. Everyone from business leaders to operational staff must grasp what usable data means and how to interpret insights.

Fifth, integrate both structured and unstructured data as standard practice. Traditional databases alone are not enough. Documents, emails, sensor data, logs, and other less structured sources often carry indispensable insight — if managed with the same rigor as structured datasets.

The takeaway is clear: building an AI-ready organization isn’t just about technology; it's about creating trust in data, empowering people, and establishing systems that endure. By implementing these five actions, organizations lay a foundation for AI that’s not only capable but also ethical, sustainable, and aligned with real business needs.

Would you like help translating these actions into concrete steps for your organization? I can support you in crafting a data strategy, setting up governance frameworks, boosting data literacy, and integrating diverse data sources — so your organization’s data culture becomes truly AI-ready and resilient.
(CIO: 5 Actions to Build an AI-Ready Data Culture (September 2025), 2025-09-12)