AIs silent partner - the Data Product

Just as real intelligence comes from having formed beliefs on a knowledge base developed through life Artificial Intelligence requires a reliable knowledge base to learn from.

Data products are critical for many AI applications because they represent the essential building blocks for developing intelligent systems. Quite simply without good data foundations AI would not be intelligent at all and would erode business value rather than add to it.

This is not to say that businesses cannot find value from 'off the shelf' AI solutions today. There are many use cases which businesses can tackle today without being concerned with data underpinnings but soon enough data will creep onto the critical path. Even for those use cases careful consideration should be given to the measurement of incremental value driven by the AI solution.

Here's a few reasons why investing effort in developing robust data products is so important:

Quality - High-quality data products ensure that AI models are trained on reliable and accurate information, leading to better predictions and decisions.

Re-usability- Data products are curated and structured datasets that can be reused across different AI projects, reducing redundancy, saving time, supporting scalability and fuelling innovation

Regulatory Compliance - Defining the appropriate data governance framework related to each use case helps in maintaining compliance with data handling regulations. This in turn helps ensure AI systems are ethical and transparent in their operations.

In short data products are the backbone of successful tailored AI. Before rushing headlong into AI solutions businesses should pause to consider how, longer term, their AI strategy will be supported by their data strategy as data may be a critical dependency.