The Secrets of AI Value Creation

5Collecting Valuable Data

Most of the time spent in school is devoted to the transmission of information and ways of obtaining it. Less time is devoted to the transmission of knowledge and ways of obtaining it (analytic thinking). Virtually no time is spent in transmitting understanding or ways of obtaining it (synthetic thinking). Furthermore, the distinction between data, information, and so on up to wisdom are seldom made in the educational process, leaving students unaware of their ignorance. They not only don't know, they don't know what they don't know.

—R. L. Ackoff (professor at the Wharton School, University of Pennsylvania)

In today's data‐rich business environment, sifting through the noise to identify relevant data is paramount because the financial burden of collecting data can be significant for an organisation. Data management costs, including third‐party sourcing, architecture, governance, and consumption, can account for up to 5% of a company's operating costs (Grande et al. 2020).

Especially when organisations start to scale the application of AI, the demand for AI‐centric, disaggregated data invariably increases, making data optimisation a key challenge for businesses. As organisations start to recognise the financial burden that data creates, they are responding by optimising their data life cycle management, including data sourcing, data governance, data infrastructure and storage, and even archiving and deleting data. AI achievers have learned the value ...