Transforming promising ideas into pertinent data practices requires looking beyond the APIs to envisioning what can be done with financial data freed from technological and organizational silos.

The road towrds the forthcoming financial revolution won’t be paved with data, but with trust.

If we are indeed in the eye of the COVID-19 storm, let’s use the data at hand to chart the course we wish to sail once we have more clement skies.

Human-centric AI depends upon corporate education’s ability to develop a clear understanding of what managers can bring to the table

Management needs to look beyond data and algorithms to explore how artificial intelligence is transforming the essence of management

Academic degrees in Artificial Intelligence focus too often on Data Science per se than its transformative impact in organizations and markets.

The business value of Data Science depends upon aligning AI projects with corporate strategy, culture and resources

Focused investments in human and machine intelligence that will add value to your career and your organization

What are the sources and significant examples of implicit bias in artificial intelligence? What can be done to minimize their consequences in establishing acceptable data practices?