From Data Governance to AI Governance: How to successfully make the shift?

In the last few years- and certainly in the face of 2020’s tumultuous turn of events- data governance has shot to the forefront of discussions both in the media and in the boardroom.

This white paper covers:

• Why proper governance is more important than ever before
• What AI governance is and why it's different than data governance
• Components for (and pitfalls to) successful AI governance

This white paper is brought to you by Dataiku and Capgemini.

There are a few conclusions we hope you take away from this whitepaper:

1. Traditional data governance, and all the areas underneath it, are still important. Whether that be data quality, master data management or data security.
2. Data science, machine learning, and AI have added new aspects to the data governance picture that necessitate an expansion of focus and application.
3. Organizations need the right sponsorship, investment, culture and communication to make sure a data governance program is effective and leads to continuous improvement across the organization.

The whitepaper explores how companies seriously engaging in scaling AI need to enhance their governance approach - with data governance as a cornerstone.

In the long run, good AI governance will allow for Enterprise AI at scale that is responsible and sustainable.