Region: Global
Author: Kevin Petrie
Many organizations now embrace artificial intelligence (AI) to streamline operations, capture revenue and differentiate their offerings. But while initial results are promising, too few early adopters give sufficient attention to the risks involved. Data and AI leaders must redouble their efforts to ensure accuracy, privacy and regulatory compliance while protecting intellectual property and avoiding biased or toxic content. Their ability to do so will make or break the success of AI innovation.
This survey-based report assesses the state of data and AI governance. We examine the policies, rules and standards that organizations have in place today as part of heritage data governance programs. Then we measure how organizations extend these programs to address the specific requirements of AI models and agents. We explore the roles, processes and technologies required to govern modern AI initiatives, with a particular focus on the best practices we can learn from leading adopters.
Data, AI and business leaders should read this report to learn: