Balance Data

Increasingly, CDOs are being asked to perform a delicate balancing act – push the limits of data monetization while still ensuring that the data remains secure. That means finding new ways to balance data opportunities and data liabilities.

According to Deloitte, 62% of AI adopters see security risks as a major concern, but only 39%
are prepared to address those risks.

Source: Deloitte

Data Privacy

CDOs must ensure that third party analytics solutions don’t take possession of data but can still provide valuable insights. Data privacy regulations such as GDPR have made it essential for CDOs to lead processes that give a clear view of exactly what dangers lurk in enormous amounts of data collected by the enterprise. They also need to train employees on privacy regulations and implement procedures for compliance with data privacy laws. It's no surprise that security is the most worrisome risk for AI adopters. According to a Deloitte survey, 62% of AI adopters see security risks as a major or extreme concern, but only 39% said they are prepared to address those risks.

Bring the Algorithm to the Data

AI systems must ensure end-to-end proactive data security. Regulatory compliance and privacy policies will increasingly require data to always remain within secure cloud accounts without ever duplicating or moving across environments. AI platforms require built-in privacy and compliance with a distributed approach to security.

Cloud infrastructure has advanced so much in recent years that enterprises can train AI and conduct data analysis in their secure environment without ever moving data out of it. Previously, businesses had to bring their data to the algorithm. Now they can bring the algorithm to the data. They can conduct analysis and train AI without ever exposing their private data to a third party. That way, CDOs can turn a potential data liability into a business opportunity.