Data is one of an organization’s most valuable assets, yet it is one of its most vulnerable, and AI is introducing more risk. One principle remains clear, Greg Campanella and Ken Feinstein of consultancy J.S. Held say: Data authenticity and integrity are foundational for AI deployment and long-term value.
Structured data has become highly valued in the digital world, and accordingly, the risk of data manipulation and related fraud has increased. AI has enabled threat actors like terrorist groups and cybercriminals to create deepfakes and more easily gain access to environments that hold sensitive personal information. While methods existed to make fake data appear authentic before the advent of AI, new technologies have made it harder to distinguish between real and deceptive data.
Business email scams, BYOD (bring your own device) policies and falsified electronic documents, for example, are big risks to businesses. The consequences of data integrity failures can be severe: costly investigations, litigation, reputational damage and operational disruptions.
Compliance challenges in a fragmented regulatory landscape
GDPR must be considered by all organizations that do business in Europe. Since its implementation in 2018, the primary goal of the GDPR has been to protect the personal data and privacy…
