Adversarial machine learning explained: How attackers disrupt AI and ML systems

As more companies roll out artificial intelligence (AI) and machine learning (ML) projects, securing them becomes more important. A report released by IBM and Morning Consult in May stated that of more than 7,500 global businesses, 35% of companies are already using AI, up 13% from last year, while another 42% are exploring it. However, almost 20% of companies say that they were having difficulties securing data and that it is slowing down AI adoption. In a survey conducted last spring by Gartner, security concerns were a top obstacle to adopting AI, tied for first place with the complexity of integrating AI solutions into existing infrastructure. According to a paper Microsoft released last spring, 90% of organizations aren't ready to defend themselves against adversarial machine learning.