Answering your 4 biggest questions about generative AI security Rapidly adopt generative AI—while helping to ensure security, privacy, and compliance

INTRODUCTION
Ready, set, generate:
Adopt generative AI quickly
and safely
The race for generative AI is on. Businesses are rushing to reinvent
customer experiences and applications, driven by potentially massive
improvements to productivity and experience.
While the generative artificial intelligence (AI) era has only just begun, organizations are already
realizing tangible benefits across virtually all business units. However, security professionals advise
caution. They cite data privacy, model bias, harmful content creation (such as deepfakes), and the
risks of malicious input on models as reasons to approach generative AI adoption with care.
It is imperative that organizations approach generative AI with a clear strategy for how to
protect their data, users, and reputation—while still enabling rapid adoption and improving
customer experience.
While this represents a multifaceted challenge, organizations should remember that standard best
practices for AI, machine learning (ML), data protection, and cloud workload security still apply. In
fact, your organization may be better prepared to secure generative AI than you think.
Establishing proper protections for generative AI workloads now will help drive innovation
across your organization—giving your teams the confidence to pursue big ideas and the freedom
to focus on growing your business.