1、W H I T E P A P E RData Security in an AI-First Paradigm7 Key Priorities for Your Security StrategyEPAM.CO MData Security in an AI-First Paradigm|05/25|2W H I T E P A P E RContentsIntroduction.3From Guidelines to Mandates:Navigating AI Security Standards.4Data Residency&Governance:Knowing Where Your

2、 Data Lives.5The Great Knowledge Gap:Building Foundations for GenAI Threat Mitigation.6AI Lifecycle Risk Management:Expanding Your Threat Model.7AI Supply Chain&Dependency Risks:Accounting for Third-Party Exposure.8Secure MLOps:Integrating AI into the Secure SDLC.9Assume Vulnerable by Default:Securi

3、ng Public LLM Architecture&Configuration.10Real-World Opportunities&Final Thoughts.11Data Security in an AI-First Paradigm|05/25|3W H I T E P A P E RIntroductionThe acceleration of AI adoption,and its evolution,has amplified the stakes for enterprises worldwide.Much like how cloud revolutionized IT,

4、AI continues to reshape the landscape with unprecedented speed and scale.When we first explored the state of security in this new paradigm,we discussed the duality of disruption,specifically this disruption:You need to accept that things are going to be messy if you want to innovate.And you need to

5、balance experimentation with risk mitigation.Innovation always introduces new vulnerabilities.However,AI and ML bring a distinct set of challenges that go beyond what we encounter in traditional engineered systems.Amid the hype to secure competitive advantage,companies fail to proactively secure the

6、ir enterprise assets welcoming risk right into the business.For many companies,security is now considered a primary roadblock to rolling out AI initiatives.In our recent survey of over 7,300 participants,35%of businesses say their top challenge to achieving modernization is a lack of sophisticated s