AI Security for Enterprises: Kanerika's CISO on Prompt Injection, ISO 27001 & SOC 2

0:00 Meet Kanerika's CISO Lalit 1:05 What AI Security Really Means 3:43 Kanerika's ISO 27001 and SOC 2 Posture 7:08 Agentic AI Risks and Access Control 10:28 Client Data Handling When Agents Go Live 13:32 Agent Failures, Observability and Prompt Manipulation 16:35 What Clients Ask in Security Reviews 19:08 Security Differences by Industry 22:01 Microsoft Purview in Client Deployments 24:58 AI Bias and Zero Trust Validation 28:03 Vetting AI Vendors Before Signing 29:57 Final Advice: Use AI Responsibly AI security means different things to different people. Some mean protecting the data that goes into a model. Others mean protecting the business from the decisions the model takes. In this episode of The Digital Shift by Kanerika, Lalit Rawat, Kanerika's Chief Information Security Officer, an eight-year Microsoft Azure MVP and the author of two books on Azure, draws the line between the two and walks through what Kanerika holds itself to before any AI agent touches a client's systems or data. What Lalit covers: Why the public conversation about AI and data (image generators, training on user uploads) is not how an enterprise should think about its data strategy Where AI security starts: Well-Architected Framework for AI, landing zones, and policies, procedures and controls defined before a model is built Why models should be trained and tested on dummy data first, and why PII and HIPAA-regulated data such as medical records and phone numbers should be restricted from training sets Prompt injection as the biggest current challenge, with behavioral analysis and guardrails as the controls that hold up over the long term The guidelines Kanerika follows: NIST and OWASP, turned into internal policies, with data retained on-site whether it belongs to a client or to Kanerika Kanerika's own posture: ISO 27001 and SOC 2, plus an internal tool that scans every piece of code before it reaches production, including code written with AI, for secure development lifecycle compliance, exposed credentials, encryption and infrastructure choices Why security has to cover every layer, from infrastructure and network to the AI layer and the application, with checks enforced in the DevOps repo before any code is merged Kanerika builds and governs enterprise AI systems under ISO 27001, ISO 27701 and SOC 2 certifications, and maps its generative AI controls to the OWASP Top 10 for LLM Applications and NIST's Generative AI Profile. Resources: AI governance consulting: https://kanerika.com/services/ai-gove... Generative AI security, layer by layer: https://kanerika.com/blogs/generative... LLM security guide: https://kanerika.com/blogs/llm-securi... AI security frameworks, types and controls: https://kanerika.com/blogs/ai-securit... Data security in AI with Microsoft Purview: https://kanerika.com/blogs/data-secur... Kanerika leadership announcement: https://kanerika.com/newsroom/kanerik... Related videos: Enterprise AI Adoption: Why Employees Resist and Most AI Projects Fail    • Enterprise AI Adoption: Why Employees Resi...   What Does It Take to Deploy an Enterprise LLM?    • What Does It Take to Deploy an Enterprise ...   State of Enterprise AI 2026: Data Foundations, Maturity Stages & ROI    • State of Enterprise AI 2026: Data Foundati...   Putting an AI partner through a security review? Talk to Kanerika: https://kanerika.com/contact-us/?utm_... Subscribe to The Digital Shift by Kanerika:    / @kanerikainc   #AISecurity #EnterpriseAI #PromptInjection #ISO27001 #SOC2 #AIGovernance #CISO #DataSecurity #TheDigitalShift #Kanerika