The CISO's platform problem: How platform engineering makes enterprise AI secure by default

Manoj and Chandra address the enterprise challenge of governing AI at scale. Security teams cannot review every LLM integration, and blanket bans on GenAI only drive shadow AI underground. Platform engineering offers a third path by embedding security by default into the infrastructure that developers use.

Key takeaways:
• Why the current model of per-project AI security review cannot scale to enterprise AI adoption
• How platforms can embed AI security controls (data classification, model access, output filtering) as defaults
• Bridging the gap between CISO requirements and developer experience through platform abstractions
• Building compliance as code for AI workloads: audit trails, data residency, and model governance
• Case patterns showing how platform-embedded security reduces risk while accelerating AI innovation