Practical lessons from deploying AI securely at scale
Brief
When I first started working on enterprise AI security initiatives, I expected the biggest challenges to be technical. I assumed we’d spend most of our time discussing prompt injection, model security, vector databases or the latest LLM vulnerabilities. I was wrong — or at least incomplete.
The technology certainly matters, but after working with multiple enterprise AI initiatives, I’ve learned that the hardest security problems rarely come from the model itself. They emerge when AI becomes part of real business processes. An AI assistant doesn’t simply answer questions.
In a single workflow, it might pull a customer record from Salesforce, open a ticket in ServiceNow and send an update through Microsoft 365 before anyone has finished reading the summary. Increasingly, it makes decisions before a human even notices, and that shift changes the threat model.