Source: Featured Blogs - Forrester
Last week's coordinated outages across Claude, ChatGPT, and Gemini showed that companies have embedded these tools into core workflows without building redundancy or fallback systems—treating them as utilities rather than experimental services. The incident exposes a real problem: enterprises are moving fast to adopt AI for competitive advantage, but their infrastructure and risk management haven't caught up, leaving them vulnerable to vendor control and single points of failure. Demand for on-premise or multi-provider AI architectures will likely grow, but most organizations lack the technical sophistication to implement them, creating a new enterprise risk that board-level security teams can't yet quantify.