This isn’t new. In the early days of the internet, service providers could throttle access based on demand or pricing tiers until regulation stepped in to standardize availability. AI is beginning to follow a similar trajectory but with a more complex set of constraints: power availability, data center capacity, geopolitical risk and vendor concentration.
What makes this different is how quickly AI is being embedded into core business workflows. Nearly three-quarters of organizations are already using AI to automate processes across multiple business functions. Yet most have done little to account for the business interruption risk that creates. Many enterprises treat AI as always-available infrastructure. In reality, it is capacity-constrained, vendor-dependent and vulnerable to disruption.
The next phase of AI maturity isn’t about adoption. It will be about resilience, continuity and dependency management.
Business continuity in an AI-dependent operating model
The question is no longer whether work can get done without AI. It is whether businesses can operate at the speed and volume they have already committed to without it.