Cloud vs. On-Premises AI: A Total Cost of Ownership Decision Guide

There is no universal answer to whether cloud or on-premises AI costs less. The deciding variable is sustained utilisation, not the headline price either option advertises. Cloud inference is billed by the unit, so its cost rises in a near-straight line with how much you use it. An on-premises appliance is a largely fixed asset cost with a low marginal cost to run, so once usage is high and steady enough, the per-inference cost keeps falling while the cloud bill keeps climbing. Somewhere between those two curves is a break-even point, and finding yours is what this guide is about. The reason most cloud-versus-on-premises comparisons reach the wrong conclusion is that they price the obvious line items and ignore the ones that actually move the total. This guide walks through the full cost picture for enterprise AI, the cost lines teams routinely under- and over-estimate, how to locate your own break-even, and why the deciding factor at the margin is often control, which no spreadsheet prices well.