A runway forecast should not be one date. AI companies face variable compute costs, enterprise payment timing and infrastructure commitments that can move cash burn quickly.

Use three operating cases

A base case reflects the current plan. A growth case includes faster hiring and usage. A downside case assumes slower collections or customer contraction.

Model cash timing

Annual contracts can improve cash before revenue is recognized, while cloud commitments can require payment before customer demand appears.

Separate controllable and committed spend

Payroll plans can sometimes be slowed; signed GPU or cloud commitments may be harder to change.

Set trigger points

Define the cash balance or growth threshold that causes hiring, infrastructure or fundraising decisions to change.

For compute-specific forecasting, see AI Startup Cash Burn Forecast.

Bottom line

Scenario-based runway planning turns uncertainty into explicit decisions instead of relying on a single optimistic burn estimate.