AI Automation Agency Financial Model – 5-Year Excel Overview | eFinancialModels

Built specifically for AI automation agencies — not a generic SaaS template.

Most “AI startup” models assume you sell a subscription product. An agency doesn’t. You earn monthly retainers, one-off projects, you pass through AI/API usage costs, and you staff with contractors. This model is built around exactly that reality, so the numbers reflect how your business actually runs.

What’s inside

Monthly engine, 60 months, rolled up automatically into Years 1–5.
Full three-statement model — Income Statement, Cash Flow Statement, and Balance Sheet that ties to zero in every period.
Revenue engine: active retainer clients (grown by new wins, reduced by monthly churn) × average retainer, plus project revenue from project count × average value.
Agency-specific costs: AI/API usage and contractor/delivery cost as a % of revenue, plus salaries (with annual growth), software, marketing, and overhead.
Bear / Base / Bull scenarios — flip one cell to switch the entire model.
Working capital (DSO/DPO), capex & depreciation, optional debt with interest, and tax with a loss carryforward so early losses shield later profits.
Dashboard with headline KPIs and live charts (revenue vs EBITDA, ARR).
Read-Me tab with step-by-step instructions and a colour legend.

How it works

Open the Assumptions tab. 2. Pick your scenario (1 = Bear, 2 = Base, 3 = Bull). 3. Edit the blue input cells. 4. The Annual tab and Dashboard update instantly.

Fully editable. No locked cells, no macros, no passwords. Colour-coded to professional standards (blue = inputs, black = formulas, green = cross-tab links). Compatible with Microsoft Excel and Google Sheets. Tax/accounting treatment is simplified for planning; confirm specifics with a qualified accountant.

Use cases:

Raising a pre-seed/seed round or applying to an accelerator and need credible financial projections.
Applying for a business loan or line of credit for an AI/automation agency.
Pricing retainers and projects, and stress-testing margins before scaling.
Planning hiring and contractor spend against realistic cash flow.
Modelling how client churn and AI/API costs affect profitability over 5 years.

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