FV is the quiet workhorse behind serious planning. In both Google Sheets and Excel, the FV function lets you answer questions every business owner, marketer, or agency lead secretly worries about:
If I invest this much every month at this rate, what will it be worth in a year? In three? What happens if I increase ad spend contributions by 10%? Can I afford this software or hire if revenue compounds as planned?
FV(rate, nper, pmt, [pv], [type]) gives you the future value of an investment or loan under a constant interest rate. Rate is your period interest, nper is the number of periods, pmt is the recurring contribution, pv is what you start with, and type controls whether payments happen at the start or end of the period. Once you learn it, you stop guessing and start simulating scenarios with intent.
Now imagine you never again have to touch these formulas manually. An AI computer agent opens your Google Sheets and Excel models, validates rate and nper units, fills FV across hundreds of rows, and builds side-by-side scenarios for best, base, and worst case – while you stay focused on sales calls, creative strategy, or investor updates. Delegating FV grunt work to an agent turns financial modeling from monthly chore into always-on decision support.
Before you automate, it helps to feel the friction. Here are core manual workflows you probably use today.
1. Basic FV in Excel for a recurring payment
=FV(rate, nper, pmt, [pv], [type]).=FV(0.06/12, 5*12, -500, 0, 0)
2. FV in Excel with both starting balance and contributions
=FV(0.06/12, 60, -500, -10000, 0).
3. FV in Google Sheets for campaign war-chest planning
=FV(rate, number_of_periods, payment, [present_value], [end_or_beginning]).=FV(0.08/4, 4*3, -2000, 0, 0).
4. Row-by-row FV for each client or property
=FV($B2/12, $C2*12, -$D2, -$E2, 0).
5. Scenario analysis by hand
This works but becomes painful when you have dozens of clients, SKUs, or campaigns.
You can reduce the busywork before bringing in an AI computer agent.
A. Use named ranges and templates in Excel
=FV(rate_monthly, total_periods, -pmt_monthly, -pv_start, 0).
B. Automate data refresh with Power Query (Excel)
Microsoft’s docs on financial functions and modeling are a good reference: https://support.microsoft.com/en-us/office/financial-functions-reference-5658d81e-6035-4f24-89c1-fbf124c2b1d8
C. Google Sheets + Apps Script trigger
=FV($B2/12, $C2*12, -$D2, -$E2, 0).
D. Zapier or Make to sync inputs
These no-code flows remove data wrangling, yet you, or your analyst, still manage every formula, scenario, and edge case. That is where an AI computer agent changes the game.
Now imagine handing off the entire workflow to an agent that can literally use your computer.
Method 1: Simular agent as your on-demand financial ops assistant
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Method 2: Always-on FV portfolio updater for agencies and SaaS teams
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Method 3: What-if scenario generator at scale
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Once this is in place, your relationship with FV changes. Instead of being the person who wrestles with rate, nper, and type every month, you become the editor-in-chief: defining assumptions and reviewing what your AI computer agent produces across Google Sheets and Excel.
To set up FV for monthly payments you need to align the interest rate and the number of periods with your payment frequency. In Excel, start by identifying your annual interest rate, say 12%, and your loan or investment term, say 4 years, with payments monthly. Rate must be per period, so use 12%/12 for rate. Nper is the total number of periods, so use 4*12. If you are contributing 500 at the end of each month and start from zero, the formula is `=FV(0.12/12, 4*12, -500, 0, 0)`. The payment is negative because it is cash you pay out. In Google Sheets, the setup is almost identical: `=FV(0.12/12, 4*12, -500, 0, 0)`. Always double-check that rate and nper use the same unit (months here). If you start with an existing balance, make pv negative as well. Testing this on a small example and comparing to an online FV calculator helps validate your setup.
FV handles a starting lump sum and recurring contributions in a single formula. Think of pv as your starting pot and pmt as your recurring adds. Suppose your business parks 20,000 in a reserve account and adds 2,000 monthly for 3 years at 7% annual interest. First convert to monthly: rate is 0.07/12, nper is 3*12. In Excel, use `=FV(0.07/12, 3*12, -2000, -20000, 0)`. Both pv and pmt are negative, because they represent money you put in. If payments occur at the beginning of each month, set type to 1: `=FV(0.07/12, 36, -2000, -20000, 1)`. In Google Sheets the formula is identical. A practical workflow is to create columns for rate, nper, pmt, pv, and then a standardized FV formula that references those cells so you can change assumptions without touching the formula itself.
Three errors show up constantly. First, mismatched units: using an annual rate with monthly periods without converting. Fix this by always writing rate as annual_rate/12 when nper is in months, and multiplying years by 12 for nper. Second, wrong sign convention: if pmt or pv have the wrong sign, your FV will look backwards (negative when you expect positive, or vice versa). Remember: cash you pay out (deposits, investments) is negative; cash you receive is positive. Third, misusing the type argument. Type 0 means payments at the end of the period, type 1 means at the beginning. Using the wrong type skews results, especially over long horizons. In Excel and Google Sheets, start by leaving type at 0 unless you clearly pay at the start of each period. Finally, watch out for non-numeric values in any argument; those throw a VALUE error. Building a small, labeled input section and referencing those cells from FV keeps you out of trouble.
To apply FV across many rows, structure your sheet like a small database. Put one client, property, or product per row. Create columns such as AnnualRate, Years, MonthlyPayment, StartBalance, and FV. In Excel, your FV column formula in row 2 might be `=FV(B2/12, C2*12, -D2, -E2, 0)`. Once you confirm it works for one row, drag the formula down through your entire list. In Google Sheets, use the same pattern or wrap it in an arrayformula for auto-expansion. To scale further, you can use filters and tables to group clients by risk profile or campaign type, and easily adjust assumptions per segment. If you are using an AI computer agent like Simular, the agent can take this a step further: it opens your workbook, pastes the template formula down to the last populated row, and checks a sample of results, so you no longer worry about missing a row or copying into the wrong range.
An AI agent turns FV from a static spreadsheet trick into a living forecasting system. Instead of you updating rates, periods, and payments every month, the agent does the mechanical work for you. For example, a Simular AI computer agent can log into your laptop, open Excel and Google Sheets, pull the latest exports from your CRM or billing system, and update the input columns used by your FV formulas. It can ensure rate and nper stay in consistent units, extend formulas for new rows, and generate scenario copies of your model at different rates or payment levels. Because Simular Pro agents operate across desktop, browser, and cloud, they can stitch together tools without APIs. You stay focused on reading the updated FV numbers and deciding what to do next – adjust ad spend, renegotiate terms, or spin up a new campaign – while the agent quietly keeps your models accurate and current.