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Most AI budgets start from the cost. This one starts from the value. Tell it the savings, new revenue, and retention you want AI to deliver in a year. It works backward to the investment that target implies, splits that into direct AI cost, change management, and an AI risk provision, and tells you how long the value takes to arrive.
A budget built from a vendor quote tells you what the software costs. It does not tell you what the outcome costs. The gap between those two numbers is where most AI programmes fail: the licence is cheap, the change is not, and nobody budgeted for the change.
So this calculator starts where a business case should start, with the result you want. You name the annual value in three lines: money saved, new revenue, and value from keeping customers or staff you would otherwise lose. From there it estimates the investment a target of that size usually requires, and shows you the shape of the spend before you commit to it.
The result is a planning estimate, not a quote. Use it to sanity check a business case, size a budget ask, or decide whether a target is realistic for the approach you have in mind.
Open the Calculator →The model is deliberately simple, and every step runs in your browser. Nothing you type is sent anywhere. Here is the logic, in plain terms.
Add your three value lines: annual savings, annual new revenue, and the annual value of better retention. That total is what you are asking AI to deliver in a year.
A benefit-to-cost ratio, set by how you build (off-the-shelf, integrated, or custom), turns that value into the delivery investment it implies. Ambitious value through custom builds costs more per dollar returned than quick wins from tools you buy.
The investment splits on the BCG rule of thumb: roughly a third goes to the technology and data, and the rest to people and process. Change management carries a floor tied to how many people you are asking to work differently, so a big rollout is never costed as cheap.
An AI risk provision is added on top, sized by your sector and how sensitive your data is. Then the model estimates a time to value from your build approach and rollout size, and a payback period from your target value.
BCG puts roughly 10 percent of the effort on algorithms, 20 percent on technology and data, and 70 percent on people and process. That split is the backbone of the three buckets.
IDC found organisations realise an average of about 3.70 US dollars for every dollar invested in generative AI, with leaders far higher. The calculator uses this to anchor its benefit-to-cost ratios.
IBM ties ungoverned AI to higher breach costs, including about 670,000 US dollars in added cost where shadow AI is involved. This informs the AI risk provision.
IBM has reported that only about a quarter of AI initiatives deliver the return their leaders expected, and Gartner expects many agentic projects to be cancelled. The risk provision is your buffer against being in that majority.
The Machine
Estimated First-Year Investment
Enter a value target below, then press equals.
The value you want, per year (USD)
Your context
Rough figures are fine. The calculator updates as you type, and nothing you enter leaves your browser.
Enter your target value above and the breakdown will appear here: the three cost buckets, the full line items, your time to value, and your payback period.
Licences, models, data work, and integration. The part a vendor quote usually covers.
Training, process redesign, communication, and the productivity dip while people adjust. The part most budgets miss.
A buffer for governance, security, oversight, and rework, sized to your sector and data sensitivity.
| Line item | Estimate |
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