Advanced Model 1.0.0

Build the cost model behind the AI business case.

Add implementation, review, and operating detail only where it improves the decision.

Choose the right depth

Advanced adds detail. Quick remains credible.

Both modes compare current and AI-assisted work against the same accepted-business-outcome standard.

Advanced Estimate

Known totals or guided cost building.

Use direct totals when you have them. Open a builder only when you need help deriving a number.

Private by design. Inputs stay in this browser and are not submitted.

Explore a realistic scenario, then adjust the numbers for your own workflow.

Analysis context

All volumes and recurring costs must use this same period.

01

Required foundation

Current process

Count only completed outcomes that passed your acceptance standard.

Where to get this number

Use approval, completion, or posting records from a representative closed period. Exclude drafts, attempts, corrected-but-not-approved work, rejected work, failed work, and incomplete work.

How will you enter current-process cost?

Direct cost of producing the accepted current-process outcomes above.

$
Where to get this number

Use finance records, departmental budgets, agency invoices, software expenses, allocated labor, rework, and quality-control cost for the selected period.

02

Required foundation

AI volume and quality

Count every attempt: accepted, corrected, rejected, failed, and unusable work.

Where to get this number

Use pilot logs, generation history, workflow records, projected task volume, or a representative sample. Include work that later needs correction or is rejected, failed, or unusable.

How will you set the accepted-outcome rate?

Share of attempts expected to pass the same acceptance standard as the current process.

%
How to estimate this

Prefer accepted pilot outcomes ÷ all pilot attempts. Without a pilot, use a conservative assumption and treat the result as lower confidence.

03

Known total or optional builder

AI-assisted cost

How will you enter AI-assisted cost?

Total directly attributable operating cost across all attempts for the same period.

$
What should be included

Include model and platform cost, software, allocated implementation, human review, corrections, quality assurance, governance, integration support, and recurring operations.

Live model check

Calculated AI cost

More information requiredAnnual selected period
Technology
Included in known total
Implementation allocation
Human review
Other operations

Enter a known total or use the builder.

Illustrative scenarios

Load an Advanced example.

Use a realistic starting point to understand the detailed model, then edit every field. These scenarios are illustrative—not benchmarks, client results, or industry-standard performance.

Ecommerce content

Component-built content operation

A scaled content operation builds current and AI-assisted cost from labor, agency, software, implementation, review, and operating components.

Period
Annual
Unit of work
Approved PDP

Where values come fromPIM/CMS approvals, team timekeeping, agency invoices, QA records, and a representative editorial pilot.Why plausibleAnnual component totals are realistic planning inputs for a scaled operation with a formal acceptance gate.

Customer service

Pilot-derived customer-service workflow

A support team derives its accepted rate from a pilot and builds technology, implementation, review, and ongoing operating cost.

Period
Monthly
Unit of work
Resolved customer case

Where values come fromResolved-contact QA records, support ledgers, contact forecasts, pilot logs, reviewer time studies, and vendor budgets.Why plausibleA 500-attempt pilot and time-derived review cost are practical inputs for a high-volume monthly workflow.

Document operations

Implementation-heavy document processing

A high-volume workflow includes a substantial one-time implementation allocation alongside technology, human review, and operating cost.

Period
Monthly
Unit of work
Processed invoice

Where values come fromPosting records, processing labor and OCR cost, invoice forecasts, validation samples, implementation plans, and automation invoices.Why plausibleLarge document programs can combine high monthly volume with material integration and launch costs.

Methodology and limits

Detailed where useful. Comparable throughout.

Advanced accepts known totals or builds them from direct components. Inactive methods never enter the calculation.

Current unit cost×AI attempts × accepted rate= Maximum AI cost at break-even
Accepted outcomes versus attempts

Current-process accepted outcomes include only completed work that passed the stated acceptance standard; failed, rejected, incomplete, or merely attempted work is excluded. AI-assisted attempts include every accepted, corrected, rejected, failed, and unusable unit. Only the accepted share becomes accepted AI-assisted outcomes.

Cost methods and double-counting protection

Known-total and component-builder methods are mutually exclusive. Current labor builders derive direct process cost. AI builders add technology, allocated implementation, review, and other operations exactly once.

Implementation and review calculations

One-time implementation cost requires an explicit 1–10 year useful life before allocation to the selected period. Review cost can be entered directly or calculated from attempts × review rate × review minutes ÷ 60 × loaded hourly cost.

Equivalent output and thresholds

Equivalent-output cost compares both processes at the current accepted-output volume. The maximum break-even AI cost shows how much total AI cost the entered accepted rate can support.

Limitations

The model does not automatically account for demand shifts, nonlinear scale, vendor tiers, tax, financing, working capital, discount rates, legal exposure, implementation delays, ramp time, unentered change-management cost, revenue effects, opportunity cost, inflation, or model-quality drift. All loaded examples are illustrative. It is not financial advice, an audit, a guaranteed ROI model, or a replacement for finance, legal, or compliance review.

Privacy

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