AI Integration Cost for Existing Apps

Reviewed 2026-08-28

Methodology and sources

This AI-integration planning result is derived only from the visible user-entered effort, rate, tooling, monthly operating cost, maintenance, capacity, complexity, expected-savings, source-provenance, and visible context selections. CostSignals does not fetch, validate, update, or endorse those entered assumptions or the calculated results.

Formula in plain English

The calculator adds six entered effort buckets, multiplies them by the entered complexity factor and blended rate, and adds entered one-time tooling for total integration cost. It separately reports setup and migration components, adds entered API, platform, storage, and maintenance amounts for monthly cost, divides adjusted effort by at least one weekly team-capacity unit for timeline, annualizes entered expected monthly savings, and divides total cost by positive expected savings net of monthly operating cost for payback; otherwise payback is zero.

Visible assumptions

• All effort, rate, tooling, monthly cost, maintenance, capacity, complexity, expected-savings, and source-provenance inputs are explicit; the required numeric cost and rate fields have no hidden current-price or labor benchmark.
• The required source name and YYYY-MM-DD source date, plus optional source URL, are user-entered provenance only and are not fetched, validated, refreshed, or endorsed by CostSignals.
• Application age, technology stack, AI-capability scope, and data readiness are neutral multiplier-1 context labels and do not change arithmetic. teamSize is the only non-neutral selector and changes implementationTimelineWeeks only; it does not change costs, savings, complexity, or payback.
• Compatibility baseCosts values are present in the generated contract but unused by every output formula.
• integrationCost and transformationCost alias totalIntegrationCost, timeline aliases implementationTimelineWeeks, ongoingCost aliases monthlyIntegrationCost, complexity aliases integrationComplexityMultiplier, annualSavings aliases estimatedAnnualSavings, and roiTimeline aliases paybackPeriod; none is a separate model.
• Payback is zero when entered expected monthly savings do not exceed modeled monthly operating cost. That zero is a no-positive-modeled-payback sentinel, not immediate payback; the timeline denominator also uses a minimum-one guard to remain finite.

Worked example

Limitations

• The calculator does not provide current labor, API, tooling, platform, or storage prices; a vendor quote or ranking; realized savings or ROI; a payback guarantee; a delivery, performance, security, compliance, architecture, or provider-suitability conclusion.
• The model excludes every dependency, migration, procurement, model, quality, operations, tax, contract, risk, and change-management item not represented by an explicit input.
• The NIST and GAO sources support AI risk-management and legacy-system investigation context only; they do not support any entered hours, rates, costs, savings, complexity, timeline, architecture, payback value, or calculated result.

Practical next steps

1. Document the source, effective date, scope, and units for every entered effort, labor-rate, tooling, operating-cost, maintenance, capacity, complexity, and savings assumption.
2. Compare scenarios with identical capabilities, dependencies, migration scope, testing scope, service levels, and omitted-cost treatment.
3. Validate architecture, security, governance, delivery capacity, and operational risks outside this arithmetic worksheet before selecting a provider or implementation path.

Source records