AI Ticket Cost

How much does each AI-resolved support ticket cost?

How this tool works

This calculator treats one resolved ticket as the unit of analysis, then estimates AI-only ticket cost from explicit request, retrieval, cache, and infra assumptions.

How It Works

  1. Set provider/model plus support-turn assumptions.
  2. Enter ticket volume and current human cost per resolved ticket.
  3. Review AI cost per ticket, monthly spend, and savings versus the human baseline.

Formula

ai_cost_per_ticket = ai_requests_per_ticket * cost_per_request

monthly_ai_cost = ai_cost_per_ticket * monthly_tickets

Assumptions and Units

  • Currency: USD
  • Unit of analysis: resolved support ticket
  • Requests per ticket includes retries and multi-turn clarifications before resolution
  • Pricing source: daily pricing snapshot in repo, no runtime scraping

Related resources: AI Payoff Point, AI + Human Ticket Cost, AI Support Agent Cost per Ticket, AI Support Deflection Rate, How To Estimate Requests Per User/Month, What Cache Hit Rate Means for RAG.

Pricing snapshot: 2026-04-09Provider: OpenAIModel: GPT-5.2

Step 1 Provider and Model

Switch model assumptions using prices from the selected snapshot.

Step 2 Support Scenario

Set ticket volume, human baseline, and escalation assumptions before tuning the AI workload.

Mid-volume SaaS support queue with moderate retrieval depth and tighter per-ticket savings headroom.

Step 3 AI Workload Assumptions

Set the support-turn assumptions first, then open advanced retrieval and infra fields if needed.
Show advanced inputs

Open these only when retrieval, reranking, vector, or infra detail changes the support decision.

Scenario actions

Copy scenario URL

Paste into ChatGPT or Claude, or share with a teammate.

Save and track this scenario

Track pricing drift on this scenario and get an email if the latest result changes.

How tracking works

After you click Save and track, we carry this exact calculator state into the tracked-scenarios page so you can sign in and confirm the save.

We save your assumptions and the pricing snapshot used for this result.

When a newer pricing snapshot lands, we recompute the same scenario, show what changed, and email you if the latest result moved.

1 tracked scenario free, then $12/mo or $120/yr for up to 25 tracked scenarios.

Decision Signal

Clear savings

Modeled AI cost is $0.2806 per resolved ticket against a $2.4 human baseline.

That leaves $2.1194 of savings per ticket, or $4,662.58 per month at the current volume.

AI cost / ticket

$0.2806

Savings vs human / ticket

+$2.1194

Monthly AI cost

$617.42

Monthly savings vs human

+$4,662.58

Most Sensitive Inputs

Most sensitive ticket-cost inputs when each is moved up by 10%.
AI requests / ticket+$0.0281
Rerank Docs+$0.0211
Cache Hit Rate-$0.0046

Totals

Summary metrics for the current support scenario.
AI cost / ticket
$0.2806
Human cost / ticket
$2.4
Savings vs human / ticket
+$2.1194
Monthly AI cost
$617.42
Monthly human cost
$5,280
Monthly savings vs human
+$4,662.58
AI cost share of human
11.7%
AI cost / ticket$0.2806
Human cost / ticket$2.4
Savings vs human / ticket+$2.1194
Monthly AI cost$617.42
Monthly human cost$5,280
Monthly savings vs human+$4,662.58
AI cost share of human11.7%

AI Cost Breakdown (USD/ticket)

Each cost component is computed independently, then summed.

Largest cost block: Reranking.

GenerationModel input/output token spend for support turns.
$0.0539
RetrievalExtra model input spend from retrieved support context.
$0.0189
RerankingReranker cost based on docs rescored per support request.
$0.245
Embeddings IngestionAmortized per-ticket share of the fixed monthly support corpus embedding refresh.
$0
Vector DbVector database query cost across support requests.
$0.0002
CacheSavings from repeated support requests served by cache. Negative means lower total cost.
$-0.0457
InfraNon-model infra overhead per support request.
$0.0084
GenerationModel input/output token spend for support turns.$0.0539
RetrievalExtra model input spend from retrieved support context.$0.0189
RerankingReranker cost based on docs rescored per support request.$0.245
Embeddings IngestionAmortized per-ticket share of the fixed monthly support corpus embedding refresh.$0
Vector DbVector database query cost across support requests.$0.0002
CacheSavings from repeated support requests served by cache. Negative means lower total cost.$-0.0457
InfraNon-model infra overhead per support request.$0.0084
Sensitivity RankingChange in ticket cost when one variable is increased by 10%.
VariableDelta AI cost / ticket
AI requests / ticketAverage AI turns needed to fully resolve a ticket.+$0.0281
Rerank DocsDocs reranked per support request.+$0.0211
Cache Hit RateFraction of support requests served from cache.-$0.0046
Output TokensGenerated tokens per support response.+$0.0029
Input TokensBase prompt tokens per support request.+$0.0017
Retrieved ChunksRetrieved chunk count per support request.+$0.0016
Tokens Per ChunkAverage chunk size in retrieved support context.+$0.0016
Infra Cost Per Request+$0.0007
Vector Queries Per RequestVector lookup count per support request.+$0
Vector Cost Per Query+$0
Embedding Ingestion Tokens Monthly+$0
Monthly ticketsTicket volume used for monthly totals and fixed-term amortization.-$0

Assumptions and Units

Explicit assumptions keep the support model reproducible and auditable.
  • CurrencyUSD
  • Unit of analysisResolved support ticket
  • Pricing snapshot2026-04-09
  • Selected model rowOpenAI/GPT-5.2
  • Ticket definitionRequests per ticket include retries and multi-turn clarifications before resolution
  • Human baselineFully loaded human support cost per resolved ticket

Recommended Next Step

Use these links to move from modeled support economics into the next pricing or implementation check.

Once the AI-only ticket cost looks plausible, open break-even pricing to test commercial headroom, then pressure-test the required deflection rate before treating the savings as real.

Sources and Snapshot

Pricing comes from the current dated snapshot.

Active Pricing Row

Selected model

OpenAI / GPT-5.2

  • Input tokens$1.75 / 1M
  • Output tokens$14 / 1M

Shared retrieval defaults

  • Embedding input$0.02 / 1M
  • Rerank docs$1 / 1K