Seven things drive the cost of AI automation: the number of systems involved, how they connect, data quality, input variety, the share of cases that need a person, how much review you want and upkeep after launch. To judge a quote, first estimate what the work costs you today, then compare that with the automation’s total cost over its first year, not just the setup fee.
Seven cost drivers
1. How many systems the workflow touches
An automation that reads email and writes to one ERP is simpler than one that also updates a CRM, an accounting system and a shipping tool. Each system adds access to set up, fields to map and changes to watch for. The handoffs between Microsoft 365, QuickBooks and NetSuite show how quickly they multiply.
2. How those systems connect
Systems with a documented API are quicker to work with. Older software without one may need workarounds, such as reading exported files or working through the screen, which take longer to build and are more fragile when the software changes.
3. How clean the data is
Duplicate customers, inconsistent item numbers and missing price levels all have to be dealt with. Sometimes the automation is the cheap part, and the expensive part is cleaning up the records it depends on.
4. How much the inputs vary
Purchase orders in three layouts are easier than purchase orders in fifty. Reading many layouts is the kind of job AI suits, but each one still needs real examples tested before you rely on it.
5. How many cases need a person
A workflow where 1 case in 20 needs a person is very different from one where 1 in 3 does. Exceptions shape the review screens, the rules and the time your team still spends.
6. How much review you want
Drafts that a person approves are safer at the start and cost some of your team’s time. Fully automatic steps save more time, but only once they’ve earned your trust. Start with drafts and move a step to automatic only when its log shows it’s reliable. Budget for the review time until then.
7. Upkeep after launch
Your business changes, and so does the software around the automation. Someone has to keep the automation current, and that work belongs in the price. The next section breaks it down.
What does it cost after launch?
The setup fee is the visible part. These costs continue for as long as the automation runs:
- Maintenance. New customers, products, price rules and document layouts mean rule updates. Ask who makes them, how fast and at what cost.
- Monitoring. Someone has to read the log, work the exception queue and notice when results drift. That’s your team’s time, the provider’s or both.
- Model or API usage. Model providers such as Anthropic and Google bill API usage by the token, a small piece of text. Both publish prices per million tokens, with input and output priced separately. Usage grows with volume and with the length of what the model reads, so a 10-page PDF costs more to process than a two-line email.
- Changes in connected software. NetSuite has two major releases each year, and you can request a Release Preview account to test each one with your own data. Microsoft’s published schedule starts disabling Exchange Web Services in Exchange Online in October 2026 and turns it off fully in April 2027, so anything that reads a mailbox that way has to move to another interface. Ask who tests and updates the automation when changes like these arrive.
- Your team’s time. Reviewing drafts and handling exceptions doesn’t stop at launch, though it should shrink as the automation earns trust.
Pricing models you may be offered
| Model | How it works | Watch for |
|---|---|---|
| Fixed fee per workflow | One price to design and launch a defined workflow | What’s included after launch |
| Monthly subscription | A recurring fee for running and maintaining automations | Limits on volume, users or workflows |
| Usage-based | A charge per transaction, document or run | Costs that grow faster than the value |
| Hourly or project time | You pay for the hours spent | Open-ended scope |
An arrangement can combine two of these, such as a setup fee plus a monthly fee. Ask for the total over the first year, not just the first invoice.
A worked estimate, with illustrative numbers
Here’s how to size one workflow before you talk to anyone. Every number below is illustrative, so use your own counts and costs.
What the work costs today. Your team handles 40 emailed purchase orders a week at 6 minutes each. That’s 240 minutes, or 4 hours, a week. Over a 50-week year, it’s 200 hours. At a fully loaded labor cost of $40 an hour, it’s $8,000 a year. Now add errors: if 2 orders a month go out wrong and each costs about $150 to put right in time, freight and credits, that’s 24 errors at $150, or $3,600 a year. Today’s total is $11,600 a year.
What would remain after automation. Say 38 of the 40 orders become drafts that take 1 minute each to check, and the other 2 still need full handling at 6 minutes each. That’s 38 minutes plus 12 minutes, or 50 minutes a week, which comes to about 42 hours and about $1,670 a year.
What the automation could be worth. The time saved is worth $8,000 minus about $1,670, or about $6,330 a year. If the automation also prevented half the errors, add $1,800, for about $8,130 a year.
What to hold a quote against. Add up the automation’s first-year cost: setup, twelve months of fees, usage and your team’s time during setup. For example, 20 hours of mapping, testing and review at $40 an hour is $800 of your own time. Look for a first-year cost well below the yearly value, with a clear plan to measure it.
How to compare quotes
Quotes arrive in different shapes. Put them on the same footing before you compare prices:
| Line up | What to ask |
|---|---|
| Scope | Which workflow, systems and exceptions are covered? |
| Setup | Does it include mapping, testing and data cleanup? |
| Recurring fees | What’s covered each month, and what are the limits? |
| Usage | Is model usage included, passed through at cost or marked up? |
| Upkeep | Who updates the automation when your rules or software change? |
| Your team’s time | How many hours will your people spend on setup and review? |
| Exit | What do you keep if you stop, and how is access shut off? |
Then run three checks:
- First-year total. For each quote, add setup, twelve months of fees, expected usage and your team’s time.
- Double the volume. Recalculate each quote at twice today’s volume. Usage-based pricing can look cheap at low volume and expensive at high volume.
- Compare with the value. Set each first-year total against the yearly value you estimated, then against the other quotes.
Questions that keep a quote honest
- What exactly is included, and what costs extra?
- What happens to the price if our volume doubles?
- Is model or API usage included, and how is it measured?
- Who maintains the automation when our rules or software change, and what does that cost?
- How will we measure the result, and when?
- What’s the total cost over the first year, including our team’s time?
- How do we stop, and what do we keep if we do?
For questions about the firm itself, see how to choose an AI consulting firm in St. Louis.
At Kestrel, an AI-native consulting firm in St. Louis, pricing isn’t published while our agent is in development, but we count the work with you before anything runs, so you have a baseline to weigh any price against. Request early access or see how we work in St. Louis.