This is probably the first question you asked when you started looking into AI automation. And it is frustrating that most answers you find online are vague. "It depends" is technically true but completely unhelpful when you are trying to plan a budget. So let us do something different and give you actual numbers.
The Three Pricing Models
There are three main ways businesses get AI automation built, and each has a different cost structure.
1. DIY with No-Code Tools
This is the cheapest upfront option. You sign up for a workflow automation platform, watch some tutorials, and build the automations yourself.
- Monthly platform cost: $20 to $200/month depending on volume and features
- Your time investment: 20 to 80+ hours for the initial build, depending on complexity
- Ongoing maintenance: 2 to 5 hours per week troubleshooting, updating, and fixing things that break
Total first-year cost: $240 to $2,400 in software, plus 100 to 300+ hours of your time.
The hidden cost here is your time. If you value your time at $75/hour (a conservative number for a business owner), those 200 hours of DIY work represent $15,000 in opportunity cost. The "cheap" option is not always cheap when you factor in what you could be doing instead.
DIY works well for simple, single-step automations. It gets painful quickly when you need multi-step workflows, error handling, conditional logic, or integrations with tools that do not have pre-built connectors.
2. Boutique Automation Agency (Like Eukairox)
This is the sweet spot for most small to mid-size businesses. You work with a specialized team that builds custom automation systems tailored to your specific workflows.
Here is what leasing looks like at Eukairox. No build fee, no long contract, and a paid pilot that is credited to month one:
- AI Receptionist: $499/month. Answers, books, and routes every enquiry.
- AI Front Office: $1,299/month. Receptionist plus scheduling, follow-up, and reviews.
- AI Operations Team: $2,900/month. The full team, including admin and reporting.
Total first-year cost: $5,988 to $34,800 depending on team size. Start with a 14-day paid pilot for $499, credited to month one, with the success metric agreed before launch.
For that investment, you get a production-ready system built by people who do this every day. It includes proper error handling, monitoring, documentation, and someone to call when something needs adjusting. Check out our pricing page for current details.
3. Enterprise Solutions and Big Consulting Firms
The enterprise route involves large consulting firms or enterprise software vendors. This is designed for companies with 500+ employees and complex, multi-department needs.
- Discovery and planning: scoped like a consulting engagement
- Implementation: scoped per department and system
- Annual licensing and support: enterprise contracts
- Timeline: 6 to 18 months
First-year totals on this route routinely run into six figures.
Unless your business has hundreds of employees and a dedicated IT department, this is almost certainly overkill. We mention it here for completeness and because some business owners get quoted these numbers first and assume that is what AI automation costs across the board. It is not.
What Affects the Price
Within any pricing model, several factors move the number up or down:
- Number of integrations: Connecting two tools is simpler than connecting eight. Each integration adds development and testing time.
- Data complexity: Moving structured data (spreadsheet rows, form fields) is straightforward. Handling unstructured data (emails, PDFs, images) requires AI processing and costs more.
- Volume: An automation that handles 50 transactions per day costs less to run than one handling 5,000. Higher volume means more computing resources and potentially higher platform fees.
- Custom logic: Simple "if this, then that" rules are cheap. Complex decision trees with multiple conditions, exceptions, and edge cases take longer to build and test.
- Compliance requirements: If your industry has specific data handling regulations (healthcare, finance, legal), the build needs additional security layers and audit trails.
How to Calculate Your ROI
Cost only matters relative to what you get back. Here is a simple ROI framework:
Step 1: Calculate your current cost. How many hours per week does your team spend on the tasks you want to automate? Multiply by the average hourly cost (salary + benefits divided by 2,080 hours). That gives you the annual cost of doing it manually.
Step 2: Add error costs. How often do manual errors happen, and what do they cost? Wrong invoices, missed follow-ups, duplicate orders, data inconsistencies. Even if errors only happen 2% of the time, they add up.
Step 3: Factor in speed. What is the revenue impact of faster processing? If automating lead follow-up means responding in 30 seconds instead of 4 hours, how many additional deals will you close?
Step 4: Compare. Take your total manual cost (step 1 + step 2 + step 3) and compare it to the automation cost. In our experience, the manual cost is typically 4x to 8x higher than the automation cost over a 12-month period.
Let us run through a real example. Say you have two employees spending a combined 25 hours per week on data entry and lead processing. At a blended cost of $30/hour:
- Manual cost: 25 hours x $30 x 52 weeks = $39,000/year
- Error and delay costs: Conservatively $5,000/year in rework, lost leads, and customer issues
- Total manual cost: $44,000/year
- AI Front Office lease: $1,299/month x 12 = $15,588/year
- Net savings in this example: about $28,400 in year one, before counting the hours your team gets back.
That is roughly 2.8x the lease cost covered in year one, in this example. And those two employees now have 25 extra hours per week to spend on revenue-generating work. Your numbers will differ, which is exactly why we agree the success metric before the pilot starts.
Red Flags in Automation Pricing
Not all pricing is transparent. Watch out for these warning signs:
- "We will scope it after you sign." Any reputable firm will give you a clear scope and price before you commit. If they cannot tell you what it will cost, they either do not understand the work or plan to upsell you later.
- No retainer, no support. If someone builds your automation and disappears, what happens when something breaks at 2 AM? Good automation needs ongoing monitoring and maintenance. A zero-support deal is not a bargain.
- Per-task or per-execution pricing that scales unpredictably. Some platforms charge per automation run. At low volume, this seems cheap. But as your business grows, the costs can spike dramatically. Understand exactly how costs scale before committing.
- Lock-in contracts with no exit clause. You should own your automations. If you want to switch providers or bring things in-house, you should be able to take your workflows with you.
Where to Start If You Have a Limited Budget
If $3,000 to $4,500 upfront feels like a stretch right now, here is a practical approach:
- Identify your single highest-ROI automation. What one workflow, if automated, would save the most time or generate the most revenue? For most businesses, this is lead follow-up or data entry between your two most-used systems.
- Start with one role. A 14-day paid pilot is $499, credited to month one. That is enough to prove the concept on your real phones before you commit to a plan.
- Reinvest the savings. Use the time and money saved from the first automation to fund the next one. Within 3 to 4 months, the automation is paying for itself and funding expansion.
This incremental approach lets you build your automation infrastructure without a large upfront investment, and every step pays for the next one. For ideas on which workflows to automate first, read our article on 5 signs your business needs AI automation.