The Quick Answer
AI automation projects typically range from $1,500 to $15,000+, depending on what you're building. I charge $110/hour, but most clients prefer fixed project pricing so there are no surprises.
Here's the realistic breakdown:
| Complexity | Price Range | Examples |
|---|---|---|
| Focused | $1,500 - $5,000 | Email workflows, data entry automation, system connectors |
| Mid-range | $5,000 - $15,000 | CRM integrations, custom chatbots, multi-step automations |
| Complex / Enterprise | $15,000+ | Multi-system platforms, custom AI models, full pipeline builds |
What Makes a Project "Simple" vs "Complex"?
It comes down to how many systems need to talk to each other and how much custom logic sits between them.
Focused ($1,500 - $5,000) means one or two systems connected with clear rules. Think: "When a new lead fills out my form, add them to my CRM and send a welcome email sequence." The input is clear, the output is clear, and the connection between them is a straight line.
These are the projects where the ROI is almost immediate. If you're spending 5-10 hours a week on something a bot could handle, a $2,000 automation pays for itself within a month or two.
Mid-range ($5,000 - $15,000) is where things get interesting. Multiple systems, conditional logic, error handling, and usually some kind of dashboard or reporting layer on top. Real examples I've built:
- An automated cold outreach tool that finds local businesses via Google Places, scores their websites, and generates personalized emails. Saved a client 20+ hours a week on manual lead research.
- Invoice payment detection that watches Stripe webhooks and email inboxes, matches payments to outstanding invoices, and sends follow-ups automatically.
- A content pipeline that pulls data from multiple sources, processes it through AI, and distributes it across channels on a schedule.
These projects involve decisions. The system needs to handle edge cases, retry failures, and give you visibility into what's happening. That takes more time to build properly.
Complex / Enterprise ($15,000+) means you're building a platform, not just connecting two tools. Multiple microservices, custom AI models or fine-tuned prompts, enterprise authentication, real-time dashboards, and the kind of reliability where "it went down for an hour" is unacceptable.
I built a capacity management platform for a major Canadian telecom that falls in this category. Cloud-native architecture on GCP, Jira integration, real-time reporting, role-based access. That's not a weekend project. But the value it delivers is proportional to the investment.
How I Price Projects
I charge $110/hour, but I almost always quote fixed project pricing. Here's why: hourly billing creates a weird incentive where the longer something takes, the more I get paid. That's not how I want to work.
Instead, I scope the project upfront during a free consultation, give you a fixed price, and stick to it. If I underestimate, that's on me. If the scope changes mid-project, we talk about it before any extra work happens.
A 2024 Clutch survey found that 68% of freelance clients prefer fixed pricing over hourly because it eliminates uncertainty. I agree. You should know exactly what you're paying before we start.
What Affects the Price
Scope and complexity are the obvious ones, but here's what people don't think about:
- Number of integrations. Every API you need to connect adds development and testing time. One integration is simple. Five integrations with different authentication methods and data formats is a different story.
- Error handling requirements. A bot that retries once on failure is cheap. A system that gracefully handles every edge case, logs errors, sends alerts, and self-recovers costs more. But it's also the difference between something that works in a demo and something that works in production.
- Data volume. Processing 100 records a day is trivial. Processing 100,000 requires different architecture.
- Compliance and security. If you're handling health data, financial records, or personal information, there are additional requirements that add to the build time.
What Drives the Cost Down
- Clear requirements. The Standish Group's CHAOS Report found that clear requirements reduce project costs by up to 50%. Know what you want before we start, and the project gets done faster and cheaper.
- Using proven tools. I don't build from scratch when existing APIs and frameworks already solve the problem. Claude API, GPT-4, Zapier, Make, custom Node.js scripts. I pick the right tool for the job, not the most impressive one.
- Phased delivery. Start with the automation that saves you the most time, get it running, then layer on additional features. You start seeing value immediately instead of waiting months for a complete system.
The ROI Math
Here's the thing that makes automation different from most business expenses: it pays for itself.
Say you're spending 15 hours a week on tasks that can be automated. At $30/hour for the employee doing that work, that's $450/week, or roughly $23,000 a year.
A $5,000 automation project pays for itself in about 11 weeks. After that, every hour saved is pure value. And the bot doesn't call in sick, doesn't need benefits, and works weekends.
McKinsey's 2024 research found that companies implementing AI automation see a 20-30% improvement in operational efficiency within the first year. For small businesses, the impact can be even more dramatic because you're often automating work that the owner is doing themselves. That's not just cost savings. That's getting your life back.
How to Get Started
The best first step is a conversation. Tell me what's eating your time, and I'll tell you what can be automated and what it'll cost. No sales pitch, no pressure. If automation doesn't make sense for your situation, I'll say so.
Most consultations take about 30 minutes. You'll walk away with a clear picture of what's possible and what it would cost, whether we work together or not.
Get a free consultation and find out what automation could do for your business.