“We should build our own AI solution.”

I’ve heard this from a dozen founders this year. I’ve built three custom AI systems myself. Here’s what nobody tells you about the real costs.

The Fantasy Budget

Most founders think custom AI costs:

• Some developer time (maybe 2-3 weeks)
• API costs (a few hundred bucks)
• Done

This is dangerously wrong.

The Actual Breakdown

Here’s what our last custom AI project really cost:

Discovery and Planning: $5,000-15,000 Before writing code, you need to figure out what you’re building. What data do you have? What decisions does the AI make? What happens when it’s wrong?

We spent three weeks on this. That’s 60+ hours of senior time.

Development: $20,000-50,000 Building the thing. Prompt engineering. Testing. Integration with your existing systems. Error handling. Edge cases.

Our “simple” chatbot took 8 weeks of development time.

Data Preparation: $5,000-20,000 AI is only as good as its data. Cleaning, formatting, organizing your data for AI consumption is tedious and expensive.

We spent two weeks just on this.

API Costs (Monthly): $200-2,000+ This one actually matches expectations. API calls are cheap. But they add up with scale.

Maintenance (Monthly): $1,000-5,000 Here’s the killer nobody mentions. AI systems need constant attention. Models change. Your data changes. Users find weird edge cases.

Budget 10-20 hours per month of developer time. Forever.

Failure Recovery: ??? When (not if) the AI does something wrong, what does it cost? For us, one hallucinated response cost a $15,000 deal.

Add it up and our “simple” AI project cost about $60,000 in year one. Ongoing costs are around $2,500/month.

The Alternative Calculation

Before building custom, always ask: what would an off-the-shelf solution cost?

For our chatbot, the closest SaaS alternative was $800/month. That’s $9,600/year with zero development risk, zero maintenance burden.

We chose to build because we needed specific integrations. But for most use cases, the math favors buying.

When Custom Makes Sense

Build custom AI when:

• Your use case is genuinely unique (be honest about this)
• You have technical talent already on staff
• The system is core to your product, not just a feature
• You’ve tested the concept with off-the-shelf tools first

Don’t build custom when:

• You just want AI for marketing purposes
• A SaaS tool does 80% of what you need
• You’d need to hire specifically for this project
• You’re hoping it’ll be “easy”

The Hidden Costs Nobody Mentions

Opportunity cost: Those 8 weeks of development? That’s 8 weeks your team wasn’t building your actual product.

Knowledge concentration: Now only one or two people understand how this system works. What happens when they leave?

Scope creep: Every AI project expands. “Can it also do X?” These requests never stop.

Expectation management: Once you have AI, everyone expects it to be magic. Managing disappointment is exhausting.

My Advice

Start with off-the-shelf tools. Always. Even if you plan to build custom eventually.

Use ChatGPT or Claude directly for 3 months. Understand what AI can and can’t do for your specific needs. Document the gaps. TechCrunch regularly covers which AI tools are worth paying for.

Then, if custom still makes sense, you’ll build something much better. And you might find you don’t need custom at all.

The best AI project is often the one you don’t build.