At some point, every company building with AI faces the same question: do we hire our own team or work with an agency?

The answer depends on your stage, your budget, and how central AI is to your business. But most comparisons you'll find online are written by agencies (including this one — we'll be upfront about that). So let's skip the marketing spin and look at actual numbers.

The real cost of an in-house AI team

Let's price out a minimal AI engineering team for a US-based company in 2026.

The minimum viable AI team:

• 1 Senior ML/AI Engineer: $180K–$250K salary
• 1 Full-stack Developer (to build the product around the AI): $140K–$200K
• 0.5 DevOps/Infra (shared): $80K–$120K equivalent

Loaded cost (salary + benefits + equipment + overhead): Multiply base salaries by 1.3–1.5x for health insurance, 401k, equipment, software licenses, and office/remote stipends.

And that's before you factor in:

• Recruiting costs: 15–25% of first-year salary per hire, or $60K–$120K in recruiter fees
• Ramp time: 2–4 months before new hires are productive in your codebase
• Management overhead: Someone needs to set direction, review architecture, and unblock the team
• Tool costs: GPU compute, model API fees, monitoring, CI/CD — roughly $2K–$10K/month
• Retention risk: AI engineers are the most poached role in tech. Average tenure is 18–24 months.

Realistic Year 1 all-in cost: $700K–$900K

The real cost of an agency

Agency pricing varies wildly, so let's use two tiers.

US-based agency (top-tier):

• Hourly rate: $150–$250/hr
• Typical project (AI feature + integration): 400–800 hours
• Cost: $60K–$200K per project
• Monthly retainer: $15K–$40K/mo for ongoing support

Offshore/nearshore specialist agency (like Codse):

• Hourly rate: $45–$75/hr
• Same project scope: 400–800 hours
• Cost: $18K–$60K per project
• Monthly retainer: $3K–$12K/mo for ongoing support

The math is pretty clear for companies that don't need a full-time team yet.

When in-house makes sense

AI is your core product. If you're building an AI-first company — the AI IS the product — you need people who live and breathe your models every day. Agency context-switching can't match full-time focus.

You have ongoing, daily AI development work. If you need 160+ hours/month of AI engineering every single month, a full-time team starts to make economic sense. Below that threshold, you're paying for idle time.

You need deep institutional knowledge. Some domains (medical devices, defense, financial regulation) require engineers who deeply understand your compliance requirements. Building that knowledge in-house is sometimes the only option.

You can actually recruit and retain. This is the part companies underestimate. Posting a job listing for a senior AI engineer and actually getting one who accepts your offer, stays for more than 18 months, and performs well — that's harder than most founders expect.

When an agency makes sense

You're validating whether AI works for your use case. Don't hire a $250K engineer to test a hypothesis. Run a 4-week sprint with an agency. If it works, scale up. If it doesn't, you saved yourself a very expensive mistake.

You need to move fast. Agencies have teams ready to go. No recruiting, no onboarding, no ramp time. A good agency ships production AI features in 2–4 weeks. Hiring an in-house engineer takes 2–4 months before they write a line of code for you.

AI is a feature, not the product. If you're adding AI capabilities to an existing product — chatbot, document processing, workflow automation — you don't need a permanent team. You need a sprint to build it and a retainer to maintain it.

Your budget is under $500K/year for AI. Below that threshold, you'll get more output from an agency than a skeleton in-house team. One senior engineer costs $300K loaded and can only do one thing at a time. An agency gives you access to a team.

You need diverse expertise. AI projects often need ML engineering, backend development, frontend work, and infrastructure. An agency brings a cross-functional team. Hiring all those roles in-house is 3–4 full-time salaries.

The hybrid model

A lot of teams we work with do both:

1. Keep 1 technical AI lead in-house — someone who understands your data, sets the AI strategy, and evaluates vendor/agency output. This person doesn't need to build everything. They need to know what good looks like.

2. Use an agency for execution — the actual building, deploying, and iterating. The in-house lead reviews code, sets requirements, and makes architectural decisions. The agency does the heavy lifting.

You get institutional knowledge from the in-house lead, execution speed from the agency, and flexibility to scale hours up or down. One salary instead of three or four.

Cost: $180K–$280K (in-house lead) + $36K–$144K/year (agency retainer) = $216K–$424K/year

That's 40–60% less than a full in-house team.

Hidden costs people forget

In-house hidden costs:

• Opportunity cost of the founder's time spent recruiting and managing
• GPU and API costs that grow with experimentation
• Knowledge loss when engineers leave (and they will)
• Context-switching tax when your small team juggles AI + product + infra

Agency hidden costs:

• Communication overhead if the agency is in a far-flung timezone
• Dependency risk if the agency disappears or raises prices
• Ramp-up cost for a new agency to learn your codebase
• Quality variance between agencies (some are excellent, some aren't)

How to decide

Three questions to work through:

Step 1: Are you spending more than $500K/year on AI development right now?

• Yes → In-house team (or hybrid)
• No → Agency

Step 2: Is AI a core part of your product (not just a feature)?

• Yes → In-house lead + agency execution
• No → Agency-only

Step 3: Can you recruit and retain senior AI talent in your market?

• Yes, and we have budget → In-house
• No, or not yet → Agency now, hire later when you can offer more interesting work

---

Trying to figure out the right model for your company? See our managed retainer options — most clients start with a sprint and convert to ongoing support once they see the output. Or book a call to talk through your specific situation.