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.
Let's price out a minimal AI engineering team for a US-based company in 2026.
The minimum viable AI team:
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.
| Role | Salary | Loaded Cost |
|---|---|---|
| Sr. AI Engineer | $220K | $286K–$330K |
| Full-stack Dev | $170K | $221K–$255K |
| DevOps (0.5 FTE) | $95K | $124K–$143K |
| Total Year 1 | $631K–$728K |
And that's before you factor in:
Realistic Year 1 all-in cost: $700K–$900K
Agency pricing varies wildly, so let's use two tiers.
US-based agency (top-tier):
Offshore/nearshore specialist agency (like Codse):
| Model | Year 1 Cost (2 projects + retainer) |
|---|---|
| In-house team | $700K–$900K |
| US agency | $180K–$520K |
| Specialist agency | $54K–$180K |
The math is pretty clear for companies that don't need a full-time team yet.
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.
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.
A lot of teams we work with do both:
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.
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.
In-house hidden costs:
Agency hidden costs:
Three questions to work through:
Step 1: Are you spending more than $500K/year on AI development right now?
Step 2: Is AI a core part of your product (not just a feature)?
Step 3: Can you recruit and retain senior AI talent in your market?
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.
Get a full AI engineering team on demand — without the $700K annual cost of hiring in-house.
Explore serviceCustom AI agents built, deployed, and maintained — from sprint to production retainer.
Explore serviceFor most companies spending under $500K/year on AI, an agency is significantly cheaper. A minimal in-house AI team costs $700K-$900K in Year 1 when you factor in salaries, benefits, recruiting, and ramp time. A specialist agency delivers the same output for $54K-$180K.
Hire in-house when AI is your core product, you need 160+ hours per month of continuous AI work, or your domain requires deep institutional knowledge (medical devices, defense, financial regulation). Otherwise, an agency or hybrid model is more cost-effective.
Keep one technical AI lead in-house to set strategy and evaluate output. Use an agency for execution — building, deploying, and iterating. This gives you institutional knowledge and execution speed at 40-60% less than a full in-house team.
Expect 2-4 months from posting the role to having a productive team member. That includes recruiting (4-8 weeks), offer negotiation, notice periods, and onboarding ramp time. An agency can start delivering in the first week.