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In-House AI Engineer vs External AI Consultancy: Total Cost of Ownership
Quick Take / Direct Answer
A full-time AI engineer in the US costs $156,000–$224,000 per year (salary + benefits + overhead). This buys one engineer's capacity, requires 3–6 months to hire and onboard, and creates a single point of knowledge risk. A specialist AI consultancy at $30,000–$55,000 per system delivers a production-ready system in 6–10 weeks with multiple specialists, established patterns from comparable builds, and no hiring risk. For organisations building their first 1–3 AI systems, external consultancy is consistently lower-risk and lower-cost.
The Full Cost Comparison
In-house AI engineer:
- Base salary (US): $120,000–$160,000
- Benefits and payroll taxes (30–40%): $36,000–$64,000
- Equipment, software, training: $10,000–$20,000
- Management overhead: $15,000–$30,000 (manager's time)
- Recruiting cost: $25,000–$50,000 (one-time)
- Ramp time (3–6 months): No productive output
- Total year 1 (fully loaded): $206,000–$324,000
- Total year 2+: $181,000–$274,000/year
External AI consultancy (Govistudio model):
- System 1 (discovery + build + first-year maintenance): $50,000–$85,000
- System 2 (year 2): $35,000–$65,000
- System 3 (year 2–3): $35,000–$65,000
- Total 3 systems over 2 years: $120,000–$215,000
What you get for each:
- In-house: one engineer who can build anything (high flexibility, high cost, high risk)
- Consultancy: three production systems with ongoing support (lower flexibility, lower cost, lower risk, faster time-to-value)
When In-House Makes Sense
In-house AI hire becomes the right choice when:
- The organisation plans to build 5+ AI systems over 24 months
- The use cases are highly proprietary and require ongoing custom development
- The organisation has the management infrastructure to hire and retain top AI engineering talent
- There is a clear path to a 3-person AI team (one engineer is too fragile)
When Consultancy Makes Sense
External consultancy is the right choice when:
- Building the first 1–3 AI systems
- Time-to-value is critical (5–8 weeks vs 6–9 months to hire + ramp)
- The organisation lacks AI engineering recruiting infrastructure
- Risk tolerance is low (proven delivery partner vs untested internal hire)