AI vs. Software Engineer: What Replacement Actually Costs
Coding assistants show the clearest productivity gains of any knowledge role — and the widest gap between demo and production reality.
These figures come from the DroidWork TCO model for a Software Engineer at mid level, on a base salary of $136,000. The employee figure is fully loaded — benefits, payroll tax, overhead, management time and recruiting amortisation — not base salary. The AI figure sums all seven cost dimensions, not tokens alone.
Where the money actually goes
Token cost is 2.0% of total AI cost for this role. The remaining 98.0% is what standard vendor ROI models omit.
| Cost dimension | Annual |
|---|---|
| Tokens / compute | $4,028 |
| Hosting & infrastructure | $39,800 |
| Security & compliance | $53,500 |
| Process failure & rework | $42,300 |
| Residual human oversight | $49,532 |
| Total AI TCO | $198,618 |
Agentic loop multiplier. Coding agents iterate — plan, write, run tests, read the failure, rewrite. That loop is where token spend multiplies 4–10× over a naive estimate.
What AI does well here
Boilerplate generation, test scaffolding, documentation, code translation, and first-pass review comments. These are genuinely 30–60% faster with a competent assistant.
What stays human
System design, debugging production incidents under time pressure, and judgement calls about technical debt. The work that makes engineers expensive is the work AI helps with least.
The honest verdict
AI reduces the cost per engineer far more reliably than it reduces the number of engineers. Model this as augmentation with a real productivity delta, not headcount removal.
Run this for your own numbers
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Open the Calculator for This Role →Frequently asked
Can AI fully replace a software engineer?
Not at current capability. AI reliably compresses the routine 40–50% of engineering work, but system design, incident response, and accountability for production systems still require an engineer. The defensible business case is throughput per engineer, not headcount reduction.
Why is the AI cost higher than the token estimate I was quoted?
Because coding is agentic. A single task triggers multiple plan-execute-observe loops, each re-consuming a growing context window. Vendor quotes price one API call; real usage bills for the whole loop.
What is the most commonly missed cost?
Human review time. Generated code still needs an engineer to read, verify, and own it. That residual oversight labour is a real line item and it does not disappear as models improve — it shifts.
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Modelled estimate for planning purposes only; not financial, legal or employment advice. Salary baselines from BLS OES, Radford/Aon and Glassdoor 2025–2026 data. Full assumptions and sources are documented in the methodology, and the model is open source. Your results will differ — that is the point; run your own inputs.