Will AI replace developers?
Updated
Software developers score 59 of 100 for AI exposure. The largest share of their task time, 79%, is work AI speeds up while they stay in charge. AI can take over 14% outright, and 7% stays with people.
- 14% AI can do it
- 79% AI helps
- 7% Needs a person
High exposure
Higher than 89% of the 923 occupations we scored.
Task by task
We graded 17 tasks, listed here from most to least exposed. AI can do 2 of them today, speeds up 13 and leaves 2 to people.
| Task | AI exposure |
|---|---|
| Prepare reports or correspondence concerning project specifications, activities, or status. Status reports and specification write-ups are routine writing AI handles well. | 78% AI can do it |
| Store, retrieve, and manipulate data for analysis of system capabilities and requirements. Querying, transforming and retrieving data is routine digital work AI scripts handle. | 68% AI can do it |
| Develop or direct software system testing or validation procedures, programming, or documentation. AI drafts test cases, validation scripts and docs; engineer directs and approves. | 65% AI helps |
| Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance. Coding assistants draft most fixes; developer still verifies hardware and integration. | 65% AI helps |
| Analyze information to determine, recommend, and plan installation of a new system or modification of an existing system. AI can analyze requirements and draft installation plans; humans decide on changes. | 50% AI helps |
| Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design. AI speeds coding and simulation; engineers still take responsibility for design and outcome predictions. | 45% AI helps |
| Monitor functioning of equipment to ensure system operates in conformance with specifications. AI monitoring tools flag anomalies against specs; people investigate and respond. | 45% AI helps |
| Determine system performance standards. AI can suggest benchmarks and metrics, but choosing standards needs expert judgement. | 40% AI helps |
| Coordinate installation of software system. Deployment scripts are automatable, but coordinating rollout across teams stays human. | 40% AI helps |
| Obtain and evaluate information on factors such as reporting formats required, costs, or security needs to determine hardware configuration. AI can compare cost and security options; hardware choice needs human accountability. | 40% AI helps |
Show the other 7 tasks
| Task | AI exposure |
|---|---|
| Analyze user needs and software requirements to determine feasibility of design within time and cost constraints. AI can draft feasibility estimates, but stakeholders and tradeoffs need human judgement. | 35% AI helps |
| Train users to use new or modified equipment. AI drafts training guides and FAQs; in-person user instruction remains human. | 35% AI helps |
| Consult with customers or other departments on project status, proposals, or technical issues, such as software system design or maintenance. Customer status and proposal communication is mostly human; AI drafts supporting material. | 30% AI helps |
| Confer with data processing or project managers to obtain information on limitations or capabilities for data processing projects. Gathering constraints from managers is interpersonal; AI helps summarize prior information. | 28% AI helps |
| Confer with systems analysts, engineers, programmers and others to design systems and to obtain information on project limitations and capabilities, performance requirements and interfaces. Requirements meetings with people need live judgement; AI only drafts notes. | 25% AI helps |
| Supervise the work of programmers, technologists and technicians and other engineering and scientific personnel. Supervising staff is people management requiring accountability and interpersonal judgement. | 15% Needs a person |
| Supervise and assign work to programmers, designers, technologists, technicians, or other engineering or scientific personnel. Assigning and overseeing staff work is management with little AI substitution. | 14% Needs a person |
How software developers compare
All occupations (923)
Computer and mathematical (36)
Pay and outlook in the US
- Median pay
- $135,980 a year, May 2025
- People employed
- 1.7 million in the US, May 2025
- Projected change in jobs
- +10.2% from 2024 to 2034
Skills to build
- Verify AI-drafted code and fixes against Amazon EC2 deployments
- Design and tune Amazon DynamoDB data models
- Build AJAX front-end features and debug browser integration
- Lead requirements meetings with customers and project managers
- Hold the AWS Certified Developer Associate credential
Safer roles nearby
5 related occupations with lower scores.
Questions about software developers and AI
Will devops be replaced by AI?
Partly. About 5 in 10 working hours go to tasks AI can already do, mostly writing status reports and specification write-ups, and querying, transforming and retrieving data. What stays with people is the requirements meetings, design tradeoffs and final approval of code that ships.
Will AI take over computer science jobs?
AI can already do 14% of the task time in computer science and speeds up another 79%. People still do 7% of it. The US has 1.7 million software developer jobs, with a projected change of +10.2% from 2024 to 2034.
Which software developer tasks is AI taking over?
Status reports and specification write-ups carry the highest exposure, at 78, because AI drafts routine writing well. Data querying, transformation and retrieval follows at 68, since AI scripts handle that digital work. Test case drafting and code fixes, at 65, are largely drafted by coding assistants while the developer verifies the result.
Which software developer tasks stay human?
Supervising programmers and assigning their work scores lowest, at 14 and 15, because it depends on accountability and interpersonal judgement. Consulting customers on proposals, project status and technical issues scores 30, since live conversation carries the outcome and AI only drafts supporting material. Feasibility decisions on time and cost constraints, at 35, still need human judgement over the tradeoffs.
How can software developers stay valuable?
Focus on the steps that need a person to sign off, namely verifying generated code, designing data models and leading requirements meetings. Test AI-drafted fixes against Amazon EC2 deployments, design Amazon DynamoDB data models, and set feasibility limits with stakeholders before any estimate goes out.
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