Software Developer
M1805
This job doesn’t expose everyone equally
⚡ AI hits junior profiles the hardest.
Future work distribution
Human only
Collaboration
AI only
This chart shows how the job's tasks split between humans and AI. "AI only" means a task AI can handle without a human — not a job removed: the role recomposes and the human refocuses on judgment, relationships and oversight.
AI Position of the Job
AI Impact on this job
You work in a role undergoing transformation: AI takes on routine tasks while enhancing your capacity for complex activities. This fact sheet indicates what AI performs directly and what it augments to make you more effective.
What will change
- Design test plans, scenarios, scripts or procedures: AI can automatically generate and execute test suites and repetitive scripts to a high degree, as it quickly traverses combinations and formalizes standardized procedures.
- Write, update and maintain programs for specific tasks: AI produces targeted code for automations, processing scripts or simple interfaces and applies routine fixes to a moderate degree, reusing proven patterns and libraries.
- Document software defects and feed tracking systems: AI extracts logs, identifies patterns and automatically drafts structured reports to a moderate degree, enabling the industrialization of incident logging.
What AI will improve
- Modify existing software to fix errors or improve performance: AI, providing a high level of assistance, suggests patches, refactorings and impact test scenarios, which speeds up iteration while leaving architectural decisions to you.
- Document and prioritize software defects: AI provides moderate assistance by enriching tickets with probable causes, reproduction steps and proposed prioritizations, which reduces triage time and facilitates your decisions.
- Design test plans and improve coverage: AI proposes coverage matrices, identifies edge cases and generates base scripts, offering high assistance on repetitive tasks so you can focus your efforts on test strategy and result analysis.
This result describes the occupation — not your role yet
Adjust your tasks, seniority and context to uncover your real exposure to AI.
For Software Developer, AI can already do 44% of tasks on its own — on average. What about you?
Your strengths against AI
Recommendations & outlook
Skills to develop
- Master AI tools and integrate them into your workflow (LLMs, IDE assistants, test generators, automated debugging).
- Strengthen supervision of AI-generated results and AI-assisted code reviews.
- Develop expertise in system design, security, and data governance to ensure solution reliability.
3-year outlook
In three years, AI will have reshaped daily work: it will handle many repetitive tasks and generate deliverables, but you’ll need to oversee, validate, and interpret results. The role will shift toward design, security, governance, and cross-functional collaboration, with sustained demand in organizations investing in human skills and quality.
AI tools used in this profession
Solutions deployed in production by professionals in this field
A general LLM assistant is already within reach
Before any specialized software, a latest-generation LLM assistant (Claude, ChatGPT, Mistral Le Chat, Gemini…) is available for this profession. Versatile, it helps draft, summarize, translate, structure or explore ideas. We treat it as a common baseline shared by almost every profession, distinct from specialized tools.
Understand this baselineMap your whole team's AI exposure
See at a glance which roles to transform first and where to invest in training.
Tasks most exposed to AI alone
8Tasks most augmented by AI
8Your role isn't an average.
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Frequently Asked Questions
While it's not certain that this profession will disappear, repetitive tasks will likely be automated, requiring you to evolve in your role. You'll have more opportunities by specializing in AI integration, system reliability, and business use-case management.
Highly skilled profiles will still be needed to design, integrate, and secure systems that interact with AI. Teams will be smaller but more specialized, shifting toward high-value tasks like system architecture and supervision rather than routine development.
Upskill in AI and data, learn MLOps and cloud deployment. Develop cross-functional skills such as business communication, project management, and staying updated on technological trends to anticipate changes and propose innovative solutions.