Systems Analyst and Designer
M1848
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 are an IT analyst-designer, and AI augments your profession without replacing it. It takes on repetitive and documentation tasks, while you retain ownership of requirements analysis, technical design, and trade-offs.
AI takes care of routine and documentation tasks while amplifying your role in analysis, design, and technical decision-making.
What will change
- Writing manuals and technical documentation, AI produces standardized content and updates from code and specifications to save time.
- First-level corrective maintenance, AI identifies recurring incidents in logs and applies fixes or repair scripts for known cases.
- Generation of basic technical models and diagrams, AI proposes typical architectures based on proven patterns when requirements are formalized.
What AI will improve
- Accelerating the drafting and updating of documents, you select, validate, and adapt the content to business constraints and target audiences.
- Assisting with handling user feedback and evolutionary maintenance, AI provides diagnostics, suggested fixes, and scripts that you oversee and integrate.
- Support for analysis and design, AI generates scenarios, prototypes, and actionable diagrams that you enrich, prioritize, and transform into operational specifications.
This result describes the occupation — not your role yet
Adjust your tasks, seniority and context to uncover your real exposure to AI.
For Systems Analyst and Designer, AI can already do 32% of tasks on its own — on average. What about you?
Your strengths against AI
Recommendations & outlook
Skills to develop
- Master AI tools (LLMs + specialized tools) to automate documentation drafts, requirements analysis, and solution modeling.
- Strengthen the ability to evaluate and validate AI outputs, ensuring compliance, security, and data ethics.
- Develop skills in AI project management and data governance to secure solution integration and optimize value creation.
3-year outlook
In three years, AI will be even more embedded in core tasks, placing supervision, framing, and governance at the heart of the profession. The risk for teams lies in significant role restructuring: some traditional positions will shrink, while new roles focused on AI system oversight and advisory will emerge. The challenge is to align with business needs while mastering security and quality requirements.
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.
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Tasks most exposed to AI alone
7Tasks most augmented by AI
7Your role isn't an average.
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Frequently Asked Questions
No, this profession will not disappear due to AI, but it will evolve. AI handles repetitive and simple analytical tasks, allowing your role to refocus on architecture, defining needs, and integrating solutions, areas that require business insight and a user-centered approach. You’ll benefit from developing skills in project management, security, and data ethics to remain indispensable.
The number of people required depends on project size and the organization's digital maturity. In companies undergoing transformation, profiles that cover business analysis, technical design, and change management are in demand, which may sustain team size. You can transition into roles like technical lead, architect, or project manager, adding strategic value while staying relevant.
To adapt, strengthen cross-functional skills between business and technology: architecture, data management, and user experience. Invest in training related to AI, system urbanization, and security, and seek assignments that allow you to act as a mediator between business teams and technical staff. Finally, expand your network and your ability to lead agile projects to support change within your organization.