IT Systems Analyst
M1852
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 as an IT research analyst, a role where AI augments you without replacing you. Artificial intelligence handles routine tasks and strengthens your ability to design, decide on, and lead projects.
AI performs repetitive and documentation-related tasks while enhancing your expertise for complex analysis and design.
What will change
- Perform repetitive tests and validations, because AI automates running test suites, detects regressions, and prioritizes anomalies to address.
- Document processes and systems, because AI generates and updates technical documentation from code and specifications, providing structured and searchable versions.
- Design and model initial proposals, as AI quickly produces mockups, diagrams, and architectures based on known patterns, covering a large portion of preliminary scoping work.
What AI will improve
- Perform tests and validations: AI suggests relevant test sets, highlights edge cases, and frees you to focus on business investigations and complex integration testing.
- Document processes and systems: AI drafts documents and harmonizes terminology, allowing you to validate the content and add the necessary operational context.
- Collaborate with developers to implement solutions: AI suggests code snippets, verifies API contracts, and facilitates review, which speeds up integration under your supervision.
This result describes the occupation — not your role yet
Adjust your tasks, seniority and context to uncover your real exposure to AI.
For IT Systems Analyst, AI can already do 29% of tasks on its own — on average. What about you?
Your strengths against AI
Recommendations & outlook
Skills to develop
- Master AI tools (LLMs and specialized tools) for designing, testing, and documenting; implement governance for AI outputs and quality controls.
- Develop user support, remote workshop facilitation, and change management skills.
- Strengthen expertise in specification writing, project management, and business data understanding; regularly practice collaborative workshops with business teams.
3-year outlook
In three years, AI will be deeply embedded in analysis and specification drafting, accelerating timelines and improving reliability. Teams will see a reshaping of roles: more business expertise, project management, and consulting, with increased pressure on priority management and quality. Some organizations will need to rethink their structures to leverage productivity gains while maintaining sufficient human oversight.
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
6Tasks most augmented by AI
7Your role isn't an average.
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Frequently Asked Questions
No, this profession won’t disappear with AI, but it will evolve. AI and automation handle repetitive tasks, allowing you to focus on interpreting results and managing projects. Your role will shift toward more strategic expertise in business analysis and data governance.
The need for IT study analysts will remain, but staffing levels depend on the company and its automation level. While automation reduces certain tasks, you’ll still be essential for interpreting results, proposing actions, and ensuring alignment with business goals. The most sought-after profiles combine technical skills with business knowledge and the ability to communicate results to stakeholders.
To adapt, focus on strengthening both technical and business skills. Enhance your expertise in SQL, Python or R, data visualization, and governance, while deepening your understanding of the domains you work in. Engage in cross-functional projects, pursue training, and regularly update your portfolio with real-world cases.