AI, Data Engineering & MLOps Survey 2025–2026
The AI space moves fast. There's a big gap between what's hyped and what works in production.
We asked professionals how they use AI, data engineering, MLOps, and developer-focused AI tools. These results show what people are using, what's still experimental, and where teams plan to invest.
Use these insights to make better decisions about tools and learning. We'll also use them to design courses and events that match what people actually need.
Survey conducted December 2025 - January 2026
Explore by Category
Respondent Demographics
Geographic distribution, job roles, organization size, and industry sectors of survey respondents.
6 questions
DataTalks.Club Community Involvement
Awareness and participation in DataTalks.Club activities and courses.
9 questions
Machine Learning & MLOps
Tools, practices, and challenges in ML engineering and operations.
16 questions
Data Engineering
Cloud platforms, tools, and challenges in data engineering workflows.
18 questions
AI Engineering & LLMs
Tools, frameworks, and challenges in building AI and LLM-based applications.
18 questions
AI Chatbots & Prompt-Based Tools
Usage patterns and productivity impact of AI assistants and coding tools.
12 questions