AI Tool Adoption in Research Teams
A survey studying how research teams evaluate, adopt, and integrate AI tools for data collection, analysis, and reporting. This instrument measures current tool usage, evaluation criteria, adoption barriers, training experiences, data quality perceptions, and team collaboration patterns.
Preguntas de ejemplo
Una vista previa del contenido de la plantilla. Todas las preguntas son editables antes de publicar.
Are you currently a member of a team that conducts research activities (e.g., data collection, analysis, or reporting) as part of your work?
- Yes
- No
Which of the following best describes your team's primary research focus?
- Market research
- Academic / scientific research
- User experience (UX) research
- Policy / social research
- Data science / analytics
- Clinical / health research
- Other (please specify)
When evaluating an AI tool for research use, please rank the following criteria from most important (1) to least important (7).
- Accuracy and reliability of outputs
- Ease of use and learning curve
- Data security and privacy compliance
- Integration with existing tools and workflows
- Cost and licensing
- Transparency of how the AI works
- Vendor support and documentation
To what extent have each of the following been barriers to AI tool adoption in your research team? 1. Budget or cost constraints 2. Lack of technical skills on the team 3. Concerns about data privacy or security 4. Skepticism about AI output quality 5. Resistance to change from team members 6. Lack of organizational support or policy 7. Difficulty integrating with existing workflows 8. Uncertainty about ethical implications
Has your team received any formal training on using AI tools for research?
- Yes, comprehensive training
- Yes, but only introductory or basic training
- No, but training is planned
- No, and no training is planned
Compared to traditional (non-AI) research methods, how would you rate the quality of outputs produced by AI-powered research tools?
How does your team typically make decisions about which AI tools to adopt?
- Individual team members choose their own tools
- Team lead or manager decides for the team
- Collaborative team decision through discussion
- IT or technology department mandates tools
- Organization-wide policy dictates tool choices
- Other (please specify)
Overall, how satisfied is your team with the AI tools currently used in your research workflow?
Which of the following best describes your role within your research team?
- Principal investigator / Lead researcher
- Senior researcher / Analyst
- Junior researcher / Research assistant
- Research manager / Director
- Data scientist / Engineer
- Research operations / Coordinator
- Other (please specify)
Thank you for completing this survey! Your responses are valuable and will help us understand how research teams are navigating the adoption of AI tools. Your responses have been recorded and will remain confidential. If you have any questions about this study, please contact the research team at the email provided in your invitation.
Which of the following tools does your research team currently use on a regular basis? (Select all that apply)
- Spreadsheet software (e.g., Excel, Google Sheets)
- Statistical software (e.g., SPSS, R, Stata)
- Survey platforms (e.g., Qualtrics, SurveyMonkey)
- Qualitative analysis tools (e.g., NVivo, Atlas.ti)
- Data visualization tools (e.g., Tableau, Power BI)
- Project management tools (e.g., Asana, Trello)
- Reference management tools (e.g., Zotero, Mendeley)
- Coding/programming environments (e.g., Python, Jupyter)
- AI-powered tools (e.g., ChatGPT, Copilot, Jasper)
- Other (please specify)
How important is each of the following when your team evaluates AI tools for research? 1. Accuracy and reliability of outputs 2. Ease of use and learning curve 3. Data security and privacy compliance 4. Integration with existing tools 5. Cost and licensing 6. Transparency of AI methods 7. Vendor support and documentation
You mentioned some barriers to AI adoption. Can you describe the most significant challenge your team has faced when trying to adopt or consider AI tools for research?
How would you rate the quality of AI-related training your team has received?
How confident are you in the accuracy of data collected or analyzed using AI tools?
How frequently does your team share knowledge or best practices about AI tools with each other?
- Daily
- A few times a week
- About once a week
- A few times a month
- Rarely
- Never
How likely is your team to expand its use of AI tools for research in the next 12 months?
How many people are on your research team?
- 1-3
- 4-7
- 8-15
- 16-30
- More than 30
Has your team used any AI-powered tools for research purposes in the past 12 months?
- Yes
- No
- I'm not sure
Which of the following training formats would be most useful for your team to learn AI research tools? (Select up to 3)
- Hands-on workshops with live practice
- On-demand video tutorials
- Written guides or documentation
- Peer-led knowledge sharing sessions
- Vendor-provided onboarding and demos
- Online courses or certifications
- Mentoring or coaching from AI-experienced colleagues
- Other (please specify)
To what extent do you agree or disagree with the following statements about AI tools and research quality? 1. AI tools help reduce human error in data analysis 2. AI tools can introduce new types of bias into research 3. I trust AI-generated outputs enough to include them in final reports without extensive manual review 4. AI tools make it easier to replicate research processes 5. The lack of transparency in how AI tools work concerns me
To what extent has the introduction of AI tools changed how your team collaborates on research projects?
Based on your responses throughout this survey, please share any additional thoughts or feelings about how AI tools are shaping research in your team or field.
Which sector does your organization primarily operate in?
- Technology / Software
- Healthcare / Pharmaceuticals
- Financial services
- Education / Academia
- Government / Public sector
- Consulting / Professional services
- Consumer goods / Retail
- Media / Entertainment
- Nonprofit / NGO
- Other (please specify)
Which AI-powered tools has your team used for research? (Select all that apply)
- Large language models (e.g., ChatGPT, Claude, Gemini)
- AI coding assistants (e.g., GitHub Copilot, Cursor)
- AI-powered survey/interview tools (e.g., QuestionPunk)
- AI data analysis tools (e.g., Julius AI, DataRobot)
- AI transcription/note-taking (e.g., Otter.ai, Fireflies)
- AI writing/editing assistants (e.g., Grammarly AI, Jasper)
- AI image/media generation tools
- AI-powered literature review tools (e.g., Elicit, Semantic Scholar)
- Other (please specify)
How many years of experience do you have in research?
- Less than 1 year
- 1-3 years
- 4-7 years
- 8-15 years
- More than 15 years
Which stage best describes your team's current level of AI tool adoption for research?
- Unaware — We haven't considered AI tools for research
- Aware — We know about AI tools but haven't tried any
- Exploring — We are experimenting with AI tools on a trial basis
- Implementing — We are actively integrating AI tools into some research workflows
- Embedded — AI tools are a standard part of our research process
Qué incluye
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Preguntas frecuentes
¿Qué preguntas incluye la plantilla «AI Tool Adoption in Research Teams»?
La plantilla incluye 28 preguntas listas para usar, empezando por: «Welcome, and thank you for your interest in this study. We are conducting research to better understand how research te…» · «Are you currently a member of a team that conducts research activities (e.g., data collection, analysis, or reporting) a…» · «Which of the following best describes your team's primary research focus?». El conjunto completo se muestra arriba y todas las preguntas son editables.
¿Cuánto se tarda en completar esta encuesta?
Los participantes suelen terminar las 28 preguntas en unos 12 minutos.
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