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AI & Technology

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.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

28 questions · ~12 min
Q01
Message

Welcome, and thank you for your interest in this study. We are conducting research to better understand how research teams use technology tools in their work. Your participation is completely voluntary, and you may stop at any time. There are no right or wrong answers — we are interested in your honest opinions and experiences. All responses are confidential, will be anonymized, and reported only in aggregate. Results will be used for internal research purposes. This survey takes approximately 10-14 minutes to complete. By continuing, you confirm that you understand the above and agree to participate.

Q02
Multiple Choice

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
Q03
Multiple Choice

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)
Q04
Multiple Choice

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)
Q05
Multiple Choice

Has your team used any AI-powered tools for research purposes in the past 12 months?

  • Yes
  • No
  • I'm not sure
Q06
Multiple Choice

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)
Q07
Multiple Choice

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
Q08
Ranking

When evaluating an AI tool for research use, please rank the following criteria from most important (1) to least important (7).

  1. Accuracy and reliability of outputs
  2. Ease of use and learning curve
  3. Data security and privacy compliance
  4. Integration with existing tools and workflows
  5. Cost and licensing
  6. Transparency of how the AI works
  7. Vendor support and documentation
Drag to rank
Q09
Opinion Scale

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

Scale: 1 – 5
Min:Not at all importantMax:Extremely important
Q10
Opinion Scale

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

Scale: 1 – 5
Min:Not a barrier at allMax:A major barrier
Q11
AI Interview

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?

Q12
Multiple Choice

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
Q13
Opinion Scale

How would you rate the quality of AI-related training your team has received?

Scale: 1 – 7
Min:Very poorMax:Excellent
Q14
Multiple Choice

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)
Q15
Opinion Scale

Compared to traditional (non-AI) research methods, how would you rate the quality of outputs produced by AI-powered research tools?

Scale: 1 – 7
Min:Much lower qualityMax:Much higher quality
Q16
Opinion Scale

How confident are you in the accuracy of data collected or analyzed using AI tools?

Scale: 1 – 7
Min:Not at all confidentMax:Extremely confident
Q17
Opinion Scale

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

Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q18
Multiple Choice

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)
Q19
Multiple Choice

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
Q20
Opinion Scale

To what extent has the introduction of AI tools changed how your team collaborates on research projects?

Scale: 1 – 7
Min:Significantly worsened collaborationMax:Significantly improved collaboration
Q21
Opinion Scale

Overall, how satisfied is your team with the AI tools currently used in your research workflow?

Scale: 1 – 7
Min:Not at all satisfiedMax:Extremely satisfied
Q22
Opinion Scale

How likely is your team to expand its use of AI tools for research in the next 12 months?

Scale: 1 – 7
Min:Not at all likelyMax:Extremely likely
Q23
Long Text

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.

Q24
Dropdown

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)
Q25
Multiple Choice

How many people are on your research team?

  • 1-3
  • 4-7
  • 8-15
  • 16-30
  • More than 30
Q26
Dropdown

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)
Q27
Multiple Choice

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
Q28
Message

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.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

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    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

Frequently asked questions

What questions are in the “AI Tool Adoption in Research Teams” template?

The template includes 28 ready-to-use questions, starting with: “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?”. The full set is previewed above, and every question is editable.

How long does this survey take to complete?

Respondents typically finish the 28 questions in about 12 minutes.

Can I customize this template?

Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.

Is this template free to use?

Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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