모든 템플릿

AI Contract Review & Redlining Adoption Survey

Measures legal professionals' adoption levels, satisfaction, barriers, and safeguard requirements for AI-assisted contract review and redlining. Designed for legal operations, in-house teams, and law firm practitioners.

샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 25개 · 약 11분
Q01
메시지

Welcome and thank you for participating in this survey about contract-review practices and AI tools. This survey is voluntary and confidential — you may stop at any time. There are no right or wrong answers; we are interested in your honest opinions and experiences from the last 3–6 months. Your responses will be anonymized and reported only in aggregate for internal research purposes. Estimated time: 11 minutes.

Q02
객관식

Does your current role involve reviewing, drafting, or redlining contracts?

  • Yes
  • No
Q03
드롭다운

How many contracts have you personally reviewed or redlined in the last 3 months?

  • 0
  • 1–5
  • 6–20
  • 21–50
  • 51+
Q04
객관식

In the last 6 months, have you used AI to assist with contract review or redlines?

  • Yes
  • No
Q05
객관식

What are the biggest barriers preventing you from using AI for contract review? Please select up to 3.

  • Data privacy/confidentiality risks
  • Quality/accuracy concerns
  • Lack of approval from leadership/IT
  • Client or counterparty restrictions
  • Cost/budget constraints
  • Unclear ROI or metrics
  • Ethical or professional responsibility concerns
  • Other (please specify)
Q06
의견 척도

How acceptable is it for your team to use AI to assist with contract redlines?

척도: 17
최소:Not at all acceptable최대:Completely acceptable
Q07
객관식

Which safeguards would you require before adopting AI for contract redlines? Select all that apply.

  • Data residency and confidentiality controls
  • Clear audit trail of AI changes
  • Explainable outputs with citations
  • Alignment with our playbooks/policy
  • Human-in-the-loop approval workflow
  • Vendor security certifications (e.g., ISO/SOC 2)
  • Indemnity or liability terms
  • Cost controls and usage limits
  • Ability to disable training on our data
  • Integration with DMS/CLM
  • Other (please specify)
Q08
장문형

Based on your responses in this survey, please share any additional thoughts or feelings about AI in your contract review workflow.

Q09
드롭다운

What is your primary role?

  • In-house counsel
  • Law firm attorney
  • Contract manager/paralegal
  • Procurement/sourcing
  • Legal operations
  • Other (please specify)
Q10
메시지

Thank you for completing this survey! Your insights will help shape how AI tools are developed and adopted for contract review. Your responses are confidential and will be reported only in aggregate.

Q11
의견 척도

How familiar are you with AI tools for contract review?

척도: 17
최소:Not at all familiar최대:Extremely familiar
Q12
객관식

Which AI-assisted capabilities have you used for contract work in the last 6 months? Select all that apply.

  • Clause extraction
  • Risk/issue flagging
  • Drafting suggested redlines
  • Playbook/policy alignment checks
  • Summarizing changes
  • Document triage or routing
  • Tested in pilots only (not live matters)
  • Other (please specify)
Q13
의견 척도

How much would you support AI drafting initial redlines for standard/boilerplate clauses?

척도: 17
최소:Strongly oppose최대:Strongly support
Q14
드롭다운

What minimum accuracy rate would you require before allowing AI to auto-apply standard redlines?

  • Below 85%
  • 85–89%
  • 90–94%
  • 95–97%
  • 98–99%
  • 100% (no errors acceptable)
Q15
AI 인터뷰

We'd like to explore your thoughts on AI in contract review a bit further. An AI moderator will ask a couple of follow-up questions based on your earlier responses.

Q16
드롭다운

How many years have you worked with contracts or practiced law?

  • 0–1
  • 2–5
  • 6–10
  • 11–20
  • 21+
Q17
의견 척도

Based on your experience using AI for contract review, how satisfied are you with the AI assistance you received?

척도: 17
최소:Not at all satisfied최대:Extremely satisfied
Q18
의견 척도

How much would you support AI flagging non-standard or high-risk terms for human review?

척도: 17
최소:Strongly oppose최대:Strongly support
Q19
드롭다운

Which best describes your organization type?

  • Company/in-house legal
  • Law firm
  • Alternative legal service provider
  • Government/public sector
  • Nonprofit/NGO
  • Other
Q20
의견 척도

How likely are you to continue using AI tools for contract review in the next 12 months?

척도: 17
최소:Not at all likely최대:Extremely likely
Q21
의견 척도

How much would you support AI automatically applying playbook-aligned redlines without human pre-approval?

척도: 17
최소:Strongly oppose최대:Strongly support
Q22
드롭다운

Approximately how many employees does your organization have?

  • 1–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
Q23
의견 척도

How much would you support AI summarizing counterparty changes and generating comparison reports?

척도: 17
최소:Strongly oppose최대:Strongly support
Q24
드롭다운

In which region are you primarily based?

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East & Africa
Q25
드롭다운

Which contract domain represents most of your work?

  • Commercial/Sales
  • Procurement/Vendor
  • Corporate/Transactions
  • Privacy/Data protection
  • Intellectual property
  • Employment
  • Other

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Combines closed-ended adoption metrics (usage frequency, familiarity, satisfaction, likelihood to continue) with an AI follow-up interview that lets respondents elaborate in their own words on AI in contract review
  • Goes beyond a single satisfaction score by measuring support levels for specific AI use cases separately — drafting boilerplate redlines, flagging high-risk terms, auto-applying playbook redlines, and summarizing counterparty changes
  • Captures concrete adoption barriers and required safeguards (including a minimum accuracy threshold before AI can auto-apply redlines), giving legal ops teams actionable guardrail data, not just sentiment
  • Segments results by role, experience, organization type, size, region, and contract domain so findings can be cut by practice area or seniority, then rolled into an auto-generated report

Jotform

Contract Review Form Template

This is a static intake/request form for routing a contract to a reviewer, not a research survey measuring AI adoption, satisfaction, or safeguard preferences. It's useful for operational contract workflows but doesn't collect attitudinal or adoption data at all. Fielding-ready as a form, but it isn't designed to study perceptions of AI-assisted review.

잘하는 점

  • Purpose-built for the contract domain, so field labels and workflow match legal document intake
  • Drag-and-drop customization typical of Jotform's form builder
  • Likely integrates with e-signature and file upload fields common to contract handling

아쉬운 점

  • No adaptive AI follow-up interviewing or voice interview option to probe why respondents feel a certain way
  • Not designed to measure adoption levels, barriers, or safeguard requirements — it's a routing form, not a research instrument
  • No automated response quality scoring or auto-generated analysis report

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