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Weekly Workload & Support Pulse Survey

A recurring pulse instrument measuring employee workload manageability, pace sustainability, support quality, and improvement priorities. Designed for weekly fielding to track burnout risk and inform resourcing decisions.

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Sample questions

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

15 questions · ~8 min
Q01
Message

Welcome to this week's pulse check. This brief survey asks about your workload and support over the last 7 days. It should take about 2–3 minutes to complete. Your responses are confidential and will be reported only in aggregate — no individual answers will be shared with your manager. Participation is voluntary, and there are no right or wrong answers. Your honest feedback helps us improve how we support our teams.

Q02
Opinion Scale

Overall, how manageable did your workload feel over the last 7 days?

Scale: 1 – 7
Min:Not at all manageableMax:Completely manageable
Q03
Opinion Scale

How supported did you feel by your direct manager over the last 7 days?

Scale: 1 – 7
Min:Not at all supportedMax:Very well supported
Q04
Ranking

For next week, rank the improvements that would help you most (top = most helpful).

  1. Clearer priorities
  2. Fewer meetings
  3. Dedicated focus-time blocks
  4. More reliable tooling
  5. Faster cross-team decisions
  6. Temporary workload coverage
Drag to rank
Q05
Long Text

Based on your responses, is there anything else you'd like to share about your workload or support experience this week?

Q06
Dropdown

Which department or function do you primarily work in?

  • Engineering
  • Product
  • Design
  • Data/Analytics
  • Sales
  • Marketing
  • Customer Support
  • Operations
  • People/HR
  • Finance
  • Legal
  • Other
  • Prefer not to say
Q07
Message

Thank you for completing this week's pulse check. Your feedback is reviewed in aggregate and directly informs how we plan resourcing and support. See you next week!

Q08
Opinion Scale

How sustainable did the pace of your work feel over the last 7 days?

Scale: 1 – 7
Min:Not at all sustainableMax:Completely sustainable
Q09
Opinion Scale

How supported did you feel by your team or peers over the last 7 days?

Scale: 1 – 7
Min:Not at all supportedMax:Very well supported
Q10
AI Interview

We'd like to understand more about your experience this week. An AI interviewer will ask a couple of brief follow-up questions based on your earlier responses.

Q11
Multiple Choice

What is your current work arrangement?

  • On-site
  • Hybrid
  • Fully remote
  • Prefer not to say
Q12
Dropdown

How many of the last 7 days did you work beyond your usual hours?

  • 0 days
  • 1 day
  • 2 days
  • 3 days
  • 4 days
  • 5 days
  • 6 days
  • 7 days
Q13
Dropdown

How long have you been at the company?

  • Less than 3 months
  • 3 to 12 months
  • 1 to 3 years
  • 3 to 5 years
  • 5+ years
  • Prefer not to say
Q14
Multiple Choice

What made your workload harder to manage in the last 7 days? Select all that apply.

  • Unclear or shifting priorities
  • Too many meetings or interruptions
  • Staffing constraints or handoffs
  • Urgent or last-minute requests
  • Cross-team dependencies
  • Tooling or environment issues
  • Process friction (e.g., reviews, approvals)
  • Nothing in particular
Q15
Multiple Choice

What region do you primarily work in?

  • Americas
  • EMEA
  • APAC
  • Prefer not to say

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.

  • AI-drafted copy

    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.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • AI interviews dynamically adapt based on whether respondents are early adopters, skeptics, or non-users—capturing qualitative depth at quantitative scale
  • Affordable academic pricing makes it accessible for the university researchers studying AI adoption who are priced out of Qualtrics
  • Every AI parameter is logged for replication—critical for the peer-reviewed AI adoption research that competitors' tools cannot support
  • AI follow-up questions probe beyond surface-level Likert ratings to uncover root causes of disengagement—something no static survey can do
  • Full transparency: every prompt, model, and logic flow is visible to HR researchers, unlike competitor 'black box' AI features

SurveyMonkey

AI Readiness Assessment Template

SurveyMonkey's AI Readiness Assessment is the closest match—evaluating employee AI awareness, training needs, and current tool usage. Solid for organizational readiness but doesn't specifically measure feature-level adoption, trust, or perceived value of AI capabilities.

What it does well

  • Covers employee awareness, comfort levels, and perceived impacts of AI
  • Includes risk, compliance, and ethical considerations alongside adoption questions
  • Fully customizable with branding, and AI-powered analysis suite for open-ended responses

Where it falls short

  • Focused on organizational readiness, not specific AI feature adoption or value perception
  • No conversational AI follow-ups to explore trust barriers or adoption hesitancy in depth
  • SurveyMonkey's own AI tools (Build with AI, analysis) operate as black boxes—no prompt or model transparency
  • No validated trust measurement scales—uses general readiness questions rather than academic trust constructs

Qualtrics

Qualtrics XM for Strategy + Research

Qualtrics publishes extensive research on AI trust gaps (e.g., their State of AI in Employee Experience report analyzing 35,000+ employees) but doesn't offer this as a self-serve template. Their conversational feedback feature is the most competitive AI-interview capability in the market.

What it does well

  • Conversational feedback uses generative AI to generate follow-up questions during live surveys—respondents contribute 40% more information
  • Own research demonstrates deep expertise in AI trust measurement at organizational scale
  • 23 question types including video/audio responses with advanced logic branching

Where it falls short

  • No public pre-built AI feature adoption or trust survey template—requires custom building
  • Pricing starts at $420/month, making it inaccessible for academic researchers and small teams
  • Conversational feedback AI is not researcher-configurable—no access to prompts, no model selection, no parameter logging
  • Enterprise-focused platform creates unnecessary complexity for straightforward adoption studies

Jotform

Technology Surveys

Jotform offers 100+ technology survey templates including some AI-adjacent ones (AI-Augmented Learning Perception, Healthcare AI Bias Awareness, Public Perception of Health AI Tools), but none specifically targeting AI feature adoption and trust in a product or workplace context.

What it does well

  • Largest volume of AI-adjacent survey templates among competitors (100+ technology surveys)
  • Free plan available with drag-and-drop customization and conditional logic
  • Separate AI Agents product offers conversational survey experiences with NLP

Where it falls short

  • No dedicated AI feature adoption or trust survey template—closest options are domain-specific (healthcare, education)
  • AI Agents are a separate product from form templates—not integrated into survey methodology
  • No academic methodology validation, no rubric checking, no scale construction guidance
  • AI Agent training is opaque—no visibility into prompts, models, or reasoning logic for researchers

SurveyMonkey

Employee Engagement Survey Template

Well-established template with benchmarking capabilities and expert-written questions across motivation, leadership, growth, recognition, and culture themes. Strong analytics with filters and crosstabs, but fundamentally limited to static question-and-answer format.

What it does well

  • Industry benchmarking data to compare scores against other organizations
  • Standardized 5-point Likert scale with built-in scoring methodology
  • Extensive customization and segmentation by team or location

Where it falls short

  • No AI-powered follow-up questions to explore the 'why' behind low scores
  • Static survey format cannot adapt to individual employee responses in real-time
  • AI features limited to survey creation assistance, not actual respondent interaction

Typeform

Employee Engagement Survey Template

Visually appealing one-question-at-a-time conversational format that improves completion rates. Strong UX and branding customization, but the 'conversational' experience is still pre-scripted—it doesn't actually listen and adapt like AI.

What it does well

  • Beautiful, conversational one-question-at-a-time interface that feels less like a survey
  • Strong integrations with Slack, Microsoft Teams, and 300+ tools
  • Excellent mobile experience with no app downloads required

Where it falls short

  • No AI follow-up probes—conversational format is just UX, not intelligent adaptation
  • No transparent AI methodology—no visible prompts or logic for researchers to audit
  • Limited survey methodology rigor—focuses on design over academic-grade question construction

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