AI Is Creating Anxiety.
This Project Creates Clarity.
AI is everywhere, but most people still do not know what is useful, what is hype, where to start, or how to use AI without feeling overwhelmed.
AI Adoption At Work 2026 is an independent public-good research project designed to understand what helps people move from AI anxiety, resistance, or scattered experimentation into more confident, useful AI adoption.
You’re Not Behind.
You’re not failing.
You’re not supposed to magically understand every new AI tool, every update, every prompt, or every use case.
The world is asking people to navigate AI without a map.
This project is the map
A public benchmark and practical toolset designed to show where people are on the AI adoption curve, what is holding them back, what kinds of AI use feel realistic, and what helps different people move forward with more confidence.
What This Research Will Help Answer
AI adoption is not one thing. Some people are avoiding it. Some are curious but anxious. Some are experimenting without a plan. Some are using it regularly, but only in narrow ways. Others are starting to integrate it into how they work.
This project will identify what people want from AI, where they are in the adoption journey, what is holding them back, and what helps each type of adopter move forward.
Research Questions
1. What Do People Actually Want AI To Help Them Do?
We will identify whether people are looking for speed, confidence, better decisions, reduced mental load, learning, creativity, income opportunity, or practical workflow support.
2. What Type Of AI Adopter Are People, And Where Are They On The Adoption Curve?
We will classify people into practical AI adoption segments and measure where they are in the journey, from denial and resistance to exploration, acceptance, integration, and leveraging. This matters because each type of adopter needs different guidance, reassurance, use cases, and support.
3. What Is Really Blocking Adoption?
We will diagnose the human barriers behind resistance, including trust, privacy, job fear, performance anxiety, workflow disruption, lack of understanding, loss of control, inadequate training, bias concerns, technology fatigue, human-connection concerns, and poor change communication.
4. Which AI Use Cases Feel Useful, Safe, And Realistic For Each Type Of Adopter?
We will identify which AI applications people are most willing to try based on their adoption segment, stage, confidence level, concerns, role, and work context.
5. What Would Make AI Feel More Worth Using?
We will quantify the conditions that make AI feel more useful, trustworthy, controllable, understandable, and relevant, including reliability, privacy, transparency, ease of use, human backup, and clear boundaries.
6. What Support Helps Each Type Of Adopter Move To The Next Stage?
We will identify the training, messaging, safeguards, examples, proof points, and confidence-builders each adoption segment needs to move forward.
See our methodology page for more in-depth details about the project
What We’ll Deliver
1. Report on AI Adaptability Trends
A publically available White Paper that reports on what drives successful AI adoption — and what doesn’t.
2. Find out how you work with AI
An online quiz to understand your AI adoption patterns and what tools make sense for you.
3. See if your organization is ready for AI
An online assessment tool of your organization to know where AI fits, what to prioritize, and what to fix first.
Our Stretch Goals
If we exceed our funding goal, we can expand the project and make the findings even more useful.
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125% funded: Create short video series summarizing key findings for maximum shareability
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150% funded: Add a social listening phase to examine themes in AI discourse on platforms such as Reddit and X
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175% funded: Publicly available dashboard featuring basic analytics of data w/ integrated chatbot to provide insights
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200% funded: Add a qualitative research phase to interview AI users to inform the survey and develop AI chatbots that adopt the personality of each Adapter Segment
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250% funded: Expand the study to include international comparison (additional countries or languages)
A Typing Tool That Turns Research Into
A Personal Roadmap
Most AI research tells people what is happening in the market. This project goes further.
The AI Adoption Typing Tool will help people understand where they are in the adoption journey and what kind of support they need next.
Each person will receive:
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Their AI Adoption Type
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Where They Are On The Adoption Curve
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Their Biggest Adoption Barriers
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The Use Cases Most Likely To Fit Them
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The Conditions That Would Make AI Feel More Useful
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Their Recommended Next Steps
The goal is not to label people as “pro-AI” or “anti-AI.”
The goal is to give people a clearer path forward based on their motivations, concerns, confidence level, and real work context.
Why This Project Is Different
Most AI content is created by companies, platforms, vendors, consultants, or influencers with something to sell.
This project is different.
AI Adoption At Work 2026 is designed as independent, transparent, public-good research.
No hype. No hidden agenda. No vendor influence. No pay-to-play findings.
The goal is simple: create practical research that helps people, small businesses, contractors, and teams make better AI decisions.
Sponsors Can Support The Research. They Cannot Shape The Research.
Supporters help make the project possible. They do not control the questions, methods, findings, interpretation, or recommendations.
Who benefits from this research
People are overwhelmed. Small businesses are confused. Enterprises are stuck in pilot purgatory.
See our enterprise sponsorship tiers if you think your organization would be interested in this work.
How The Research Will Work
The project will use survey research to study how people think about, use, resist, and adopt AI in real work contexts.
The survey will examine:
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AI Adoption Stage: Where people are on the journey from resistance to leveraging.
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Desired Outcomes: What people actually want AI to help them do.
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Adoption Barriers: What slows people down or keeps them from using AI effectively.
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Use-Case Interest: Which AI applications feel useful, safe, and realistic.
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Trust Conditions: What makes AI feel more reliable, understandable, and controllable.
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Support Needs: What training, examples, safeguards, or guidance people need next.
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Ideal AI Experience: What kind of AI experience people actually want.
This project is lead by
Meet the Research Team
See who are leading the project
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How you can support our research
AI is moving fast. The public needs clearer, more independent guidance on how people actually adopt it, what holds them back, and what helps them move forward.
Your support funds the full research process: survey design, data collection, analysis, segment development, report writing, public tools, data visualization, and project updates.
Every contribution helps turn AI confusion into independent public research that people, small businesses, contractors, and teams can actually use.
Support the project. Share it. Help build clarity in a noisy AI world.
Make a donation
See this page for detailed descriptions of the supporter tiers
$0 raised
0 donations
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Amount
Curious
$3
Interested Observer
$15
Research Supporter
$35
Research Partner
$75
Data Explorer
$150
Co-Investigator
$500
Other
0/100
Comment (optional)
Independence & Transparency Charter
This charter is the backbone of the project.
It’s how we ensure the world gets something it can trust.
1. No sponsor or backer can influence the research
No enterprise, vendor, or individual can edit, shape, cancel, or bias the findings.
2. All funding flows are transparent
Through Open Collective, every dollar in and out is publicly visible.
3. All methods are published openly
Sampling, analysis, frameworks, and limitations are shared publicly.
4. All deliverables are public
The benchmark report, segment profiles, tools, and assessments are free and accessible.
5. No data is sold
Backer data, survey data, and research data are never sold or shared with vendors.
6. No hidden agenda
We are not selling a product. We are building a public resource.
7. No enterprise influence
Enterprise backers receive early access — not editorial control.
8. No vendor involvement
This project is not funded by AI companies, tool vendors, or consultancies.
9. No pay‑to‑play
No one can buy their way into the findings.
10. Radical transparency
We build in public, publish updates, and show our work as it develops.
Help Build The AI Clarity People Need
AI should not feel like chaos.
It should feel understandable, useful, and human.
AI Adoption At Work 2026 exists to help people understand where they are, what is holding them back, what use cases fit, and what to do next.
If you want AI to feel less overwhelming and more empowering, support the project today.