Finding Leaders Worth Following
AI User Research
Understanding Human-AI Interaction Through Behavioral Science
Artificial intelligence is changing how people work, learn, communicate, create, and make decisions.
But successful AI products are not built solely on powerful algorithms, they succeed when people understand them, trust them, and are willing to use them.
Dr. Change helps organizations understand how humans experience AI by combining behavioral science, mixed-methods research, qualitative inquiry, and user experience research to evaluate AI products, intelligent systems, copilots, and automation.
Rather than asking whether an AI model is technically accurate, we investigate whether people can effectively interact with it.
Because successful AI is ultimately about human behavior
Navigating the AI Airspace: Why Your Organization Needs a Control Tower 🛩️🤖
Why AI User Research Matters
Imagine your company’s AI initiatives as airplanes. Right now, you might have a few experimental models taking off. But as LLMs, predictive algorithms, and automated workflows multiply, your digital airspace gets crowded fast.
Without coordination, you face a high risk of organizational collisions, costly model drift, compliance violations, or ethical blind spots.
Organizations often measure AI performance through technical metrics:
- Accuracy
- Precision
- Recall
- Latency
- Cost
Users evaluate AI differently.
They ask questions like:
- Can I trust it?
- Does it make my work easier?
- Do I understand its recommendations?
- Is it helping me make better decisions?
- Does it feel intuitive?
- Would I continue using it?
AI User Research bridges the gap between technical performance and human adoption.
Our Philosophy
Artificial intelligence should augment human decision-making, not replace it.
Human-centered AI begins with understanding people.
Our approach combines:
- Behavioral Science
- Human Factors
- User Experience Research
- Qualitative Research
- Organizational Psychology
- Responsible AI Principles
- Mixed-Methods Research
to evaluate how people actually experience intelligent systems.
Rather than viewing AI through an engineering lens alone, we examine how humans perceive, interpret, trust, and collaborate with AI in real-world environments.
AI User Research Services
Human-AI Interaction Research
Understand how users interact with AI-powered systems throughout their workflows.
Research may include:
- Human-AI Collaboration
- Workflow Observation
- Behavioral Analysis
- AI Adoption Studies
- User Decision Processes
- User Mental Models
AI Usability Testing
Evaluate whether AI-powered products are intuitive, understandable, and efficient.
Services include:
- Moderated Usability Testing
- Task-Based Evaluation
- User Observation
- Workflow Analysis
- Friction Identification
- Interface Evaluation
AI Trust Research
Trust determines adoption.
We investigate the factors that influence user trust in AI systems, including:
- Transparency
- Explainability
- Confidence
- Reliability
- Perceived Accuracy
- Human Oversight
- Decision Confidence
AI Adoption Research
Successful AI implementation depends on user acceptance.
Research areas include:
- Adoption Barriers
- Resistance to AI
- Organizational Readiness
- User Acceptance
- Technology Adoption
- Change Readiness
Stakeholder & User Interviews
Interview the people who matter most.
Research participants may include:
- End Users
- Executives
- Product Managers
- Developers
- Subject Matter Experts
- Customers
- Employees
Interview findings reveal how AI influences behavior, workflows, expectations, and organizational outcomes.
AI Journey Mapping
AI experiences extend beyond individual prompts.
Journey Mapping identifies:
- User touchpoints
- Moments of uncertainty
- Trust breakdowns
- Decision bottlenecks
- Adoption opportunities
Deliverables include:
- AI User Journey Maps
- Experience Gap Analysis
- Opportunity Maps
- Behavioral Recommendations
Responsible AI Governance & Launching Products & Services that Actually Sell Starts with Effective AI User Research
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Frequently Asked Questions
Is AI User Research the same as Responsible AI?
No.
Responsible AI is a broad discipline that includes governance, policy, ethics, compliance, risk management, and technical safeguards.
AI User Research focuses specifically on the human experience of AI, how people understand, trust, adopt, and interact with intelligent systems.
The two disciplines are complementary.
Do you evaluate AI models?
Our focus is not on benchmarking model performance.
Instead, we evaluate how humans experience AI systems, ensuring that products are intuitive, trustworthy, and aligned with user needs.
Do you conduct qualitative or quantitative research?
Dr. Change specializes in mixed-methods research, integrating qualitative depth with quantitative measurement to provide comprehensive behavioral insight.
Do you provide Responsible AI consulting?
Yes.
Behavioral research can support Responsible AI initiatives by informing governance decisions, improving transparency, strengthening human oversight, and identifying adoption risks. While our primary focus is AI User Research, these insights naturally complement broader Responsible AI strategies.
How We Can Help
Research Methods
Depending on organizational objectives, engagements may utilize:
Qualitative Methods
- Semi-Structured Interviews
- Behavioral Interviews
- Observation
- Think-Aloud Studies
- Contextual Inquiry
- Diary Studies
- Thematic Analysis
- Phenomenological Research
Quantitative Methods
- Survey Research
- User Satisfaction Measurement
- Trust Scales
- Behavioral Analytics
- Mixed-Methods Integration
- Descriptive Statistics
Typical AI Research Questions
Organizations often ask:
- Why aren't users adopting our AI tools?
- Why don't employees trust our AI recommendations?
- Which AI features create the most value?
- Where does user frustration occur?
- How should human oversight be incorporated?
- How can explainability improve adoption?
- What factors influence confidence in AI-generated outputs?
- How should AI fit into existing workflows?
Behavioral science helps answer these questions.
Who We Support
AI User Research benefits organizations across many industries.
Examples include:
- AI Product Companies
- Technology Organizations
- SaaS Platforms
- Healthcare
- Financial Services
- Government
- Education
- Enterprise Software
- Human Resources Technology
- Customer Experience Teams
- Research Organizations
Deliverables
Every engagement is tailored to organizational objectives.
Common deliverables include:
- AI Research Plans
- Interview Guides
- User Personas
- Journey Maps
- Behavioral Themes
- Executive Research Reports
- Strategic Recommendations
- Product Improvement Priorities
- AI Adoption Insights
- Trust & Experience Findings
Why Dr. Change?
Most AI consultants begin with technology.
Dr. Change begins with people.
Our background combines:
- Behavioral Science
- Organizational Leadership
- Doctoral-Level Qualitative Research
- Consumer Insights
- UX Research
- Organizational Psychology
- Leadership Assessment
- Mixed-Methods Research
- Responsible AI Principles
This multidisciplinary perspective allows us to understand not only how AI functions, but how humans experience it.
Better AI Begins with Better Human Understanding
Artificial intelligence is transforming organizations.
Behavioral science ensures it transforms them responsibly.
Whether you're evaluating a new AI product, improving adoption, understanding user trust, or integrating AI into organizational workflows, Dr. Change provides research that places human experience at the center of intelligent technology.
