University of Phoenix Researchers Share Insights on Building Trust in AI-Driven Teams

Presentations at global qualitative research conference explore methods for maintaining credibility and collaboration in virtual, AI-enabled environments

Apr. 7, 2026 at 8:16pm

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A highly detailed, glowing 3D illustration of a complex neural network structure illuminated by pulsing neon cyan and magenta lights, conceptually representing the integration of AI systems into research workflows.As AI becomes more prevalent in research, new methods are needed to build trust in the credibility of findings and collaboration within virtual, technology-enabled teams.Phoenix Today

Researchers from the University of Phoenix College of Doctoral Studies and the Center for Educational and Instructional Technology Research (CEITR) presented studies on AI-integrated research teams, qualitative trustworthiness, and human-AI collaboration at The Qualitative Report (TQR) 17th Annual Conference. The researchers outlined practical approaches to evaluating team performance, strengthening trust, and distributing cognitive tasks between humans and AI systems in order to maintain credibility in virtual, AI-enabled research environments.

Why it matters

As artificial intelligence becomes more integrated into research and workplace environments, building trust in the credibility of the process and findings remains a critical challenge. The University of Phoenix researchers are developing methods to help teams effectively collaborate across distances, apply AI responsibly, and ensure rigorous qualitative analysis to support credible scholarship.

The details

The University of Phoenix researchers shared insights across multiple sessions at the TQR conference. Key takeaways include: 1) Maintaining trust in AI-enabled research depends on methodological rigor like credibility, dependability and confirmability; 2) Self-awareness and humility directly influence research team performance and help mitigate risks like imposter syndrome; 3) Q-methodology strengthens the study of human perspectives by combining qualitative depth with quantitative structure; 4) Human-AI collaboration can be optimized using Bloom's Taxonomy to clarify cognitive task distribution; and 5) Structured reflection and "remembered awareness" improve qualitative data analysis and reduce flawed interpretations.

  • The Qualitative Report (TQR) 17th Annual Conference was held from March 24-26, 2026.

The players

Mansureh Kebritchi

Chair of the Center for Educational and Instructional Technology Research (CEITR) and faculty in the College of Doctoral Studies at the University of Phoenix.

Steven Geer

Research consultant and DBA.

LauraAnn Migliore

Dissertation chair and faculty member at the University of Phoenix.

Karen Johnson

CEITR senior research fellow and faculty at the University of Phoenix.

Michelle Susberry Hill

Researcher and faculty at the University of Phoenix.

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What they’re saying

“As artificial intelligence becomes more integrated into research and workplace environments, trust remains the foundation of credible scholarship.”

— Mansureh Kebritchi, Chair of CEITR and faculty in the College of Doctoral Studies at the University of Phoenix

What’s next

The University of Phoenix researchers plan to continue exploring methods for building trust and collaboration in AI-integrated research environments. Their work will be presented at future academic conferences and published in scholarly journals.

The takeaway

The University of Phoenix research highlights the critical need to develop rigorous qualitative methods, foster self-awareness and humility within research teams, and optimize human-AI collaboration in order to maintain credibility and trust as artificial intelligence becomes more integrated into the research process.