Integrating HI × AI to Improve Problem Identification and Innovation Practice in Organizations
Research Foundation for HI × AI
Effective innovation requires more than generating ideas or adopting new technologies. Organizations must first understand the problems worth solving, create the conditions for change, implement solutions within complex human systems, and evaluate whether those solutions create meaningful value.
This annotated bibliography was developed as part of doctoral study in Organizational Innovation at National University. It examines the scholarly foundations informing AMPLIFIED! and the use of Human Insights × Artificial Intelligence to improve problem identification and innovation practice in organizations.
The research considers how Human Insights provide context, judgment, meaning, and direction while Artificial Intelligence expands analytical, generative, and computational capability.
Problem of Practice
Research across innovation, organizational learning, and Design Thinking demonstrates that organizations frequently struggle to establish consistent, scalable, and repeatable approaches for identifying problems and developing solutions.
Organizations may adopt technologies or pursue solutions before adequately understanding the underlying problem. The result can be initiatives that are misaligned with organizational needs, difficult to implement, or unsustainable over time.
The research supporting AMPLIFIED! examines how HI × AI can strengthen innovation across the full cycle—from understanding the problem through implementation, evaluation, and continued refinement.
Areas of Research
The annotated bibliography organizes the literature into six areas:
1. Internal Factors Influencing Innovation Adoption
Research addressing organizational culture, leadership, communication, readiness for change, and the internal conditions that influence whether innovation advances or stalls.
2. External Factors Influencing Innovation Adoption
Research examining market conditions, competitive pressures, institutional forces, regulation, technological change, and other environmental factors shaping innovation decisions.
3. Human Dynamics Influencing Innovation Implementation
Research exploring psychological safety, resistance to change, sensemaking, motivation, participation, and the human behaviors that affect implementation.
4. Organizational Dynamics Influencing Innovation Implementation
Research examining organizational systems, workflows, learning structures, feedback mechanisms, continuous improvement, and the conditions required to sustain innovation.
5. ROI and Value Realization
Research considering how organizations evaluate the financial, operational, experiential, and strategic value created through innovation.
6. Integrating Human Insights and Artificial Intelligence
Research addressing hybrid intelligence, human–AI collaboration, augmentation, organizational decision-making, and the complementary roles of human judgment and Artificial Intelligence.
Implications for AMPLIFIED!
Across the literature, innovation emerges as both a human and organizational systems process.
Technology alone does not create innovation. Effective adoption and implementation depend on context, leadership, culture, readiness, participation, learning, and alignment between organizational objectives and technological capability.
This research provides part of the scholarly foundation for AMPLIFIED! by examining how Human Insights can establish direction and meaning while Artificial Intelligence expands, challenges, analyzes, and accelerates the work.
Together, HI × AI provides a basis for investigating how organizations can improve problem identification, solution creation, implementation, and continuous learning.
About the Resource
Integrating HI × AI to Improve Problem Identification and Innovation Practice in Organizations was prepared by Kevin Popovic for EDD 800: Organizational Innovation at National University.
The 45-page annotated bibliography includes peer-reviewed and foundational research spanning organizational culture, innovation adoption, implementation science, organizational learning, Design Thinking, human–AI collaboration, and value realization.
