AI’s integration into business processes has reshaped organizational structures, introducing new forms of innovation and operational efficiencies. Feedback loops between humans and AI are critical to ensuring adaptive performance and co-learning. Recent research in human-AI interaction further stresses the importance of transparency and trust in reciprocal feedback systems, which helps mitigate automation bias and strengthens collaborative learning between human operators and AI. At the same time, the rapid co-evolution of AI and human systems raises critical ethical questions. Key concerns include fairness, accountability, transparency, and the risk of exacerbating social inequalities. Nevertheless, while ethical issues and fears of job displacement persist, cognitive augmentation—where AI systems support human decision-making and creativity—offers an alternative vision for the future of work. Researchers have also emphasized the need for reskilling and continuous learning to prepare workers for AI-augmented roles in the rapidly evolving job market.
Although extensive research has explored the potential of AI and its ethical quandaries, scant research has examined how AI and humans can co-evolve to ensure optimal organizational and societal outcomes. This Research Topic explores the emerging field of AI-human co-evolution. The ultimate goal of this Research Topic is to co-create a framework of knowledge that enables researchers, practitioners, and policymakers to better understand and facilitate AI-human co-evolution. This framework will provide practical guidelines for fostering sustainable growth, responsible innovation, and equitable human-AI partnerships. By integrating insights from multiple disciplines, the Research Topic aims to contribute to a growing body of knowledge on how AI can be harmoniously embedded in human-centered processes, creating value for both organizations and society at large.
The Research Topic will bring together interdisciplinary insights from computer science, organizational theory, ethics, and cognitive sciences to address four key dimensions: (1) Feedback Loop Design, (2) Organizational Innovation and Transformation, (3) Ethical Considerations and Responsible AI, and (4) Workforce Dynamics and Cognitive Augmentation.
Submissions may include original research articles, theoretical papers, systematic reviews, embedded case studies, and preliminary findings. All submissions will be peer-reviewed to ensure academic rigor and relevance. We invite contributions that address, but are not limited to, the following themes:
• Designing adaptive AI-human feedback loops • Organizational innovation through AI integration • Ethical frameworks for AI-human collaboration • The future of work in AI-augmented environments • Human-AI hybrid intelligence systems • Cognitive augmentation and decision-making • Embedded case studies of AI-human co-evolution • Systematic bibliographic reviews on AI and human-centered innovation
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
