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Call for Papers: Shaping the Future of Machine Leadership

Updated: 1 day ago

2025 Inaugural Edition


“How do you lead an AI tool that is better at human tasks than you are?” 

The Machine Leadership Journal is dedicated to advancing the emerging field of AI leadership. We are focused on identifying, developing, and sharing the best practices for AI strategy and adoption. This includes understanding the unique traits and cognitive processes that predict AI leadership success, the methods for integrating machines into the workforce, the process for safely introducing AI to children, and domain specific AI leadership practices that optimize use cases across industries. For our inaugural edition, we are seeking research studies and thought leadership articles that focus on five themes. Each area addresses a specific aspect of AI leadership, while providing a foundation for additional lines of inquiry. Though our Editorial Board maintains a robust peer review process, we welcome author(s) from a variety of professional and academic backgrounds, AI experience, and regional exposure.   

The Machine Leadership Journal is seeking contributions for its 2025 inaugural edition. Details regarding topic areas and submission requirements are listed below.​​

Focus Area 1: AI Talent Assessments 

Machines are a new species that requires leaders to have a broad set of skills. In the age of AI, leaders must be able to: 1) lead machines; 2) lead engineers that lead machines; and 3) lead hybrid organizations that adopt AI. Our Editorial Board is interested in research studies and/or thought leadership that highlights the unique competencies that are required to lead machines and AI teams. Topics may include but are not limited to: AI leadership traits, AI cognitive processes, talent assessment methods for AI leaders, and job role and readiness predictors for AI technical domains. Other focus areas could include unique AI leadership factors that impact key industries. The Board is interested in highlighting the similarities and differences between existing people leadership competency models and emerging AI leadership traits.​

Focus Area 2: The AI Playground 

The safe adoption of AI with children is a critical priority for society. This includes AI skills at each child development stage such as preschool, elementary, and adolescence. Our Editorial Board is interested in research studies and/or thought leadership that highlights methods, tools, or best practices for introducing AI to children. This may include but is not limited to: AI child development plans; child data privacy and cyber protection policies; toolkits for parents; and safe adoption practices. The Board is interested in methods for balancing child development between the physical and digital environments, ensuring optimal outcomes in both.​​​

Focus Area 3: AI Strategy and Adoption​

The ability to maximize AI within an organization or society are important practices. Our Board is interested in research studies and/or thought leadership that analyzes the process for effective adoption of AI. This may include but is not limited to: AI strategy development; managing the balance between Machine Autonomy and Trust; building AI competencies within the workforce; handling ethical AI dilemmas; data governance and privacy policies; keeping up with the pace of AI innovation; and leading change programs that introduce AI tools, platforms, and models. The Board is interested in approaches that balance productivity and automation with human centric design. Specifically, how companies can find the optimal approach to introducing AI without harming the organization’s culture. 

​​Focus Area 4: AI Leadership for Specific Domains 

AI leadership practices are strongly influenced by the industry and use case. Our Board is interested in research studies and/or thought leadership that highlights best practices for leading machines, engineers, and AI teams within specific contexts such as technical domains or industry use cases. This may include but is not limited to: AI leadership practices for the C-Suite; computer vision; robotics and autonomous vehicles; big data and MLOps; LLMs and Transformers; AI agents and Prompt Engineering; data governance and privacy; cyber security; and ethical AI. The Board is interested in AI leadership practices that impact the technical domain and specific industries. This includes AI leadership methods within technology, healthcare, telecom, energy, manufacturing, public sector, among others. ​​

Focus Area 5: The Future of AI 

The Future of AI is one where machines will be fully integrated into human society. Our Board is interested in research studies and/or thought leadership that forecasts potential pathways for innovation across all AI technical domains and use cases. This may include but is not limited to: AI enhancements to existing models such as LLMs and Transformers; new AI tools that will be introduced; scenarios where AI becomes further integrated into human life such as IoT and wearables; and new use cases impacting specific industries such as healthcare, finance, energy, among others. The Board is interested in visionary thinking that anchors projections based on historical adoption patterns, the current pace of AI innovation, and the potential pathways for individuals, organizations, and society to adopt new AI tools.

Submission Guidelines


Timeline


  • Abstract Proposals: Due by August 31, 2025
  • Full Proposals: September 30, 2025
  • Proposals and Ethical Guidelines Approved: October 31, 2025
  • Editorial Review: November through December 2025
  • DOI Assignment, Publication and Content Marketing: January 2026

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