Volume 1, Issue 1

Fall 2026 · Business • Education • Technology · Research, Ideas, and Innovation

Welcome to the inaugural issue of Wolf Business Review. Volume 1, Issue 1 brings together evidence-informed writing across education, workforce development, leadership, cybersecurity, and artificial intelligence. The issue reflects WBR’s interdisciplinary mission: to make serious ideas accessible, practical, and useful while maintaining clear standards for evidence, citation, transparency, and editorial review.

Welcome to Wolf Business Review

Read Editor’s Note →

Wolf Business Review was created to provide an accessible, credible home for research, professional insight, and forward-looking ideas across Business, Education, and Technology. In this inaugural note, Founder and Editor-in-Chief Ted Wolf introduces WBR’s mission, editorial values, and commitment to transparent human judgment in an increasingly AI-enabled publishing environment.

In this issue

004

Cybersecurity Belongs in the Curriculum

A practical case for integrating cybersecurity concepts into teaching, digital citizenship, and responsible technology use.

Ted Wolf

Editorially reviewed by Wolf Business Review. Not externally peer reviewed.
005

When Everyone Has AI, What Becomes Valuable?

AI does not eliminate scarcity—it moves scarcity. A transparent AI-generated analysis under human editorial oversight.

Wolf Business Review
Generated by OpenAI’s ChatGPT
Human Editor: Ted Wolf

Not externally peer reviewed.
Issue review and transparency note. Wolf Business Review distinguishes editorial review from peer review. Unless an individual article specifically states otherwise, articles in Volume 1, Issue 1 received WBR editorial review and final human editorial approval but were not externally peer reviewed. AI-assisted editorial tools may support review, citation checking, and publication preparation; final editorial decisions are made by the human Editor-in-Chief.

Publication: Wolf Business Review · Volume: 1 · Issue: 1 · Season: Fall 2026 · Format: Digital-first · Citation model: Article numbers rather than page ranges.

Your work can be part of the next issue.

Submissions are evaluated on the quality and contribution of the work rather than academic rank, institutional prestige, professional title, or career stage.