Editorial methodology
How each strategic brief is developed.
AI Business Strategy Daily is designed to turn rapidly changing AI developments into original, transparent, and practically useful analysis for business leaders.
Research and source selection
Each daily strategic brief evaluates a minimum of five and typically no more than ten relevant sources. Primary evidence—official announcements, technical documentation, regulatory material, research papers, earnings disclosures, and company publications—is prioritized. Credible secondary reporting is used to add context or independent scrutiny.
Sources must directly support the claims attributed to them. Unverified statistics, invented citations, and unattributed quotations are not permitted.
Original analysis
The publication does more than summarize news. Each article considers what a development changes for competitive strategy, customer value, operating models, governance, leadership, or organizational execution. Practical implications and questions for executives make that analysis actionable.
Doctoral research lens
Relevant articles may draw on four findings from Dr. Gates' doctoral research: understanding competitors and market disruption; using effective transformation strategy to improve execution; developing leaders capable of producing value from digital innovation; and understanding the innovations customers will adopt and value.
The research is used as an analytical lens rather than as a compulsory reference. A connection is included only when it materially improves the analysis.
Academic and program relevance
Articles periodically identify capabilities, cases, and questions relevant to graduate study in AI business strategy. Dr. Gates serves as Assistant Professor and Program Director of the M.S. in AI Business Strategy program at Eastern University. The views expressed in this independent publication are his own and do not necessarily represent Eastern University.
A(DT)2 applications
When appropriate, an article may apply the current A(DT)2 Agile Design Thinking Digital Transformation Framework to a business challenge. The authoritative framework is the version displayed on this website—not the earlier conceptual figure appearing in the doctoral dissertation.
Explore the current A(DT)2 framework →Human review and publication
Technology may assist with research organization, comparison, and initial drafting. No article is published automatically. Dr. Anton Gates reviews the evidence, analysis, language, and recommendations and explicitly approves every article before publication. Material corrections are identified through the article's modification date.