Business schools need
to prepare graduates for workplaces in which generative artificial intelligence
(GenAI) shapes analysis, communication, customer insight, and decision support.
Yet the field still lacks a business-school-specific account of what students
should learn beyond tool familiarity. This structured narrative review
synthesizes recent literature on AI literacy, business-student preparedness,
ethical readiness, and curriculum integration in business education. It draws
together four areas of evidence: business-student readiness and adoption, AI
literacy and competency frameworks, AI ethics literacy and ethical reflection,
and business-school curriculum and implementation. The literature indicates
that business students increasingly use GenAI, although much current use
remains concentrated in general-purpose academic tasks. More advanced business
applications, especially data analysis and decision support, appear less
developed. Ethics belongs within business AI literacy because privacy, bias, accountability,
transparency, disclosure, and professional responsibility shape managerial use
of AI. The review proposes a five-domain Business AI Literacy and Ethical
Capability Framework: foundational AI and generative AI understanding, business
application and decision-support fluency, critical evaluation and verification,
ethical and governance judgment, and transparent professional communication and
adaptive learning. The framework begins with recurring AI literacy dimensions
in the literature and adapts them to business education using business-student
and business-school evidence. It also outlines a three-stage curriculum
progression model and discusses implications for pedagogy, assessment, faculty
development, and institutional policy. The framework gives business schools a
practical way to connect AI use with verification, ethics, and professional
judgment across the curriculum.
