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Treat GenAI like an employee: a conceptual framework for the use of GenAI in small business

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Purpose
    This study aims to develop a practical and ethical framework and guidelines for small businesses to overcome several barriers to the adoption and use of generative artificial intelligence (GenAI) by small business. The use of GenAI offers positive benefits for social impact through well-being if managed ethically.

    Design/methodology/approach
    A conceptual approach was used that integrates two theoretical and practice-based frameworks; the passive–interactive–proactive (PIP) framework and code of ethics for professional accountants and professional standards.

    Findings
    The authors propose treating GenAI like a human, and in doing so, they offer a new conceptual framework; the ethical AI, smarter small business framework. They also develop a set of onboarding guidelines for getting started with GenAI to train the tool.

    Practical implications
    This framework and onboarding process can encourage small businesses to take small steps in using GenAI to build confidence and competence. By humanising the technology as an employee, small businesses can draw on familiar employee scripts to leverage the strengths of GenAI. This research can create a positive social impact for small-business owners.

    Originality/value
    This research provides the first set of guidelines for small businesses to adopt and use GenAI in an ethical and responsible manner through humanising the technology as an employee. In doing so, this research identifies three levels of engagement with the technology and extends the PIP framework from consumer contexts to business contexts. This type of initiative is new in the AI literature embracing ethical and responsible use of GenAI.
    Original languageEnglish
    Pages (from-to)1-16
    Number of pages16
    JournalJournal of Social Impact in Business Research
    Volume2
    Issue number 3
    DOIs
    Publication statusPublished - Dec 2026

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