AI is already reshaping business research. Are your decisions defensible?
Artificial intelligence is already embedded across the business research lifecycle, from literature review to data analysis and manuscript development. Faculty, doctoral supervisors, and research leaders are now expected to make decisions about AI use in real time, often without clear standards or institutional guidance.
The risk is no longer whether AI is used. The risk is whether that use is consistent, defensible, and aligned with emerging expectations from journals, institutions, and accreditors. This course addresses that gap.
Course Overview
This one-day course is designed to help participants move from informal or inconsistent AI use to structured, responsible, and defensible research practices. Rather than focusing only on tools, the course emphasizes:
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Identifying ethical risks in AI-supported research
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Applying core principles such as transparency, accountability, bias mitigation, and integrity
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Interpreting and applying institutional and journal expectations
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Making and justifying research decisions with confidence
Participants will work through realistic scenarios, engage in structured analysis, and leave with a practical framework they can apply immediately. This course represents the Developing / Guided Practice stage of the Ethics of AI in Business Research credential.
Why This Course Matters Now
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AI is increasingly referenced in accreditation and assurance of learning expectations
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Journal policies on AI use are evolving rapidly
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Many institutions lack clear or actionable guidance
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Inconsistent practices create risk for: research integrity, faculty evaluation, doctoral supervision, institutional credibility
Without a structured approach, AI use in research becomes difficult to justify and even harder to defend.
What You Will Learn
By the end of this course, participants will be able to:
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Identify where AI is used across the research lifecycle and where risks emerge.
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Explain core ethical principles relevant to AI-supported research.
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Distinguish appropriate, questionable, and high-risk uses of AI.
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Apply institutional and journal guidance to research scenarios.
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Evaluate AI-supported research challenges using structured ethical reasoning to develop and justify defensible responses.
Who Should Attend
The course is designed for:
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Faculty currently using or considering AI in research
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Doctoral supervisors navigating AI use in student work
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PhD students and early-career researchers developing research practices
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Research leaders responsible for maintaining integrity and consistency
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Institutional staff supporting research policy, compliance, or faculty development
What You Will Take Away
Participants will leave with:
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A practical framework for evaluating AI use in research
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Increased confidence in making defensible decisions
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Experience applying ethical principles to realistic scenarios
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Clearer understanding of journal and institutional expectations
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A starting point for aligning individual practice with institutional responsibility
What Makes This Course Different
This is not a theoretical discussion of AI ethics. This is a decision-focused learning experience designed to help you:
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Recognize risks before they become problems
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Apply principles in context, not in isolation
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Justify your decisions to colleagues, reviewers, and leadership
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Begin aligning your work with emerging institutional and accreditation expectations
Credential Pathway
This course is the first step in the Ethics of AI in Business Research credential pathway:
- Course 1: Foundations of Ethical AI Use in Business Research
- Course 2: Ethical AI in Research Design and Data Management
- Course 3: Responsible AI in Analysis and Scholarly Communication
- Course 4: Leading Ethical AI Practice in Business Research
Participants progress from guided application to independent decision-making and institutional leadership.
If you are already using AI in your research, this course will help ensure your decisions are defensible. If you are not yet using AI, it will prepare you for the decisions you will soon be expected to make.
Contact Us
For more information, contact [email protected].
