IMPORTANT INFORMATION
If you expect to take ARTI3000 - Business Applications for Artificial Intelligence in 2026, please take the 2026 substitute BUSI2001 - Emerging Technologies, Data and Business Analytics as a replacement.

Business Applications for Artificial Intelligence

Undergraduate

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Mode
Mode
Your studies will be on-campus, and may include some online delivery
On campus
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Area/Catalogue
ARTI 3000
Course ID icon
Course ID
200281
Campus icon
Campus
Adelaide City Campus West
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course owner
Course owner
School of Accounting and Fin
Course level icon
Course level
3
Work Integrated Learning course
Work Integrated Learning course
No
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
Discipline group A
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes

Course overview

This course aims to cater to students from diverse disciplines, providing them with a comprehensive understanding of how AI is transforming the business landscape and shaping the future of various industries. By bridging the gap between technology and social disciplines, this course empowers students to navigate the complexities of Industry 4.0 with confidence, enabling them to become proactive leaders and innovators in the AI-driven business world.

  • Artificial Intelligence and Decision

  • AI-Assisted Decision-Making Applications

  • System Design for Business 

Course learning outcomes

  • Critically analyse the anatomy of decisions to determine where AI can genuinely improve judgment and where human accountability, values, and context must remain central, across a range of professional domains.
  • Apply Python to build, test, and interpret decision-support tools, testing underlying assumptions rather than accepting model output uncritically.
  • Design end-to-end AI-augmented workflows that allocate roles appropriately between human and AI contributors, and that embed accountability, override mechanisms, and feedback loops suited to the stakes and structure of the decision.
  • Critically evaluate how AI is reshaping professional expertise, accountability, and governance requirements, and communicate the practical and ethical implications of AI-assisted decision-making to technical and non-technical stakeholders alike.

Prerequisite(s)

  • must have completed BUSI1009 Predictive and Visual Analytics for Managers and Consultants

Corequisite(s)

N/A

Antirequisite(s)

N/A

Assumed knowledge

Students are expected to have completed business analytics foundation courses including Python programming.

Textbook(s)

N/A

Inherent requirements

N/A

Other resources

This course uses: 1. Textbooks and other Learning Material: "AI Textbook for Managers: A Practical Guide to AI-Assisted Analysis and Decision-Making” by Ilker Cingillioglu, Springer Reach, available as hardcopy or ebook (https://www.amazon.com.au/Textbook-Managers-Practical-AI-Assisted-Decision-Making) or free on Kindleunlimited. Important: Note that this is one resource and not the only source of truth. This is a recommended textbook which is not expected to be purchased. Students using an alternative text would be expected to do equally as well as those using this textbook. 2. Online Platforms: Google Colab: A user-friendly free cloud-based interactive development environment (IDE) for Python programming and experimentation. 3. Programming Tools: Python 3.x: A versatile programming tool commonly used in text analytics, offering a rich ecosystem of built-in libraries.

Assessment

  • Multiple Choice Questions – 20%
  • Report – 30%
  • Multiple Choice Questions – 50%
Degree list
The following degrees include this course
Bachelor of Laws (Honours), Bachelor of Commerce