COMMGMT 7031 - Artificial Intelligence for Business

North Terrace Campus - Trimester 3 - 2024

Artificial Intelligence (AI) is changing the world, it is impacting every industry and is forecast to be a multi-trillion dollar industry by the end of the decade. Many of the world's largest companies, including Google, Facebook and Amazon, heavily utilise AI throughout their businesses to outpace their competitors. But what is Artificial Intelligence? And how can it be leveraged to improve a business? This course aims to answer these questions through exploring the types of AI that exist, how AI is currently being used to create value within businesses, and how this transformative technology can be harnessed to create new products and services. Throughout the course we will also explore the societal, economic and ethical questions that arise when applying AI in business.

  • General Course Information
    Course Details
    Course Code COMMGMT 7031
    Course Artificial Intelligence for Business
    Coordinating Unit Management
    Term Trimester 3
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact 3 hours per session (Up to 18 hours per week for intensive mode)
    Available for Study Abroad and Exchange
    Course Staff

    No information currently available.

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    1. Distinguish the different types of AI and how they are applied in a business context
    2. Identify the different types of datasets and data sources and how they can be leveraged to gain strategic advantage with AI
    3. Assess an organisation's existing data sources and business processes to identify opportunities to gain strategic advantage using AI
    4. Analyse and advise on the viability and practicality of applying AI to a business opportunity
    5. Communicate the social, economic and ethical implications of applying AI in real world applications
    University Graduate Attributes

    No information currently available.

  • Learning & Teaching Activities
    Learning & Teaching Modes

    No information currently available.


    No information currently available.

    Learning Activities Summary

    No information currently available.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Weighting CLOs
    Assignment 1 – AI Comparative Test Individual 20% 1
    Assignment 1 – AI Impact Report Individual 40% 1, 2, 3
    Assignment 3 - AI Innovation Pitch Group 20% 2, 3, 4
    Participation & Reflection Individual 10% 1, 2, 3, 4
    Assessment Detail
    Assignment 1 – AI Comparative Analysis Test - Individual (20%)

    The student will compare and contrast different AI tools and analyse practicality of each in a business context, either within their own organisation or in general. 500 word report.

    Assignment 2 – AI Impact Report - Individual (40%)

    Provide an in-depth assessment of existing business resources and processes to identify opportunities to integrate AI. This assessment will encourage students to take a closer look at the use of AI in a business context and to gain a greater understanding of associated challenges, pros and cons, grounded in a thorough understanding of applying AI technologies in a viable manner.

    Assignment 3 - AI Innovation Pitch - Group (30%)

    This is designed to demonstrate that students could take a new AI use case/idea to the boardroom of a current or future employer.

    As future leaders the students should be able to articulate the impacts and benefits of using AI to solve problems. This assignment will culminate how AI can be applied in a viable and responsible manner.

    This assignment is designed to test their understanding of the practical, cultural, and ethical challenges of deploying real world AI, along with their team work in researching and articulating their points.

    Participation and Reflection Individual (10%)
    Short multiple choice quizzes designed reinforce the key concepts (AI and data types) learnt in sessions 1 and 2.

    This will allow students the opportunity to test their understanding and seek further guidance if needed before we progress with more complex topics.

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

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