AI for Business Professionals

General Information

This subject equips professionals and emerging business leaders with the strategic, ethical, and practical knowledge to leverage artificial intelligence (AI) both personally and within modern organisations. Students will explore AI's capabilities, limitations, and implications, and learn how to apply AI tools to improve decision-making, innovation, and operations. Through a combination of theoretical content, real-world case studies, and hands-on tool exploration, students will be prepared to lead AI-driven transformation within their industries.

  • Academic unit: Bond Business School
    Subject code: ENAI71-111
    Subject title: AI for Business Professionals
    Subject level: Postgraduate
    Semester/Year: September 2026
    Credit points: 10.000
  • Timetable: https://bond.edu.au/timetable
    Delivery mode: Standard
    Workload items:
    • Forum: x12 (Total hours: 24) - Forum
    • Computer Lab: x12 (Total hours: 24) - Computer Lab
    • Personal Study Hours: x12 (Total hours: 72) - Recommended study time & reviewing materials.
    Attendance and learning activities: N/A
  • Prescribed resources:

    No Prescribed resources.

    After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.
    iLearn@Bond & Email:

    iLearn@Bond is the Learning Management System at Bond University and is used to provide access to subject materials, class recordings and detailed subject information regarding the subject curriculum, assessment, and timing. Both iLearn and the Student Email facility are used to provide important subject notifications.

    Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student.

    To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au
    Class recordings:

    The primary workload items for this subject will be recorded for the purpose of revision.

    These recordings are not a substitute for attending classes. Students are encouraged to attend all sessions as there may be instances where a session is not recorded due to the presence of a guest speaker, the inclusion of sensitive or protected content, or technical issues. Students are advised not to rely solely on these recordings for revision.

    See the Recording policy for further details.
Academic unit: Bond Business School
Subject code: ENAI71-111
Subject title: AI for Business Professionals
Subject level: Postgraduate
Semester/Year: September 2026
Credit points: 10.000

Enrolment requirements

Requisites:

Nil
Restrictions:

Nil

Assurance of learning

Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.

At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.

Program Learning Outcomes (PLOs)

Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.

Find your program

Subject Learning Outcomes (SLOs)

On successful completion of this subject the learner will be able to:

  1. Critically assess the strategic implications, capabilities, and constraints of AI for business transformation, communicating insights to both technical and non-technical stakeholders
  2. Evaluate AI opportunities within organisations using frameworks for readiness, ethical consideration and implementation feasibility
  3. Integrate AI tools and platforms into complex business scenarios, addressing concepts such as change management, risk identification, and tool selection
  4. Design a comprehensive AI innovation or adoption strategy tailored to a specific sector, incorporating stakeholder engagement, data governance, and scalability considerations

Generative Artificial Intelligence in Assessment

The University acknowledges that Generative Artificial Intelligence (Gen-AI) tools are an important facet of contemporary life. Their use in assessment is considered in line with students’ development of the skills and knowledge which demonstrate learning outcomes and underpin study and career success. Instructions on the use of Gen-AI are given for each assessment task; it is your responsibility to adhere to these instructions.

  • Type Task % Timing* Outcomes assessed AI category
    Written Report Strategic AI Plan for a chosen organisation. Includes roadmap, risks, stakeholder and impact analysis. 40.00% Week 8 1, 2, 3, 4
    Presentation Analysis and prototype implementation of an AI opportunity in a chosen industry with justification and tools. 10.00% Week 12 1, 2, 3, 4
    Capstone Project Analysis and prototype implementation of an AI opportunity in a chosen industry with justification and tools. 40.00% Week 13 1, 2, 3, 4
    Computer-aided Test (Open) 2 x practical quizzes designed to consolidate and deepen understanding of subject curriculum. 10.00% Ongoing 1, 2
    • * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
    • C = Students must reach a level of competency to successfully complete this assessment.

    AI Categories

    • Ai Prohibited: Learning to develop AI-free knowledge and skills.

    • Ai Supported: Learning with the help of AI as directed.

    • Ai Focussed: Learning AI expertise and mastery as directed.

    Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.

  • Assessment criteria

    High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking.
    Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas.
    Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above.
    Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment.
    Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines.

    Quality assurance

    For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.

Type Task % Timing* Outcomes assessed AI category
Written Report Strategic AI Plan for a chosen organisation. Includes roadmap, risks, stakeholder and impact analysis. 40.00% Week 8 1, 2, 3, 4
Presentation Analysis and prototype implementation of an AI opportunity in a chosen industry with justification and tools. 10.00% Week 12 1, 2, 3, 4
Capstone Project Analysis and prototype implementation of an AI opportunity in a chosen industry with justification and tools. 40.00% Week 13 1, 2, 3, 4
Computer-aided Test (Open) 2 x practical quizzes designed to consolidate and deepen understanding of subject curriculum. 10.00% Ongoing 1, 2
  • * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
  • C = Students must reach a level of competency to successfully complete this assessment.

AI Categories

  • Ai Prohibited: Learning to develop AI-free knowledge and skills.

  • Ai Supported: Learning with the help of AI as directed.

  • Ai Focussed: Learning AI expertise and mastery as directed.

Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.

Study Information

Submission procedures

Students must check the iLearn@Bond subject site for detailed assessment information and submission procedures.

Policy on late submission and extensions

A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the subject coordinator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.

Academic Integrity

Bond University‘s Student Code of Conduct Policy , Student Charter, Academic Integrity Policy and our Graduate Attributes guide expectations regarding student behaviour, their rights and responsibilities. Information on these topics can be found on our Academic Integrity webpage recognising that academic integrity involves demonstrating the principles of integrity (honesty, fairness, trust, professionalism, courage, responsibility, and respect) in words and actions across all aspects of academic endeavour.

Staff are required to report suspected misconduct. This includes all types of plagiarism, cheating, collusion, fabrication or falsification of data/content or other misconduct relating to assessment such as the falsification of medical certificates for assessment extensions. The longer term personal, social and financial consequences of misconduct can be severe, so please ask for help if you are unsure.

If your work is subject to an inquiry, you will be given an opportunity to respond and appropriate support will be provided. Academic work under inquiry will not be marked until the process has concluded. Penalties for misconduct include a warning, reduced grade, a requirement to repeat the assessment, suspension or expulsion from the University.

Feedback on assessment

Feedback on assessment will be provided to students according to the requirements of the Assessment Procedure Schedule A - Assessment Communication Procedure.

Whilst in most cases feedback should be provided within two weeks of the assessment submission due date, the Procedure should be checked if the assessment is linked to others or if the subject is a non-standard (e.g., intensive) subject.

Accessibility and Inclusion Support

Support is available to students where a physical, mental or neurological condition exists that would impact the student’s capacity to complete studies, exams or assessment tasks. For effective support, special requirement needs should be arranged with the University in advance of or at the start of each semester, or, for acute conditions, as soon as practicable after the condition arises. Reasonable adjustments are not guaranteed where applications are submitted late in the semester (for example, when lodged just prior to critical assessment and examination dates).

As outlined in the Accessibility and Inclusion Policy, to qualify for support, students must meet certain criteria. Students are also required to meet with the Accessibility and Inclusion Advisor who will ensure that reasonable adjustments are afforded to qualifying students.

For more information and to apply online, visit BondAbility.

Subject curriculum

Approved on: Jan 27, 2026. Edition: 2.3
Last updated: Jan 27, 2026