Unit rationale, description and aim

As technology continues to evolve, professionals across various disciplines must understand how artificial intelligence (AI) can be leveraged to analyze and influence human behavior. AI enables deeper insights by enhancing data analysis and informing strategic decision-making in marketing, healthcare, education, and public policy. This unit explores AI’s role not only in marketing but also in broader applications, equipping students with transferable knowledge applicable across industries.

Students will examine how AI-driven tools assist marketers in developing consumer engagement strategies, optimizing campaigns, and driving behavioral change in commercial and social contexts. Additionally, they will explore examples from disciplines such as healthcare (AI in patient engagement), education (personalized learning algorithms), and governance (AI-assisted policy decisions) to foster a holistic understanding of AI’s impact.

This unit also requires students to critically assess the ethical considerations of AI adoption, examining its implications for consumers, organizations, governments, and society. By engaging with real-world applications beyond marketing, students will develop interdisciplinary AI competencies that prepare them for diverse professional environments, ensuring their ability to implement AI responsibly and strategically.

2026 10

Campus offering

No unit offerings are currently available for this unit.

Prerequisites

Nil

Learning outcomes

To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.

Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.

Explore the graduate capabilities.

Explain how artificial intelligence can be used to...

Learning Outcome 01

Explain how artificial intelligence can be used to inform marketing campaigns to change consumer behaviour
Relevant Graduate Capabilities: GC1, GC10

Develop marketing collateral to communicate ideas ...

Learning Outcome 02

Develop marketing collateral to communicate ideas and change behaviours
Relevant Graduate Capabilities: GC2, GC10

Create behaviour change strategies capable of solv...

Learning Outcome 03

Create behaviour change strategies capable of solving marketing problems using digital platforms
Relevant Graduate Capabilities: GC7, GC10

Describe how artificial intelligence and human int...

Learning Outcome 04

Describe how artificial intelligence and human intelligence work together to create effective marketing campaigns to change consumer behaviour
Relevant Graduate Capabilities: GC2, GC7

Apply ethical approaches when using artificial int...

Learning Outcome 05

Apply ethical approaches when using artificial intelligence to influence marketing and consumer behaviour
Relevant Graduate Capabilities: GC6, GC11

Content

Topics will include:

  • Overview of artificial intelligence 
  • Overview of AI technologies used in marketing
  • Current and future uses of artificial intelligence  
  • Writing effective prompts for artificial intelligence large language models  
  • Analysing data to develop consumer insights with the support of artificial intelligence  
  • Artificial intelligence and marketing management  
  • Understanding consumer behaviour  
  • Changing consumer behaviour in commercial and social contexts  
  • Developing behaviour change strategies  
  • Using artificial intelligence to develop marketing collateral  
  • Combining artificial and human intelligence  
  • Ethical considerations for AI in marketing and consumer behaviour  
  • The dark side of artificial intelligence in marketing and consumer behaviour

Assessment strategy and rationale

To pass this unit, students are required to complete and submit three graded assessment tasks and achieve an aggregate mark of at least 50%. Marking will be in accordance with rubrics specifically developed to measure levels of achievement of the learning outcomes for each assessment item.

Students are encouraged to use AI tools responsibly within the guidelines of ethical academic practice. Permissible uses of AI include conducting research, generating ideas, and analyzing data to support learning. AI-generated content may be used as a starting point, provided students critically assess and refine the material to ensure originality and academic integrity. AI-driven insights may also be incorporated into marketing strategies, as long as students remain transparent about the role AI plays in decision-making.

Despite these acceptable uses, students must ensure that AI does not replace intellectual engagement in their work. Submitting AI-generated content without refinement, validation, or critical evaluation is not permitted. The use of AI tools to bypass individual effort in completing assessment tasks is also prohibited, as is any application of AI that violates academic integrity policies, such as unauthorized automated content generation without disclosure.

The assessment strategy for this unit allows students to demonstrate their knowledge and skills in how AI can be used in marketing and consumer behaviour. The first assessment allows students to demonstrate their knowledge of how AI works in marketing and consumer behaviour. The second assessment requires students to demonstrate an understanding of the ethical use of AI in marketing and consumer behaviour. The third assessment requires students to demonstrate their practical use of AI to create marketing collateral that would be implemented as part of a marketing strategy to change behaviour. In this task, students must also demonstrate how artificial intelligence, and human intelligence can be used together to enhance marketing strategies. 

Overview of assessments

Assessment Task 1: Digital portfolio: Students ...

Assessment Task 1: Digital portfolio:

Students will create a portfolio explaining how AI can be used in marketing and consumer behaviour in solving a real-world problem. The portfolio must be supported by a reference list.

Submission Type: Individual

Artifact: 1000-word reflective report


Weighting

25%

Learning Outcomes LO1, LO2, LO4
Graduate Capabilities GC1, GC2, GC7, GC9, GC10, GC11

Assessment Task 2: AI Ethics Report: This asses...

Assessment Task 2: AI Ethics Report: This assessment task consists of a 1500-word report detailing the use of AI in marketing and the ethical considerations for marketers seeking to use AI to address a problem. The report must detail how all stakeholders are impacted by the use of AI and strategies marketers can adopt to ensure ethical use of AI. The students are required to apply AI tools to their selected scenario to complete the task.

Submission Type: Individual

Artifact: 1200-word report and the program to showcase applying AI to the selected scenario

Weighting

35% 

Learning Outcomes LO1, LO5
Graduate Capabilities GC1, GC9, GC11

Assessment Task 3: Marketing Strategy: Students...

Assessment Task 3: Marketing Strategy:

Students will be provided with a real-world client who has a marketing problem that requires a behaviour change strategy to be developed. Students will develop a behaviour change strategy to solve the problem and use AI to develop artifacts that will be included in the campaign to implement the strategy. Students will present their work in a 1800-word report and submit the outcomes of the project including the recorded 5-6 minute presentation and the programs.

Submission Type: Individual

Word Limit: 1800-word report, 5-6 minute presentation, programs

Weighting

40%

Learning Outcomes LO2, LO3, LO4, LO5
Graduate Capabilities GC1, GC2, GC7, GC10, GC11

Learning and teaching strategy and rationale

Students should anticipate undertaking 150 hours of study for this unit over a twelve-week semester or equivalent study period, including class attendance, readings, online forum participation and assessment preparation.

This unit may be offered in “Attendance” and/or “Online” mode to cater for the learning needs and preferences of a range of participants.

Attendance Mode

Students will require face-to-face attendance in blocks of time determined by the school. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for students to prepare and revise.

Online Mode

This unit utilises an active learning approach whereby students will engage in e-module activities, readings and reflections, and opportunities to collaborate with peers in an online environment. This can involve, but is not limited to, online workshops, online discussion forums, chat rooms, guided reading, and webinars. Pre-recorded lectures will be incorporated within the online learning environment and e-modules. In addition, electronic readings will be provided to guide students’ reading and extend other aspects of online learning.

Representative texts and references

Representative texts and references

Barari, M., Ferm, L-E. C., Quach, S., Thaichon, P., and Ngo, L., 2024. The dark side of artificial intelligence in marketing: Meta-analytics review. Marketing Intelligence & Planning, 42(7), pp.1234-1256.  

Davenport, T., Guha, A., Grewal, D., and Bressgott, T., 2020. How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, pp.24-42.  

Jain, V., Wadhwani, K., and Eastman J. K., 2024. Artificial intelligence consumer behavior: A hybrid review and research agenda. Journal of Consumer Behaviour, 23(2), pp.676-697.  

Letheren, K., Russell-Bennett, R., and Whittaker, L., 2020. Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3-4), pp.216-232. 

Longoni, C., and Cian, L., 2022. Artificial intelligence in utilitarian vs. hedonic contexts: The “word-of-machine” effect. Journal of Marketing, 86(1), pp.91-108.  

Pagani, M. and Yoram, W., 2024. Unlocking Marketing Creativity Using Artificial Intelligence. Journal of Interactive Marketing (in press).  

Park, H. E., 2024. The double-edged sword of generative artificial intelligence in digitalization: An affordances and constraints perspective. Psychology & Marketing, 41(11), pp.2924-2941.  

Vlačić, B., Corbo, L., e Silva, S. C., and Dabić, M., 2021. The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, pp.187-203.  

Wu, C-W., and Monfort, A., 2023. Rolle of artificial intelligence in marketing strategies and performance. Psychology & Marketing, 40(3), pp.484-496.  

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