Outline

Overview

Digital transformation is more than the adoption of new technologies—it requires reimagining business models, processes, and customer engagement to drive innovation, efficiency, and sustained competitive advantage. It is a critical mindset for modern managers. While managers must critically assess the promises and pitfalls of emerging technologies to avoid hype-driven decisions, digital innovation also offers powerful tools and techniques for navigating dynamic environments. This foundational unit examines how digital technologies are reshaping business, government, and not-for-profit sectors. Students will gain a strategic and operational understanding of transformation, exploring the role of leadership in change management, the alignment of digital initiatives with corporate strategy and governance, and the cultural and ethical challenges of organisational transformation. Exemplary technologies covered include Artificial Intelligence (AI), Augmented Reality, the Internet of Things (IoT), and Blockchain. By the end of the course, students will be equipped to lead, assess, and implement digital transformation initiatives that foster innovation and sustainable growth.

Unit details and rules

Academic unit	Business Information Systems
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Students should undertake this unit in their first semester of study.
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Daniel Gozman, daniel.gozman@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Portfolio or journal	Emerging Technology Blogs Individual blogs which provide an opportunity to feedforward and inform the interactive oral assessment	5%	Multiple weeks	4 x 500 words	AI allowed
Outcomes assessed:
Presentation	Pitch Video Group pitch which will provide feedforward on progress with the report	10%	Week 04 Due date: 18 Mar 2026 at 23:59 Closing date: 28 Mar 2026	5 minutes	AI allowed
Outcomes assessed:
Research analysis	Report Assesses analytical skills and understanding of unit content	20%	Week 10 Due date: 05 May 2026 at 23:59 Closing date: 15 May 2026	3500 words	AI allowed
Outcomes assessed:
Presentation	Presentation + Q and A Demonstrates collaboration and communication skills in-class	10%	Week 10	10 minutes presentation + 5 mins Q and A	AI allowed
Outcomes assessed:
Interactive oral	Interactive Oral Secured assessment where students will draw on their experiences across the unit in a scenario based professional conversation	55%	Week 11	15 minutes	AI prohibited
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Pitch Video: group pitch which will provide feedforward on progress with the report

Report: assesses analytical skills and understanding of unit content

Presentation: demonstrates collaboration and communication skills

Emgering Technology Blogs: individual blogs which provide an opportunity to feedforward and inform the interactive oral assessment

Interactive Oral: details to be provided

Assessment criteria

Assessments - assessment grading:

The University awards common result grades, set out in the Coursework Policy (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late penalties will be applied per University policy.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Managerial Practices	Workshop (2 hr)
Week 01	Week 1: Managerial Practices - self-directed learning	Self-directed learning (2 hr)
Week 02	Blockchain and hype cycles	Workshop (2 hr)
Week 02	Week 2: Blockchain and hype cycles - self-directed learning	Self-directed learning (2 hr)
Week 03	Building a digital transformation business model	Workshop (2 hr)
Week 03	Week 3: Building a digital transformation business model - self-directed learning	Self-directed learning (2 hr)
Week 04	Artificial Intelligence	Workshop (2 hr)
Week 04	Week 4: Artificial Intelligence - self-directed learning	Self-directed learning (2 hr)
Week 05	Building a technology strategy	Workshop (2 hr)
Week 05	Week 5: Building a technology strategy - self-directed learning	Self-directed learning (2 hr)
Week 06	Internet of things	Workshop (2 hr)
Week 06	Week 6: Internet of things - self-directed learning	Self-directed learning (2 hr)
Week 07	Project management	Workshop (2 hr)
Week 07	Week 7: Project management - self-directed learning	Self-directed learning (2 hr)
Week 08	Augmented reality and virtual reality	Workshop (2 hr)
Week 08	Week 8: Augmented reality and virtual reality - self-directed learning	Self-directed learning (2 hr)
Week 09	Strategic alignment, IT governance and cyber security	Workshop (2 hr)
Week 09	Week 9: Strategic alignment, IT governance and cyber security- self-directed learning	Self-directed learning (2 hr)
Week 10	Presentations and close	Workshop (2 hr)
Week 10	Week 10: Presentations and close - self-directed learning	Self-directed learning (2 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. critically discuss and evaluate the key issues, debates, principles, ethical implications, concepts, and theories of digital transformation
LO2. apply appropriate methods and frameworks for digital transformation interventions in diverse (including culturally diverse) contexts and provide evidence-based arguments to support related analysis
LO3. communicate digital transformation outcomes and related analysis for diverse audiences convincingly and professionally
LO4. collaborate effectively to address ambiguous problems in digital transformation, integrating diverse cultural perspectives.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This unit is being offered for the first time in 2026.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

DMBA6001: Leading Strategic Digital Transformation

Semester 1, 2026 [Online] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links