Business & Management Business Management and Administration

This programme aims to develop business-led competencies for the strategic deployment of artificial intelligence (AI) and digital technologies in contemporary organisations. Through an integrated set of modules, students will strengthen their ability to align AI-enabled solutions with business strategy, lead organisational transformation, and support managerial decision-making using data analytics and predictive approaches.

On completion of the programme, students should be able to:

1.       critically analyse and apply business management strategies to address challenges and opportunities in digital enterprises;

2.       explain and apply core principles of artificial intelligence and data analytics to analyse complex business problems;

3.       utilise data-driven decision-making frameworks and AI tools to improve business performance and competitiveness;

4.       demonstrate effective digital leadership skills and manage organisational change in response to technological advancements;

5.       evaluate and implement predictive modelling with data visualisation and storytelling skills for business decision-making;

6.       critically evaluate and apply interdisciplinary knowledge, concepts and professional skills across diverse intercultural, organisational and technological contexts, and to exercise informed judgment in addressing complex real-world issues; and 

7.       critically evaluate, integrate and apply subject knowledge and appropriate methodologies in the planning and execution of a significant project, and to communicate evidence-based findings, conclusions and recommendations in an academic/professional manner.

Lecture Schedule

The programme usually offers five sessions per week (3-4 sessions on weekday and 1-2 sessions on Saturday tentatively).

Programme Structure

The programme consists of ten modules, to be taught over 2 semesters (12 months), 5 modules taught in each semester.

Module		Lecture Hours	QF Credits	HKQF Level
1	AI in Strategic Business Management	33	9	6
2	Technology Management and Digital Transformation	33	9
3	Data Analytics and Decision Making in Management and Innovation	33	9
4	Digital Leadership, Change and Organisation Design	33	9
5	Predictive Modelling and Forecasting for Business Decision Making	36	12
6	Data Visualisation and Storytelling for Business Managers	36	12
Total		204	60

 

Assessment

Assessment method: individual written reports, discussion, group project, mid-term test and examination 

Award

Upon successful completion of the programme (pass all 6 modules), with attendance no less than 80%, students will be awarded within the HKU system through HKU SPACE a "Postgraduate Diploma in Digital Business Management with Artificial Intelligence".

Application Code	-MS197A	-

MODULE DESCRIPTION

AI in Strategic Business Management

This module aims to equip students with the strategic acumen to leverage Artificial Intelligence (AI) as a core driver of business competitiveness. It focuses on moving beyond operational AI to understanding how AI shapes business models, competitive strategy, and long-term organisational resilience.

Technology Management and Digital Transformation

This module aims to develop an understanding of managing technological assets and leading enterprise-wide, AI‑enabled digital transformation. It bridges the gap between technical infrastructure and organisational strategy, focusing on how to manage the lifecycle of technology, navigate legacy system constraints, and orchestrate a cultural shift towards digital-first operations.

Data Analytics and Decision Making in Management and Innovation

This module aims to develop managerial competence in using data analytics to drive innovation and strategic decision-making. It moves beyond descriptive analytics to emphasise diagnostic and prescriptive approaches. Students will learn to frame business problems as analytical questions, interpret complex analytical outputs, and foster a data-driven culture that supports experimentation and innovation.

Digital Leadership, Change and Organisation Design

This module aims to explore the transformation of leadership paradigms and organisational structures in the digital era. It addresses the tension between hierarchical legacy structures and the need for agility, networked teams, and decentralised decision-making. Students will develop the leadership capabilities required to champion digital change, manage diverse talent, and design organisations that are resilient, adaptive, and human-centric.

Predictive Modelling and Forecasting for Business Decision Making

This module aims to equip non-technical managers with the foundational knowledge to understand, commission, and critically evaluate predictive models and forecasts. It demystifies machine learning algorithms from a managerial perspective, focusing on how to select appropriate models for business scenarios (e.g., demand forecasting, customer churn) and how to interpret model outputs to make proactive strategic decisions.

Data Visualisation and Storytelling for Business Managers

This module aims to introduce students with the essential skills and knowledge to effectively visualise data and craft compelling narratives for business decision-making. Students will learn how to interpret complex datasets, use visualisation tools, and communicate insights to diverse stakeholders, enabling them to support strategic and operational objectives within modern organisational settings.

Common Generic Modules (CGM)

Students have the unique opportunity to study the following Common Generic Modules (CGM) alongside peers from other postgraduate programmes:

1. Executive Leadership Development
2. Intercultural Communication – Trilingualism and Hong Kong Culture
3. Intelligent Technologies for ESG Integration and Sustainable Development 

Taken together, these modules provide a coherent set of advanced generic learning experiences that broaden students’ intellectual and professional horizons, reinforce transferable capabilities, and enhance the relevance of the individual programmes to contemporary postgraduate education.

Capstone Project

The Capstone Project is designed to provide students with an extended opportunity to synthesise and apply the knowledge, concepts and skills developed through both their discipline-specific studies and the CGMs. In pedagogical terms, the Capstone Project will incorporate a range of non-lecture learning activities, such as e-learning tasks, seminars, site visits, field trips, practice-based exploration and other supervised experiential or enquiry-based activities. Emphasis is placed on integration, independent inquiry, application, critical reflection and the production of work that demonstrates advanced learning achievement.

Programme Specific Activities

During the study period, students will also have the opportunity to participate in programme-specific activities such as field trips, and career talks, all tailored to their individual needs.

Course Fee

• Application Fee
  HK$600 (Non-refundable)
  
  Course Fee
  HK$140,000

Applicants shall hold a bachelor’s degree in business or related areas awarded by a recognised institution.

If the degree or equivalent qualification is from an institution where the language of teaching and assessment is not English, applicants shall provide evidence of English proficiency, such as:

(i) an overall band of 6.0 or above with no subtests lower than 5.5 in the IELTS; or

(ii) a score of 80 or above (for tests taken prior to 21 January 2026) or a score of 4.5 or above (for tests taken from 21 January 2026 onwards) in the internet-based TOEFL (iBT); or

(iii) HKALE Use of English at Grade E or above; or

(iv) HKDSE Examination English Language at Level 3 or above; or

(v) Grade C or above in Cambridge English: C1 Advanced; or

(vi) 180 or above in Cambridge Linguaskill General Certificate; or

(vii) equivalent qualifications.

Applicants who hold a relevant and recognised professional qualification in a relevant discipline and three years of full-time work experience at senior managerial level in related industries will be considered case by case.

Applicants with other qualifications will be considered on individual merit.

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