The MSc in Enterprise AI programme aims to address the critical industry needs and talent gaps by meeting the growing learning needs around business-centric AI skills, AI literacy for non-technical leaders, and responsible AI governance. It also uniquely addresses applied innovation through AI product management and no-/low-code platforms. Strategically
positioned relative to existing offerings in AI and digital transformation, the programme is unique in nurturing a new generation of “AI-savvy” professionals and business leaders who can drive enterprise AI integration for strategic value.
Why Choose Our Programme?
- Addresses key industry gaps by training professionals who can apply AI for maximum business impact.
- Focuses on practical, business-centric skills that go beyond traditional computer science degrees, such as analysing workflows and driving adoption of AI solutions.
- Boosts AI literacy for non-technical professionals by demystifying core concepts and empowering people from various backgrounds (like marketing and finance) to work effectively with AI.
- Emphasises responsible AI and governance, a crucial and in-demand skill set that prepares students to manage ethical issues, risks, and regulatory compliance.
- Develops skills in AI product management and innovation, preparing students to lead AI projects from concept to deployment and solve real-world business problems.
The admissions requirements for the MSc in Enterprise AI are as follows:
• Eligibility: A Bachelor’s degree with honours or its equivalent in any discipline from an institution of recognised standing.
• English Requirement: TOEFL (internet-based test)> 85 or IELTS (academic)> 6.0 is required if your first language is not English. Applicants may be waived from this requirement if the applicant has completed the first degree taught entirely in English, situated in an English-speaking country. The TOEFL/IELTS result is only valid for 2 years after the test and should be valid at the beginning of the application period.
• Work Experience: Candidates opting for the programme on part-time basis should preferably have 1 or more years of relevant work experience after their first degree. The programme also welcomes mid-career professionals with longer work histories.
| Programme Title | Master of Science in Enterprise Artificial Intelligence Programme |
| Period of Candidature | • Full Time: minimum 1 Year / 3 Trimesters, maximum 2 Years / 6 Trimesters • Part Time: minimum 1.5 Years / 5 Trimesters, maximum 3 Years / 9 Trimesters |
Course Requirement | 12 Courses and 1 Capstone Course |
| Total AU Requirement | 30 AUs |
| Funding | Self-funded Programme (Non-subsidised) |
Academic Unit Structure and Requirement
The MSc in Enterprise AI is designed as a flexible, interdisciplinary, and industry-aligned
programme that equips students with both the strategic insight and practical tools needed to
lead AI transformation initiatives across diverse sectors. The programme adopts a modular
architecture comprising 30 Academic Units (AUs), delivered through five curriculum pillars.
The total number of AUs required for graduation is 30.
Core Curriculum Structure (30 AUs)
The MSc in Enterprise AI is structured around five foundational pillars that reflect the full AI
transformation lifecycle—from strategic visioning and data intelligence to implementation,
ethical governance, and applied capstone execution:
1) Strategy, Leadership & Transformation (7.5 AUs)
This pillar cultivates the strategic thinking, leadership, and change management
capabilities required to drive AI adoption in enterprise contexts. Courses explore how AI
technologies reshape business models, organisational processes, and innovation
strategies. Students gain skills in AI project planning, business alignment, and
transformation leadership.
Courses include:
• AI-Driven Business Process Transformation and Automation (1.5 AUs)
• Strategic Management and Leadership of AI and Digital Innovation (3 AUs)
• AI Projects and Performance Management (1.5 AUs)
• Emerging AI Technologies (1.5 AUs)
2) Data, Analytics & Intelligence (9 AUs)
This pillar develops analytical proficiency and data-driven decision-making competencies.
Students will engage with structured and unstructured data sources, including predictive
analytics, machine learning, and natural language/vision applications. Emphasis is placed
on real-world business use cases and quantitative reasoning in support of strategic insight.
Courses include:
• Contemporary Data Architecture, Management and Governance (3 AUs)
• Applied Predictive Analytics for Business Strategy (3 AUs)
• Next-Gen Analytics: From Language to Vision (3 AUs)
3) Platforms, Tools & Implementation (7.5 AUs)
Focused on application and operationalisation, this pillar trains students to work with
contemporary AI tools, no-code/low-code platforms, and enterprise-scale integration
technologies. It covers hands-on proficiency in deploying AI solutions, designing intelligent
systems, and evaluating platform interoperability across the business technology stack.
Courses include:
• Generative AI and Agentic AI (3 AUs)
• AI Ecosystems: Platforms, Integration, and Automation (1.5 AUs)
• AI Product Development and Agile Thinking (3 AUs)
4) Ethics, Governance & Responsible AI (3 AUs)
With increasing regulatory scrutiny and societal impact, this pillar ensures students
develop a principled understanding of responsible AI use. Students explore topics
including algorithmic bias, data ethics, cybersecurity, compliance, and governance
frameworks aligned with global standards (e.g., OECD, EU AI Act, Singapore Model AI
Governance Framework).
Courses include:
- Responsible AI and Governance (1.5 AUs)
- AI-Driven Cybersecurity: Safeguarding the Intelligent Enterprise (1.5 AUs)
5) AI Transformation Capstone (3 AUs)
The capstone is the integrative apex of the programme, where students apply their
accumulated knowledge to address a complex, real-world AI transformation challenge in
a selected industry or enterprise domain. Working independently or in teams, students
develop an AI strategy, design implementation roadmaps, and produce executive-level
deliverables, such as business cases or technical pilots.
Graduates of the MSc in Enterprise AI will be equipped to pursue a variety of high-impact
career pathways at the intersection of technology and business. The programme’s blend of
skills prepares students for roles such as:
• AI Project Lead / AI Project Manager
• Digital Transformation Strategist
• AI Product Manager
• Innovation or AI Consultant
• AI Governance or Policy Officer
Programme Fees
- The fee of the programme is $57,770 (inclusive of GST) for AY2026.
- There is an application fee of $50.
- There is a deposit fee of $5,000 which can be used to offset the first tuition fee payment.
Financial Aid
- All NTU alumni and associate alumni, regardless of nationality, will receive a 10% tuition fee discount.
- Singaporeans and Permanent Residents will receive a S$5,000 subsidy. Those eligible for financial aid may receive up to S$15,000.