Artificial Intelligence is reshaping every profession — from business and healthcare to engineering, design, and social science.
Organisations everywhere are searching for people who can connect intelligent technologies with real-world systems and processes. That’s where this programme stands apart.
The Master of AI Integrated IT Solutions is New Zealand’s first postgraduate programme that brings together Artificial Intelligence and Information Technology in one integrated qualification. Whether you come from an IT background or another discipline, this programme helps you develop the technical, analytical, and leadership skills needed to apply AI tools and thinking across industries.
Through experiential learning, industry-focused projects, and research-based practice, you’ll learn to design and manage AI-enabled solutions that address real challenges — from automation and data analysis to sustainability and ethical innovation. Graduates emerge ready to lead digital transformation, bridge technical and strategic roles, and shape the future of intelligent systems in Aotearoa New Zealand and beyond.
The programme is built around strong links with industry, research, and technology partners.
Through the Postgraduate Professional Project, students have the opportunity to apply their learning to real-world challenges within organisations across New Zealand’s growing digital and AI sectors.
Projects may be developed in collaboration with an external company, community organisation, or research initiative, depending on availability and alignment with the student’s professional goals.
This hands-on experience builds leadership, research, and problem-solving capabilities — preparing graduates to deliver AI-integrated solutions that make a real impact.
Graduates of the Master of AI Integrated IT Solutions are prepared to lead innovation and digital transformation wherever technology and intelligence meet. Building on advanced expertise in AI integration, ethical governance, and applied research, you’ll be ready to take on high-level roles across sectors adopting AI at scale.
Graduates may pursue careers such as:
Technical and Development Roles: AI Engineer, Data Scientist, Machine Learning Engineer, Software Developer, DevOps Engineer, UX Designer.
Strategic and Leadership Roles: AI Project Manager, Product Manager, Business Intelligence Analyst, Digital Transformation Consultant, Innovation Lead.
Policy, Ethics, and Governance Roles: AI Policy & Governance Specialist, Digital Sustainability Manager, Responsible AI Advisor.
Research and Emerging Technology Roles: AI Research Scientist, Cloud AI Architect, Human-Centred AI Designer.
Graduates may also progress to doctoral study or research careers in emerging AI and digital innovation fields.
The Master of AI Integrated IT Solutions offers three qualification pathways tailored to different learner backgrounds and levels of prior expertise. While the entry point and progression stages differ, all learners ultimately develop the capabilities.
120-Credit Master’s (Advanced Specialisation)
Designed for experienced IT professionals, this intensive one-year programme focuses on advanced AI integration, strategic leadership, and applied or research-based specialisation. Graduates demonstrate high-level autonomy and innovation through their final project or thesis.
Learners choose one of four pathways:
Integrative and Research pathways are intended for highly experienced professionals or those transitioning into research careers. While these options do not require formal coursework, learners will participate in targeted workshops and knowledge-sharing sessions.
180-Credit Master’s (For IT Background)
You’ll start with courses in AI integration, research methods, and your chosen area of specialisation. You’ll then complete either a final project or a thesis. This structured approach helps you build strong practical and analytical skills step by step. It’s designed for IT graduates who want to develop advanced expertise in the field.
All learners complete:
Pathway Options:
240-Credit Master's (For Non-IT Background)
This programme is designed for learners from non-IT backgrounds who wish to transition into AI-integrated IT roles. You will begin with foundational study in IT, AI, and research methods, and progressively develop advanced capabilities in AI-integrated IT solutions.
The programme includes 120 credits of coursework, followed by a substantial project or research component to demonstrate advanced (Level 9) capability.
Core courses include:
Pathway options:
Elective options
Students can choose from a range of elective courses to tailor their learning towards specific interests and career goals. These may include:
Elective offerings may vary by intake and are subject to availability, prerequisite requirements, and academic advising.
Progression to Project or Research Pathways
Entry into the final project or research stage of the programme is based on academic performance in prior coursework and programme approval. In some cases, an interview may be required.
Opportunities to undertake industry-based or externally aligned projects depend on availability and alignment with the student’s area of study.
Courses
|
Course |
Description |
|
AI-Enhanced Research Methods |
Provides students with a comprehensive foundation in research methodologies, covering both qualitative and quantitative approaches, ethical research practices, and contemporary research design principles. |
|
AI for IT Professionals |
Provides an industry-focused introduction to Artificial Intelligence (AI), equipping learners with the foundational knowledge, tools, and applications required to understand and evaluate AI-driven solutions in contemporary professional settings. |
|
Project Management |
Develops learners’ advanced knowledge and practical skills in project management, with a focus on AI-integrated and IT project environments. |
|
Advanced Business Intelligence and Reporting |
Develops advanced skills in business intelligence (BI) and reporting using industry-standard tools and methodologies. |
|
Data and Big Data Management |
Equips learners with the skills and knowledge to manage data and big data systems effectively within AI-integrated IT environments. |
|
Data Mining |
Introduces data mining concepts and techniques within the context of AI-integrated IT solutions. |
|
Cybersecurity |
Introduces the principles and practices of cybersecurity within modern IT systems. |
|
IoT, Edge and Cloud Assisted Computing |
Introduces learners to the fundamentals of Internet of Things (IoT), edge, and their integration with cloud computing, and how they integrate to create intelligent systems. |
|
Human-Centred AI and User Experience Design |
Provides a comprehensive and practice-oriented exploration of user experience (UX) design, progressing from foundational methods to advanced techniques, and culminating in the application of human-centred design in artificial intelligence (AI) contexts. |
|
Game Design and Development |
Provides learners with the opportunity to explore the principles and practices of game design and development, with a focus on integrating AI technologies. |
|
Quality Assurance and Testing |
Introduces the principles and practices of quality assurance (QA) and software testing in the context of AI-integrated IT systems. |
|
Level 8 Special Topic |
Provides learners with the opportunity to explore emerging or specialised topics in AI-integrated IT solutions not covered elsewhere in the programme. |
|
AI Ethics, Governance, and Sustainability |
Critically explores the ethical, governance, and sustainability challenges posed by AI technologies in both local and global contexts. |
|
Distributed Ledgers |
Critically explores distributed ledger technologies (DLTs) with an emphasis on blockchain integration into complex AI-driven IT systems. |
|
Advanced Software Development and Systems Management |
Provides an in-depth exploration of modern software engineering practices, with a focus on the design, development, deployment, and lifecycle management of complex, scalable, and AI-integrated systems. |
|
Cloud-Based Solutions |
Explores advanced cloud computing architectures and services for building, deploying, and managing scalable, secure, and AI-enabled Cloud solutions. |
|
AI-Driven Security Solutions |
Explores advanced security solutions powered by AI and machine learning. Learners will design and evaluate intelligent systems for threat detection, anomaly detection, and predictive security. |
|
Advanced Mobile and Wireless Technologies |
Provides an in-depth understanding of advanced mobile and wireless communication technologies, with a focus on intelligent and AI-enabled systems. |
|
Level 9 Special Topic |
Enables learners to undertake independent, advanced study on a specialised or emerging topic within AI-integrated IT solutions, not addressed elsewhere in the programme. |
|
Master's Applied Project |
Focuses on executing an advanced AI-integrated IT project, addressing a real-world industry or applied research challenge. |
|
Master's Integrative Project |
Enables learners to apply their AI and IT expertise to a large-scale, real-world project, either in an external industry setting or within an internal research-focused environment. |
|
Master's Thesis |
Enables learners to undertake independent, AI-integrated research that contributes to advancements in AI methodologies, applications, and governance. |
The Master of AI Integrated IT Solutions is designed for IT graduates, professionals, and those with relevant technical experience who want to advance their expertise in intelligent systems and digital innovation.
Students can tailor their learning journey through three pathways — Applied Project, Integrative Project, or Research Thesis — depending on their background and career goals. Each option offers a different balance of practical application, analytical depth, and research focus, preparing graduates to lead AI-driven transformation in their chosen field.
The programme also offers flexible exit points, allowing students to complete recognised postgraduate milestones if they choose to finish their studies early. Graduates of the master’s can progress to doctoral (PhD) study or move into senior roles leading innovation, digital transformation, and AI integration across industries.
Whichever path you choose, you’ll graduate ready to design, lead, and implement the next generation of intelligent technology solutions.
Minimum entry requirements are:
120-Credit Master’s (Advanced Specialisation)
Applicants must have prior postgraduate-level study in IT or a closely related field:
180-Credit Master’s (For IT Background)
Applicants are expected to have an undergraduate background in IT or a related field:
240-Credit Master’s (For Non-IT Background)
This pathway is designed for applicants from non-IT disciplines:
Applicants with non-IT backgrounds should demonstrate an interest in digital technologies, AI, or IT-enabled transformation.
Additional Admission Considerations (All Master’s Pathways)
Applicants may be required to provide additional information to support their application, including:
Academic performance in prior study is considered as part of the selection process. A B– grade average (or equivalent) is generally indicative of readiness for postgraduate study; however, applications are assessed holistically, and relevant professional experience may also be taken into account.
Applicants who do not fully meet standard academic entry criteria may still be considered where they can demonstrate substantial relevant professional experience and capability.
Progression to Project or Research Components
Entry into the project or research stage of the programme is based on successful completion of prior coursework and demonstrated readiness for advanced independent work.
For entry into the 120-credit Integrative Project or Research Thesis, a minimum B– grade average (or equivalent) in prior coursework is normally required.
Progression is also subject to:
An interview may be required to assess readiness for an independent project or research work at Level 9.
English Language Requirements
Applicants for whom English is not their first language must provide evidence of English language competence:
See here for NZQA proficiency table.
You’ll study in a vibrant, future-focused environment designed to support hands-on, experiential learning. Our modern campus in the heart of Auckland—New Zealand’s largest tech and innovation hub—offers advanced computer labs, collaborative project spaces, and industry-standard tools for AI and IT experimentation.
Throughout your studies, you’ll receive structured academic, technical, and professional support.
Beyond the classroom, you’ll join a diverse community that values collaboration, innovation, and balance—offering opportunities to participate in social events, cultural celebrations, and industry meet-ups that enrich both your personal and professional journey.
All students are required to bring their own laptop to participate fully in coursework, labs, and projects. The following minimum specifications are required:
Processor (CPU):
Memory (RAM):
Storage:
Graphics (GPU):
Operating System:
Connectivity:
Other Requirements:
Notes for Students