Information Technology

Master of AI Integrated IT Solutions

Master of AI Integrated IT Solutions

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.

Programme summary

Level:
Level 9
Credits:
180
Fees:
International fee: $40,500, Fee after scholarship: $34,700
Duration:
1.5 years full-time
Who Can Join:
International students
Campus:
Auckland Central (Queen St)
Intakes:
February, April, July, October

Highlights

Work on real-world AI projects guided by experienced academics and industry mentors.

Be part of New Zealand’s first postgraduate programme focused on AI-Integrated IT Solutions.

Carry out complex applied or research projects that bring fresh insights into AI-integrated IT systems.

Critically review AI solutions based on data, stakeholder input, and reflective practice.

YOUR EXCITING NEW CAREER AWAITS

 

This programme leads to successful careers as AI Engineers, Data Scientists, Business Intelligence Analysts, Cybersecurity Specialists (AI-powered), IT Consultants (AI & Digital Solutions), Project Managers (AI-driven IT Solutions), and more.

 

PROGRAMME INFORMATION

PROGRAMME INFORMATION

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.

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:

  • AI for IT Professionals (15 credits)
  • AI-Enhanced Research Methods (15 credits)

Pathway Options:

  • Applied Project Pathway: Four electives (60 credits) plus Master’s Applied Project (90 credits).
  • Integrative Project or Research Thesis: Two electives (30 credits) plus Integrative Project or Thesis (120 credits).

 

Elective options

  • Project Management
  • Advanced Business Intelligence and Reporting
  • Data and Big Data Management
  • Data Mining
  • Cybersecurity
  • IoT, Edge and Cloud Assisted Computing
  • Human-Centred AI and User Experience Design
  • Game Design and Development
  • Quality Assurance and Testing
  • Level 8 Special Topic
  • AI Ethics, Governance, and Sustainability
  • Distributed Ledgers
  • Advanced Software Development and Systems Management
  • Cloud-Based Solutions
  • AI-Driven Security Solutions
  • Advanced Mobile and Wireless Technologies
  • Level 9 Special Topic
  • All electives are subject to availability, prerequisite requirements, and academic guidance. Elective selection is guided through academic advising to ensure alignment with programme rules, learner background, and desired project or research pathway. Some electives may require specific prior knowledge or experience.

Entry into the Master’s Integrative Project or Research Thesis requires a minimum GPA of B- in prior coursework, academic approval from the Head of Department or Programme Manager and may include an interview. Admission to an external project or research component is subject to availability and project alignment.

 

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:

  • A Bachelor’s degree in IT or a related discipline, or
  • At least five years of relevant professional experience in IT, business, or a related domain (for applicants without a degree).

Additional Requirements:

  • Applicants without a degree must submit a Statement of Purpose outlining their background, motivations, and professional goals.
  • An interview may be required to assess academic and professional readiness.
  • Applicants with prior tertiary qualifications are encouraged to demonstrate academic readiness. A B– grade average (or equivalent GPA) is generally considered a useful indicator, but applicants may also be considered based on relevant professional experience, interview performance, and Statement of Purpose.
  • Exceptional applicants who do not meet the standard academic criteria but demonstrate relevant and substantial professional experience may also be considered.

 

English Language Requirements:

Applicants for whom English is not their first language must provide evidence of English language competence:

  • IELTS Academic: Overall band score of 6.5, with no individual band less than 6.0, or
  • An equivalent score in an NZQA-recognised English Proficiency Test.

Click here for equivalent academic entry requirements by country. 

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.

  • Peer Tutors and Learning Support Advisors can help with research, data analysis, and academic writing.
  • Our Employability and Industry Engagement Team connects you with networking events, workshops, and real-world projects that integrate AI and IT solutions into professional contexts.
  • For personal or wellbeing matters, the Student Success Team provides confidential support and pastoral care.

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):

  • Intel Core i7 (12th gen or later) OR AMD Ryzen 7 (5000 series or later)
  • Apple Silicon (M1/M2/M3) devices also supported

Memory (RAM):

  • Minimum: 16 GB
  • Recommended: 32 GB for data-intensive and AI-related tasks

Storage:

  • Minimum: 512 GB SSD
  • Recommended: 1 TB SSD
    (Students will also receive cloud storage via institutional accounts.)

Graphics (GPU):

  • Dedicated GPU strongly recommended for AI, ML, gaming, or simulation courses:
    • NVIDIA RTX 3060 or above, OR Apple M1/M2/M3 Pro/Max equivalent
  • Integrated graphics acceptable for coursework-only students, but may limit performance in electives such as Game Development or Deep Learning

Operating System:

  • Windows 11 (preferred), OR
  • macOS Ventura or later, OR
  • Linux (Ubuntu 22.04 or equivalent)

Connectivity:

  • Wi-Fi 6 (802.11ax) or later
  • Minimum 2 × USB-A/USB-C ports, HDMI (or adapter)
  • Headset with microphone for online sessions

Other Requirements:

  • Webcam (built-in or external) for online classes
  • Ability to run virtualisation / containers (e.g., Docker, VMware, VirtualBox)
  • Access to cloud services (AWS, Azure, GCP – provided via student accounts)

Notes for Students

  • High-end GPUs are particularly recommended if you plan to take courses in Game Development, Data Mining, or Advanced Machine Learning.
  • The institution provides access to specialist labs, cloud environments, and licensed software for workloads beyond BYOD capacity.
  • Chromebooks, iPads, and tablets are not suitable as a primary device.