The People Exploring How Generative AI Is Changing Election Information Discovery
When New Zealanders ask ChatGPT, Gemini or Perplexity about election policies, what information do these AI systems surface? Which sources do they cite? And how does that information change as the election approaches?
These are the questions driving the CiteCompass NZ Election 2026 AI Visibility Monitor — an independent, 12-week longitudinal research initiative examining how generative AI represents political-party information during New Zealand’s 2026 General Election.
Behind the technology and weekly data is a multidisciplinary research team bringing together expertise in artificial intelligence, data analytics, governance, research methodology and digital transformation.
Today, we’re introducing three postgraduate researchers from Massey University who are contributing to this initiative.
Why This Research Matters
Generative AI is becoming an increasingly important intermediary between people and the information they discover.
Rather than simply presenting a list of websites, AI platforms synthesise information into answers, often drawing on multiple sources.
This creates an important new area of research: understanding how AI systems discover, select, represent and cite publicly available information.
The CiteCompass study monitors six parliamentary political parties across five policy areas:
- Cost of Living
- Economy, Jobs & Growth
- Health
- Housing
- Crime & Public Safety
Together, these create 30 party-policy profiles, monitored weekly using a consistent research framework.
The study measures how visible political-policy information is within generative AI-generated responses. It does not assess the quality of policies, predict election results or measure voter support.
Our research team is helping explore these emerging information-discovery patterns through systematic analysis, transparent reporting and a commitment to responsible research.
Meet Our Research Collaborators
Alice Gu — PhD Researcher, Massey University
Research interests: Human–Machine Collaboration, Advanced Technologies and Research Analytics
Alice Gu is a PhD student at Massey University and a Graduate Research Collaborator with CiteCompass.
Her doctoral research explores how advanced technologies and human–machine collaboration under Industry 5.0 can enhance supply chain capabilities.
Alice’s research has been accepted for presentation at the EURAM and BAM 2026 conferences.
With extensive professional experience in strategic management and technology-enabled business practices, Alice brings analytical thinking, research synthesis and a strong commitment to methodological rigour.
Through the CiteCompass NZ Election 2026 AI Visibility Study, Alice aims to contribute to the systematic analysis of AI-generated information, identifying patterns and changes in AI visibility over time.
Her research perspective emphasises transparent, evidence-based and non-partisan analysis, alongside a broader interest in how artificial intelligence is reshaping public information environments.
Connect with Alice on LinkedIn
Hisal Hansaja Nanayakkara Ratnayake — Master of Analytics, Massey University
Research interests: Data Analytics, Machine Learning and AI Information Systems
Hisal is completing a Master of Analytics at Massey University, having previously earned a Bachelor of Information Sciences in Software Engineering.
His experience spans software development, artificial intelligence, database management, machine learning and data analytics.
Through his work as a Data Analyst with Te Tira Ahu Pae, Hisal worked with complex organisational datasets, improving data definitions, strengthening reporting standards and automating financial and student-engagement reporting to support senior management and Board decision-making.
He has also engaged with Massey University teams on AI-related initiatives and serves as the student representative for Massey’s Auckland campus.
Through the CiteCompass research initiative, Hisal is particularly interested in examining how generative AI systems surface, represent and cite information.
He aims to contribute his analytical expertise to transparent, politically neutral research while extending his experience in AI analytics and longitudinal research.
Connect with Hisal on LinkedIn
Mohamed Osman — PhD Researcher, Massey Business School
Research interests: Responsible AI, Technology Adoption and Governance
Mohamed Osman is a PhD researcher at Massey Business School, exploring how emerging technologies, including artificial intelligence, influence healthcare quality and service delivery in New Zealand.
He holds a Master of Business Studies in Management with Distinction and brings extensive professional experience in clinical governance, healthcare leadership, quality improvement and research.
Mohamed currently serves as a Clinical Governance Lead and is also a practising registered pharmacist.
His academic interests centre on digital transformation, technology adoption and the responsible application of emerging technologies to improve decision-making and outcomes.
As part of the CiteCompass research team, Mohamed is interested in understanding how artificial intelligence shapes information, public perception and democratic discourse.
He brings a valuable governance and research perspective to the initiative, with a particular interest in transparency, academic rigour and responsible innovation.
Connect with Mohamed Osman on LinkedIn
Bringing Together Research and AI Visibility Expertise
The postgraduate researchers contribute complementary expertise to a research initiative established and led by CiteCompass.
CiteCompass Directors and Co-Founders Doug Johnstone and Andrew McPherson bring experience spanning digital strategy, AI information discovery, technology implementation, content authority and AI visibility measurement. Ron Murray our Global Partner Manager and AEO Optimization Expert Rebecca Caroe provide governance and guidance to the project.
The CiteCompass platform provides the technical foundation for monitoring how publicly available information appears across major generative AI systems.
The wider research initiative combines that measurement capability with researchers who bring experience in statistical and data analysis, research synthesis, technology governance and human–technology interaction.
This combination supports an important objective: building a clearer evidence base for understanding how generative AI systems represent information in an evolving public information environment.
A Commitment to Independent and Transparent Research
Political independence is fundamental to the CiteCompass NZ Election 2026 AI Visibility Monitor.
The study applies an equivalent research architecture, measurement framework and monitoring methodology to all six parliamentary parties included in the research.
Individual research questions may evolve over time as part of CiteCompass’s dynamic methodology, reflecting changes in the information environment.
The research is observational rather than a controlled experiment or political opinion poll.
We report what the data shows, including variations in AI visibility, source selection and citations, without drawing conclusions about the political merits of the information being measured.
Our governing principle is straightforward:
Observe. Measure. Report. Do not advocate.
This research does not endorse or oppose political parties, recommend how New Zealanders should vote or predict election outcomes.
Our objective is to contribute to a better understanding of how generative AI is changing information discovery — an issue with implications that extend well beyond politics.
Follow the Research
As New Zealand approaches the 2026 General Election, the CiteCompass research team will continue examining how AI-generated answers, source citations and political-policy visibility evolve.
The longitudinal study provides an opportunity to observe these changes over time rather than relying on a single snapshot.
We welcome interest from researchers, journalists, technology professionals and anyone seeking to better understand the growing role of generative AI in public information discovery.
Explore the research:
Visit the NZ Election 2026 AI Visibility Monitor and Research Methodology
Explore the Interactive AI Visibility Report
About CiteCompass
CiteCompass is an AI visibility research and analytics platform helping organisations understand how they are discovered, represented and cited across generative AI systems.
The CiteCompass NZ Election 2026 AI Visibility Monitor applies this technology to an independent longitudinal study of how publicly available political information is surfaced and cited during New Zealand’s 2026 General Election.
Research disclosure: The study is an independent CiteCompass initiative with contributions from postgraduate researchers studying at Massey University. Individual university affiliations do not, by themselves, imply institutional endorsement. The research does not assess political-policy quality, measure voter support or predict election outcomes.