Evidence · Immigration

Immigration: questions, answers and evidence

Read all 797 original answers and the tables behind the findings. The 27 missing answers are from the China comparison on three platforms.

questions
143
captured answers
797
missing responses
27
answers collected
15–20 October 2026

01

Every question, with its answers

Each question was written as a voter would ask it and went to all four assistants. Some were also asked from a town. Open a question to read every answer to it in full.

Showing 20 of 143 questions

02

The tables behind the study

Every figure on the study page comes from these tables. They are CSV files, which open in any spreadsheet.

  • Complete AI answers

    answers.csv

    One complete original answer, with the question, platform, country setting and migrant profile.

    question_id, surface_code, location_ref, result_id, prompt_id, platform, scan_id, collection_panel, question_text, response_text

  • The questions we asked

    question-catalogue.csv

    One question with the migrant profile, wording and purpose.

    question_id, question_version, group_id, case_id, asked_for, output_id, module_ids, category, wording_style, prompt_set, collection_panel, comparison_id, exact_text, distinguishing_facts, stated_facts, tags, status

  • Planned questions, platforms and countries

    execution-assignments.csv

    One question, platform and country we planned to collect an answer from.

    question_id, collection_panel, location_name, location_ref, surface, surface_code

  • The 27 missing answers

    missing-cells.csv

    One expected answer that was not collected.

    question_id, collection_panel, location_name, location_ref, surface, surface_code

  • Locations named for each migrant profile

    location-by-persona.csv

    How often a place was named in the twelve New Zealand answers for each migrant profile.

    persona, place, answers, denominator, wording_styles, wording_count, surface_count

  • Locations named across question wordings

    location-by-wording.csv

    One profile, platform and place, showing which versions of the question led to an answer naming the place.

    persona, surface, place, answers, denominator, wording_styles

  • Locations named by collection country

    location-by-region.csv

    One place and country setting; the China comparison has nine answers on Google AI Mode only.

    region, place, answers, denominator, surfaces

  • Eight countries on Google AI Mode

    location-ai-mode-eight-regions.csv

    One place and country across the same nine questions on Google AI Mode.

    region, place, answers, denominator

  • Matched local and overseas answers

    matched-region-answer-pairs.csv

    A New Zealand answer alongside the same question and platform using another country setting.

    region, surface, persona, question_id, result_id, nz_result_id, same_place_set, jaccard, added_names, omitted_names

  • Topics explicitly raised in the answers

    signals-by-output-platform.csv

    How often selected words and phrases appeared, by topic and platform.

    output, surface, signal, answers, denominator

  • Topics raised for each migrant profile

    signals-by-persona-output.csv

    How often selected words and phrases appeared, by migrant profile and topic.

    output, persona, signal, answers, denominator

  • Website addresses in captured answers

    captured-answer-links.csv

    Web addresses saved in the original answers, with image and file links identified.

    question_id, result_id, prompt_id, surface, surface_code, region, output, persona, wording, panel, words, raw_page, transcript, url, domain, host_class, image_or_asset

  • Extra table: links excluding images and files

    captured-links-by-platform.csv

    One platform across the same 143 New Zealand questions. The table excludes image and file links; the main Sources section counts those links.

    surface, denominator, answers_with_links, answers_with_govt_links

  • Captured answer lengths

    platform-answer-length.csv

    One platform across the same 143 local questions.

    surface, answers, median_words, mean_words

  • Recorded websites by answer

    sources-by-answer.csv

    Each website recorded as a source for an answer, with the page addresses and number of statements linked to the website.

    question_id, result_id, prompt_id, surface, surface_code, region, output, persona, wording, panel, words, raw_page, transcript, domain, publisher, claim_count, source_urls

  • Recorded sources and their original claims

    source-claim-ledger.csv

    Sources attached to individual statements, with the original answer, quotation and source passage.

    narrative_id, claim_id, question_id, result_id, prompt_id, surface, surface_code, region, output, persona, wording, panel, words, raw_page, transcript, domain, url, source_passage, claim_quote, quote_exact

  • Answers with sources and answers with links

    source-answer-coverage.csv

    Each New Zealand answer, showing whether sources were recorded and whether the answer text contains a web link.

    question_id, result_id, prompt_id, surface, surface_code, region, output, persona, wording, panel, words, raw_page, transcript, associated_websites, had_sources, literal_url_answer

  • Website publisher classifications

    source-publisher-classification.csv

    Each website, the type of organisation behind the website and the reason for the category. Unconfirmed types remain Other.

    domain, publisher, basis, source

  • Tone toward each place

    place-sentiment-ledger.csv

    One named place in one answer, with the positive, neutral, negative or mixed label, supporting passages and reason. All 108 New Zealand answers about where to live were reviewed.

    result_id, question_id, prompt_id, persona, assistant, region, place, stance, paragraph_numbers, supporting_passages, display_passage, reason, answer_sha256, reviewed_on

  • Facts supplied in each question

    prompt-reporting-eligibility.csv

    Every question, with corrected descriptions of the facts stated and limits on interpreting its answers.

    question_id, reviewed_on, prompt_sha256, original_stated_facts, corrected_stated_facts, metadata_changed, destination_explicit, descriptive_counts_included, interpretation_rule

  • Sources across question styles

    source-wording-incidence.csv

    One website, profile, topic and platform, with answer totals, question styles and the original answer references.

    persona, output, surface, domain, answers_with_source, eligible_answers, wording_styles_with_source, eligible_wording_styles, observed_styles, eligible_styles, answer_ids, by_style

  • Questions with corrected fact descriptions

    question-catalogue-reviewed.csv

    The unchanged original question text with fact descriptions reviewed on 28 October 2026.

    question_id, question_version, group_id, case_id, asked_for, output_id, module_ids, category, wording_style, prompt_set, collection_panel, comparison_id, exact_text, distinguishing_facts, stated_facts, tags, status

  • Statements checked against official sources

    statement-checks.csv

    One checked statement, with its exact passage, verdict, official source, review date and original answer reference.

    check_id, measure_id, question_checked, result_id, prompt_id, question_id, persona, assistant, wording, exact_statement, verdict, what_the_source_says, source_name, source_url, checked_on, answer_sha256

  • Policy questions covered by the checks

    statement-measures.csv

    One policy question, showing checked statements, original answers and the question wordings represented.

    measure_id, question_checked, checked_statements, distinct_answers, wording_styles_with_checked_assertions, wording_styles, answer_ids, question_ids, scope

Use the question and answer numbers to follow the evidence between tables. Locations named in warnings and comparisons count. Sources attached to an answer and web links in the answer text are counted separately.

03

The reviewed evidence

We read all 108 New Zealand answers about where to live to assess the tone toward each named place. A separate selection of 41 answers explores practical advice and contrasts across topics. The original policy checks were made on 22 October and expanded on 28 October 2026; verdicts cover selected statements, not every answer.

ChatGPT · New Zealand country setting

I work in software and data and would be moving on my own without a job lined up. I'm open to anywhere in New Zealand. Where would you suggest I start looking?

If you work in software and data and are moving to New Zealand alone without a job lined up, I’d prioritise places where you can combine a realistic job search, a manageable cost of living, and an easy way to build a social life.

I wouldn’t automatically choose Auckland just because it’s the biggest city, nor would I move to a small town purely for cheaper rent. Your best starting point is likely a city with several potential employers, good access to professional networks, and enough financial runway to search without too much pressure.

Where I’d start looking

1. Auckland — best for maximising job options

Best overall starting point

Auckland is where I’d start if getting a job is your top priority. Its larger economy gives you a wider pool of potential employers across software, SaaS, fintech, consulting, retail technology, cloud infrastructure and data analytics.

  • Best for: software engineering, data engineering, analytics, cloud and product roles.
  • Trade-off: housing costs can eat into your savings, and commuting can be frustrating.
  • My approach: rent a room in a shared house initially, rather than committing to an expensive solo apartment.

2. Wellington — best for data, analytics and public-sector tech

Wellington is particularly worth investigating if your background includes data analysis, data platforms, business intelligence, Python, consulting or enterprise software.

Government agencies, consultancies and organisations working in policy, statistics and digital services are important potential employers. Recent listings have included data and analyst-developer roles at Stats NZ and other government organisations. Senior Data Analyst | Canterbury - Christchurch;WellingtonData Analyst Jobs in All Wellington, Job Vacancies - Sep 2026

  • Best for: analytics, data science, BI, data engineering and government digital services.
  • Trade-off: the market is more exposed to public-sector hiring and budget changes.
  • Lifestyle: compact, walkable central areas and plenty of opportunities to meet people through professional and hobby groups.

3. Christchurch — best for balancing costs and career

Christchurch would be high on my list if you want a good quality of life while preserving your savings. It has opportunities across software, engineering, technology services, agriculture technology and data.

4. Hamilton — a practical lower-cost alternative

Hamilton is worth considering if you prefer a smaller city and are open to roles in healthcare, education, agritech, logistics, business systems and regional employers.

  • Best for: data and reporting, business systems, software support and technology roles connected to established industries.
  • Trade-off: fewer dedicated technology employers and less choice if you're looking for a very specialised software role.
  • My approach: consider it especially if you find promising employers before you move.

How I’d compare them

Factor Auckland Wellington Christchurch Hamilton
Breadth of job market Excellent Strong Good More limited
Data and analytics Strong Excellent for public-sector data Good Good in selected industries
Software opportunities Excellent Strong Good Moderate
Housing-cost pressure High Moderate–high Generally lower Generally lower
My verdict Start here Strong alternative Best balance to explore Selective option

These are broad comparisons, not guarantees of current vacancy numbers or salaries. Your specialisation and experience level could change the ranking substantially.

Where to look for jobs before moving

I'd begin with these resources, comparing actual vacancies across all four cities rather than relying on broad impressions of the market.

SEEK New Zealand

Start with software developer, data engineer, analytics engineer, data analyst and machine learning searches.

Browse data analyst jobs · Browse software jobs

NZ Government Jobs

Especially relevant for analytics, statistics, data platforms, digital delivery and public-sector technology.

Browse government vacancies

LinkedIn

Find local recruiters, hiring managers, technology meetups and alumni or professional contacts before you arrive.

Search New Zealand jobs

I'd also contact technology recruitment firms before relocating, apply to a mix of permanent and fixed-term roles, and ask recruiters which city currently has the strongest demand for your particular skills. Don't assume remote work means you can live anywhere: some employers require you to be based in a particular region or attend an office.

Moving alone without a job: my recommended strategy

  1. Apply from overseas or wherever you currently live. Try to establish whether employers will interview you before you incur relocation costs.
  2. Choose temporary accommodation first. A room in a shared flat or short-term rental gives you flexibility while you learn the neighbourhoods.
  3. Keep a financial buffer. Ideally, budget for several months without employment, including rent, food, transport, setup costs and any visa-related expenses.
  4. Build a routine immediately. Coworking spaces, sports clubs, meetups and volunteering can help you form a social network when you arrive on your own.
  5. Review the evidence after a few weeks. If one city produces substantially more interviews, let that guide where you settle.

One important caveat: if you are not already entitled to work in New Zealand, check your visa and work rights before making relocation plans. The options available to you may depend on your citizenship and visa conditions.

Two things that would help me narrow this down

Your answers could change my recommendation quite a bit.

With those details, I can give you a much more targeted recommendation—including which city I'd choose first, which industries I'd target, and how I'd approach the move without a job lined up.

Ask anything

ChatGPT can make mistakes. Check important info.

Captured 15–20 October 2026

Gemini · New Zealand country setting

I work in software and data and would be moving on my own without a job lined up. I'm open to anywhere in New Zealand. Where would you suggest I start looking?

If you are planning to move to New Zealand solo and without a job lined up in software or data, your best bet is to target the country's three primary tech hubs. While New Zealand’s tech ecosystem is relatively tight-knit, these three cities offer distinct advantages depending on your risk tolerance, lifestyle preferences, and specialization.


1. Auckland: The Commercial & Scale-Up Capital

  • Best for: Private sector tech, high-growth SaaS, multinational enterprise hubs, and maximum job volume.
  • Why start here: Auckland is New Zealand’s economic engine. It hosts the largest concentration of corporate headquarters, major tech consultancies, and scaling product companies (such as Vista Group and various global cloud/SaaS branches). If your background is heavily commercial, product-focused, or involves modern cloud data stacks (Snowflake, Databricks, modern data engineering), Auckland generally has the highest raw number of private-sector openings.
  • The Catch: The cost of living (particularly rent) is the highest in the country, which is an important factor when arriving without an immediate income.

2. Wellington: The Government, Policy, & Data Epicenter

  • Best for: Public sector data roles, government digital agencies, large consulting firms, and stable enterprise environments.
  • Why start here: Wellington is the capital and the heart of New Zealand’s public sector, ministries, and crown entities. It has a massive appetite for data engineers, analysts, data architects, and integration specialists to support large-scale government infrastructure and data platforms. The tech community here is collaborative, deeply connected, and heavily driven by civic tech and complex data governance.
  • The Catch: The local economy is more heavily weighted toward government spending, meaning public sector budget shifts can occasionally influence hiring volumes.

3. Christchurch: The Rising Innovation & Engineering Hub

  • Best for: Ag-tech, hardware-software integration, geospatial/mapping tech, lower cost of living, and a balanced lifestyle.
  • Why start here: Christchurch has quietly built a thriving tech and startup ecosystem (anchored by a strong manufacturing, engineering, and ag-tech sector like Halter or local software firms). It offers a vibrant community for developers and data professionals with a drastically more manageable cost of living and housing market than Auckland. Many companies here are deeply innovative and offer great hybrid flexibility.
  • The Catch: Fewer total enterprise or massive corporate headquarters compared to Auckland, meaning networking and targeted outreach are crucial.

Recommended Strategy for an Independent Move

  1. Scan the Local Boards Early: Before booking a ticket, spend a couple of weeks actively browsing SEEK NZ, Trade Me Jobs, and Workable. Pay attention to which cities are posting the most roles matching your specific tech stack (e.g., AWS/Azure, Python, SQL, Spark, .NET).
  2. Leverage Hybrid Flexibility: Many Kiwi companies offer hybrid working models. Landing a role based out of Auckland or Wellington often gives you the flexibility to live slightly outside the central business districts or choose a city like Christchurch while working remotely for certain distributed teams.
  3. Tap into Local Meetups: Tech communities in New Zealand (like WellyTech or various Auckland/Christchurch developer and data meetups on Meetup.com) are very welcoming to newcomers. Attending events or co-working spaces early on is often how unadvertised or "hidden" contract and permanent roles are secured.

Which specific areas of software or data do you lean toward (e.g., data engineering, backend development, analytics, machine learning)? Knowing your stack could help narrow down which city has the tightest alignment.

Ask Gemini

Gemini is AI and can make mistakes.

Captured 15–20 October 2026

Google AI Mode · New Zealand country setting

I work in software and data and would be moving on my own without a job lined up. I'm open to anywhere in New Zealand. Where would you suggest I start looking?

Moving to New Zealand independently without a job lined up in software and data means targeting areas with the highest density of tech employers, active networking scenes, and robust job markets.

The primary urban centers serve distinct segments of the tech and data industries:


** Auckland (The Commercial & Corporate Hub)**

  • The Vibe: New Zealand's largest economic center and the largest market for private-sector tech, enterprise software, and major corporate data teams.
  • Focus Areas: Fintech, SaaS, large-scale retail/logistics tech, and major enterprise corporations.
  • Pros: Highest number of overall job listings, largest concentration of multinational tech firms and scale-ups, and diverse industries.
  • Cons: Highest cost of living and rental market in the country, plus heavy commuter traffic.

Wellington (The Public Sector & Digital Capital)

  • The Vibe: The capital city with a high concentration of digital tech roles, heavily weighted toward government agencies, ministries, and public-sector data infrastructure.
  • Focus Areas: Government digital services, policy-adjacent data analytics, security, and enterprise software contracting.
  • Pros: Very high concentration of digital tech professionals, strong contracting market with competitive hourly rates, and a compact, walkable, creative urban environment.
  • Cons: Heavily exposed to government spending shifts and public sector restructuring cycles.

Christchurch (The Engineering & Innovation Hub)

  • The Vibe: A fast-growing center for software engineering, agritech, hardware-software integration, and heavy tech innovation anchored by the city's Innovation Precinct.
  • Focus Areas: Software development, cloud computing, agritech, geospatial data, and manufacturing tech.
  • Pros: Thriving, collaborative tech community, significantly more affordable housing and cost of living compared to Auckland or Wellington , and a balanced lifestyle close to the mountains and sea.
  • Cons: Smaller absolute volume of entry-level or pure data-analyst corporate roles compared to Auckland.

Recommended Approach to Starting Your Search

  1. ** Auckland or Christchurch** are generally the most versatile launchpads for a software and data professional depending on whether you lean toward large commercial enterprises (Auckland) or a blend of affordability, lifestyle, and a thriving innovation precinct (Christchurch).
  2. Check local job boards and recruitment agencies that specialize heavily in the local tech landscape, such as Seek New Zealand or specialized IT recruiters like Absolute IT. [Absolute IT]
  3. Engage with local tech communities and Slack/Meetup groups (such as TechLife NZ or local city-based developer/data meetups) before or immediately upon arrival, as a massive portion of the mid-to-senior market runs on networking.

Would you like to explore the job market viability for your specific stack/specialty (e.g., data engineering vs. frontend/backend vs. machine learning), or do you want to narrow down based on lifestyle preferences like climate or housing budget?

Ask anything

Captured 15–20 October 2026

AI Overviews · New Zealand country setting

I work in software and data and would be moving on my own without a job lined up. I'm open to anywhere in New Zealand. Where would you suggest I start looking?

AI Overview

Moving to a new country solo without a job lined up is an incredibly bold and exciting step! The tech sector in New Zealand is well-connected, but navigating it from scratch requires targeting the right regions and channels.

To give yourself the highest probability of success in software and data, you should focus your efforts on Auckland and Wellington, as these two hubs collectively hold roughly 70% to 80% of all ICT roles in the country.

An overview of where the opportunities live and how to start your search includes:

🏢 Key Geographic Hubs


** Auckland :** This is the commercial powerhouse of New Zealand and accounts for more than 50% of the country's tech jobs. It is home to major corporate headquarters, large data engineering teams, banks, and established tech enterprises.


Wellington : As the nation's capital, it accounts for a large portion of the remaining tech sector. It is a massive hub for data analytics and software development due to the Government/Public Sector contracts, alongside a highly collaborative, creative startup ecosystem (companies like Xero are based here).


Christchurch : If you prefer a slightly lower cost of living with plenty of outdoor access, Christchurch holds about 14% of the tech market and boasts a strong manufacturing, hardware-software integration, and geospatial data niche.


💻 Where to Look: Primary Job Boards

In New Zealand, the job market is heavily centralized on a few key sites. You should set up alerts on these immediately:

  • SEEK New Zealand : This is the absolute gold standard job board in NZ. Most software engineering, data analyst, data scientist, and database administrator roles are posted here first.
  • LinkedIn : Heavily utilized by local tech recruiters. Ensure your profile location is updated to New Zealand as soon as you land, as local recruiters prioritize applicants already inside the country.
  • Trade Me Jobs : While known for classifieds, Trade Me also features local corporate and IT listings, occasionally listing roles that miss the bigger corporate sites.

🤝 Accessing the "Hidden" Tech Market

Because you are arriving without a role, networking will be your superpower. The New Zealand tech ecosystem operates heavily on word-of-mouth and recruitment agencies.

  1. Register with Specialized IT Recruitment Agencies: Reach out to major local agencies like Absolute IT, Potentia, Hudson, Absolute IT, or Find Recruitment. They don't charge applicants, and they often have roles that never make it to public job boards.

  2. Join Local Meetups: Use Meetup.com once you decide on a temporary base. Attend local Python NZ, .NET user groups, Data Science NZ, or Agile meetups. Kiwis are generally highly approachable, and buying someone a coffee can easily lead to an internal referral.


⚠️ Crucial Next Steps: Visas & The Green List

Since you don't have a job lined up, your legal right to work is the most critical variable. Ensure you review the following:

  • Working Holiday Visa (WHV): If you are under 30 or 35 (depending on your nationality), this is the easiest way to enter and work legally immediately.
  • The Green List Pathway: New Zealand maintains a fast-track residency and work visa scheme called the Immigration NZ Green List. Many high-level software engineering and data roles fall under Tier 1 ("Straight to Residence"). Even if you enter on a temporary visa, finding an Accredited Employer who can transition you to a Green List visa is your best long-term play.

To help narrow down the best launchpad for your move, could you tell me:

  • What visa pathway are you planning to use to enter (e.g., Working Holiday, Tourist/Digital Nomad, or looking for sponsorship)?
  • What is your specific tech stack or focus (e.g., Python/Cloud Data Engineering, Frontend React, .NET DevOps)?
  • What kind of lifestyle do you prefer (big city bustle or proximity to beaches and mountains)?
Ask anything

Captured 15–20 October 2026