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Stay informed throughout the Royal Commission

The Royal Commission is well underway, and it's imperative for aged care organisations to be aware of the media generated, and how it could affect your business or communications.

Keen to stay on top of it all?

Let our team help!

We can provide you with a comprehensive view of the topics and spokespeople through delivering insights to you and your team. We can aid in decision making and help your organisation manage your reputation.

Get in touch with us today!

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Your daily briefing to keep you informed

Coverage of the Royal Commission is expected to highlight the failure of aged care institutions and leaders within the sector.

Our Briefing can be tailored to your organisation’s specifications and requirements. Manage your reputation and ensure you are aware of the media generated.

Get a sample briefing of what you could be receiving each day.

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How do I navigate aged care in Australia? How easy are government services to deal with? How well supported are people with disabilities? These are big questions about life in Australia, and many people now put them to an AI tool before they visit a website, pick up the phone or speak to anyone. They rarely mention a government agency by name, yet the answer they get still shapes what they believe about the services behind it: whether the system works, who is responsible and whose information they can trust. That is reputation taking shape, in a conversation no communications team is part of.

To see how that plays out, we used Your Prompts, a new feature in Isentia's AI View, to track how leading AI models answer these questions. Here's what we found, whose information the models used, how each model goes about sourcing its answers, and what it all means for public-sector communicators.

Starting with the question

Most AI visibility tracking starts with an organisation's name. Your Prompts lets you set your own questions, which gives public-sector teams a much wider view of their reputation. People rarely ask an AI tool about an agency by name; they ask for help with whatever problem is in front of them, whether that's getting a parent into aged care or working out what support is available for a carer. Or they ask something bigger, such as how well the country looks after older people.

We tracked six sets of questions across leading AI models, covering the things people deal with at different stages of life: finding their way around government services, getting older, living with disability and caring for someone, raising a family, staying healthy, and making ends meet. For this article we focused on three of them: access and navigation, aged care, and disability and carers. These are the moments when people depend most directly on the government, which means a wrong or incomplete answer can have real consequences for someone trying to get help, and can colour how they feel about the system as a whole.

We compared answers from ChatGPT, Claude, Gemini, Perplexity and Google AI Overview, looking at what each model said, which sources it cited and which organisations it named. The questions were set up for tracking rather than drawn from a survey of what the public actually asks, and the findings reflect a single point in time, using the latest data from 27 October 2026. Even so, the patterns in how AI finds and presents information about public services were clear and consistent.

How easy are government services to deal with in Australia?

We asked this alongside a second question: how well government support reaches the people who need it. Most models landed on a similar view: digital services work well for simple tasks, while complex cases, phone contact and people in vulnerable situations are where things get harder. The more interesting part is where that view comes from. The models formed it largely through oversight bodies, with the national audit office's findings carrying particular weight.

Government's own voice only came through when a model cited official pages, as when one model described digital services as a major strength, using a government website as the source. In other words, when AI assesses how the government is performing, it largely takes the word of the ‘referees’. Owned content can earn you a line in the answer, but auditors, commissions and advocates write most of the scorecard. For reputation, that gives an audit finding a second life. Well after the news cycle moves on, it can still be part of the answer people get when they ask how the government is doing. That brings us back to a question we raised in our article on AI visibility for government agencies: is your organisation still seen as the main authority on its own services?

How do I navigate aged care in Australia?

Almost every model named government services as the place to go for financial assessments, payments and in-person help, and the tone was neutral to positive. One model went as far as recommending that people complete a means assessment early so they don't end up paying more than they need to.

The catch is that the agencies people were being sent to were rarely the source of that information, which mostly came from other government portals and guides written by aged care providers and advocacy groups. In one answer, even an agency's own contact details were taken from a seniors' advocacy group's website. Being named in an answer, then, is quite different from being its source. It builds recognition, but someone else is setting people's expectations of what they'll find when they get there, and if that guide is out of date, it's the service they feel let down by.

Zoom out to the bigger question of how well Australia looks after older people, and the agencies that were the first port of call in the practical answers didn't appear at all. These answers were framed by the Royal Commission into Aged Care Quality and Safety, which concluded in 2021, with most models opening on its findings and some giving them more weight than the reforms that followed. This is the reputational point that's easiest to miss: the practical question tells people where to go, while the big question tells them what kind of system they're dealing with. As we covered in why content freshness matters for AI visibility, old stories have a habit of shaping AI answers long after the facts have moved on.

How well supported are people with disabilities in Australia?

The models discussed income support payments without naming the agency that delivers them, focusing instead on the NDIS and the gaps in support. That said, not every absence is a problem. Some questions genuinely aren't about a particular organisation, so it makes sense for it to sit them out. The useful distinction for communicators is between a relevant absence, where the question simply isn't about you, and a missed opportunity, where your work is being discussed and you aren't getting the credit. Repeated across enough answers, a missed opportunity leaves people with a picture of support that doesn't include the people delivering it.

Questions about caring for someone played out differently. Every model gave almost the same answer and pointed people to the same national carer support service. When official information is clear and consistent across agencies, peak bodies and support services, AI repeats it faithfully. There was one notable exception, where a model explained the government's carer payments using a blog from a private company that sells personal medical alarms. The information was mostly accurate, but it shows how far an explanation can travel from its original source. The good news is that consistency across your wider network really does pay off: when the organisations around you describe your services the way you do, AI is more likely to get them right, and that shared story becomes part of your reputation.

Why each model tells the story differently

Across all three categories, each model showed clear habits in the sources it reached for. We can see what each one cites, even if we can't see exactly how it decides, and the patterns are consistent enough to act on. In practice, your reputation can look different depending on the tool someone uses. These habits also build on what we found when we looked at how different LLMs represent your organisation.

Model	Where it gets its information	Example from our research	What it means for communicators
ChatGPT	Official statistics, audit reports and formal reviews. It pairs almost every claim with a figure or finding, much like a policy analyst writing a briefing note.	When asked whether government support reaches people in need, it built its answer around the national audit office’s findings. It was also the model most likely to cite the website of the agency delivering a service.	Oversight reports shape how ChatGPT judges your performance, while your own pages shape how it describes what you do.
Claude	The widest mix of sources, including advocacy groups, provider guides and commentary alongside government material. It tends to explain the reasons behind an issue and present more than one side.	When describing the Royal Commission’s “national disgrace” finding, it relied mostly on second-hand accounts of the report, such as Wikipedia and a private aged care provider’s website.	The organisations that retell your story effectively become your spokespeople.
Gemini	University research and international bodies such as the OECD, drawn from Google’s broad index of academic platforms, video and international sources.	On aged care, it drew on an overseas policy institute’s summary of Australia’s new aged care legislation.	Published research and evaluations carry real weight, as do secondary sources describing your work, wherever in the world they are published.
Perplexity	The most recently updated pages, quoted closely. It is built around live search with visible citations, so it favours recent, easy-to-access pages.	On access to services, it quoted a government corporate plan published only weeks earlier.	This is where keeping your own content current pays off fastest.
Google AI Overview	A small number of sources, summarised briefly, because it is designed to give a quick answer at the top of search results.	On disability support, it relied mainly on the scheme’s own website and summarised criticism in general terms, without naming who made it.	The few sources it chooses carry a lot of weight, so clear, well-structured official pages give you the best chance of being one of them.

One question, several versions

Put together, the same question can produce an audit-style answer, an advocacy-informed analysis, a research summary or a current snapshot, depending on which tool someone happens to open. Two people asking the same question can come away with quite different impressions of the same service. There's no single AI view of an organisation to manage, because each model has its own sources and each needs a slightly different approach.

Zooming out: how these answers add up to reputation

Look at any one of these answers and it can seem like a visibility issue. Put them together and it's a reputation issue. For public-sector organisations, reputation has always been about more than what's said about you by name. It rests on whether people believe the system works, know where to turn and trust what they're told, and those impressions are now forming in AI answers, one question at a time.

Across these questions, four things shaped the impression an answer left:

• Who gets named. Whether you appear when your work is being discussed, and get the credit for it.
• Who does the explaining. Whether people hear how your services work from you, or from a provider, an advocate or a company blog.
• Who acts as referee. Whose assessment of your performance gets repeated as the verdict.
• Which story sets the frame. Whether the answer opens on where things stand today, or on a finding from years ago.

None of this shows up if you only ask AI about your organisation by name. You see it when you ask the questions your audience is asking. And it matters, because AI is now one of the main places where people go for information about the things that matter to them.

What this means for public-sector communicators

Government organisations can't control what AI says, but they can do a lot to influence the information it draws on, and with it the reputation that forms around them. Five practical steps came out of this research.

• Track the big questions, not just your name. The most useful insights came from questions about services and real-life situations rather than about any one organisation, so start with what your audience is trying to do or understand, and check what AI is telling them.
• Work with the bodies that assess your performance. Auditors, commissions and advocates shape how AI judges your work, so respond to their findings publicly and make sure your progress is recorded in the sources they, and AI, rely on. That way an old finding doesn't have to stand alone.
• Support the organisations that explain your services. Sister agencies, peak bodies, providers and advocacy groups often explain your services for you, so give them clear, current information to work from. As we found in our analysis of Tier 1 and Tier 2 media in AI answers, specialist and niche sources often matter more to AI than their profile suggests.
• Keep practical information clear and up to date. Plain-language pages on eligibility, processes and how to get help are what AI repeats when people ask how to do something. Organisations that deliver services directly rely on this more than most, because outdated information can lead someone to miss out on support they're entitled to.
• Check answers across several models regularly. Each model uses different sources, so one model's answer is a poor guide to the others, and because answers shift as new content is published, regular tracking shows whether your updates are reaching the sources AI uses.

Whose information is AI using?

AI is already answering big questions about life in Australia, whether or not the public-sector organisations involved are part of the conversation. This research shows that an organisation can be mentioned often and still have surprisingly little say in how its services are described or how its performance is judged, with other organisations doing much of the explaining and each AI model weighing those voices differently.

For communicators, the job is to understand that wider network of sources and make sure accurate, current information runs through all of it. It's worth asking what AI says about your organisation. It's just as worthwhile asking what AI says when nobody mentions you, and whose information it's using to say it. That's where much of your reputation is now taking shape.

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Want to see what AI tells people about the questions that matter to your audience? Get in touch about AI View.

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A weekly tracker tracing the stories, figures and policies driving media and social coverage in the 2026 New Zealand General Election across Online News, TV, Radio, Newspaper, Magazine, X, Facebook, Instagram, TikTok, Threads and Forums. This edition covers conversations and coverage from 15th - 21st October, highlighting what’s shaping the election conversation.

1. Election Conversation

Media = news coverage. Social = all public posts across X, Facebook, Instagram, TikTok and Threads - everyone posting, not just media outlets.

2. Media Issue of the Week

Opportunity Party Puts the Kingmaker Question at the Centre of the Campaign

The Opportunity Party, led by Qiulae Wong, was the most covered new story in the news this week. It polled 8% in the 1News Verian poll on 13 October and 5.4% in the Post/Freshwater poll on 19 October, just above the 5% needed to enter Parliament. With National and Labour close together, outlets described it as a possible kingmaker. Christopher Luxon ruled out working with the party at the Herald leaders' debate, then told West Coast voters he would work with "whoever I have to", and campaign chair Simeon Brown ruled it out again. David Seymour said ACT would consider a four-party arrangement that includes Opportunity. Later in the week the focus turned to the party itself, with former board members describing internal problems and Wong saying the party's rules need another look.

News outlets ran 271 items on the party or the kingmaker question in the headline or summary (9.5% of the 2,842 election items), and it was mentioned somewhere in 724 (25.5%). Coverage was highest on 15 October, after Luxon's West Coast comments, Brown's response and Seymour's remarks, and again on 20 and 21 October, with new poll results, the former board members' claims and Wong's comments on coalition deals.

It matters because it affects who can form a government. The Post projected that Opportunity's seven MPs could give either a Labour-led bloc a narrow 61-seat majority or a National-led bloc 66 seats, so every party has had to say whether it would work with Opportunity. On social media it was a smaller conversation, with 325 posts (4.2%), and those posts were less negative than average (44.4% negative against 53.0% overall). The story is about coalition options rather than a policy position, so it is not linked to a party issue below.

3. What's happening across media and social?

2,842 media items · 7,730 social items · share of each channel's own conversation, so the two bars are directly comparable

"Social" is all public posts across X, Facebook, Instagram, TikTok and Threads - not just media organisations' own accounts.

Most frequent bylines and presenters: The most frequent bylines and presenters this week were Sean Plunket (The Platform), Ryan Bridge (Three), Henry Cooke (Waikato Times) and John MacDonald (Newstalk ZB).

Widest-reach accounts: The accounts with the widest reach among election posts were news outlets: the New Zealand Herald, 1News, Radio Tarana, RNZ and Stuff, along with the New Zealand Labour Party account. Party leaders' own accounts posted often but have smaller followings.

Law and order made up 22.1% of the issues discussed on social media but 9.1% in the news, about 2.4 times as much. Part of the gap is the continuing reaction to the Greens' and Te Pāti Māori's visit to a Mongrel Mob event, last week's Media Issue of the Week: 137 of the 791 law and order posts mention it. Across all social posts the visit came up in 291 (3.8%), 70.5% of them negative, and in 257 news items (9.0%).

The Opportunity Party shows the gap the other way round. It was in the headline or summary of 9.5% of news items but only 4.2% of social posts, about 2.3 times as much attention in the news. Among the parties, NZ First, the Greens and ACT had a bigger share of social mentions than news mentions (NZ First 19.6% against 12.7%, Greens 18.2% against 13.7%, ACT 14.1% against 9.9%), while National and Labour had a bigger share in the news (National 25.8% against 21.0%, Labour 23.5% against 17.8%).

4. Party Share of Conversation

Shown for seven parties, including Te Pāti Māori and the Opportunity Party (TOP), which is this week's Media Issue of the Week. Shares add up to 100% of the seven shown. Share of conversation measures attention, not polling, and is not a sign of electoral success.

5. Top candidates this week

Christopher Luxon (1,614 mentions) and Chris Hipkins (1,611) were level at the top. Both were at the centre of the final leaders' debate on 20 October and the questions about working with Opportunity, and each party announced new policy during the week.

Winston Peters (1,133) was third and was mentioned far more on social media (726) than in the news (407). The most shared posts about him covered his comments on diversity, his message to David Seymour on strategic voting and his public meetings. David Seymour (840) drew attention for saying ACT could work with Opportunity.

Chloe Swarbrick (412) was in the news more than on social media (227 against 185), with coverage of the Greens' plan to reverse public service cuts and the Mongrel Mob visit. Mentions measure how much someone is being talked about, not how they are polling.

6. Election Issues

Top 4 themes this week

What's driving conversation about each party?

Each party's top issues this week in social conversation, ranked by how much they were discussed

Issues are ranked from social posts. Counts are not shown because the numbers for a single party and issue are small.

7. Issues to Watch

• The coalition question around the Opportunity Party is likely to stay in the news until election day. Luxon has given two different answers on working with the party, and polls this month have put it between 4.8% and 8%, so a small shift in support could change which parties can form a government. The party's internal problems are also now in the spotlight.
• Voter enrolment is becoming a political issue ahead of the 25 October deadline. New rules mean people cannot enrol at the polling booth, and 112 news items this week covered enrolment or the electoral roll, many focused on young and first-time voters. The number enrolled when the roll closes will show whether these concerns made a difference.
• Social conversation leaned negative this week: 53.0% of posts with a clear tone were negative, 32.6% neutral and 14.4% positive. Cost of living is a top issue for four parties (National, Labour, Greens and ACT). Health is a top issue for two parties (National and Labour). Issues that matter to several parties are the ones most likely to keep shaping the campaign.

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If you want to find out more about how Isentia can help you understand the NZ media landscape, please reach out to us here.