Blog post
April 15, 2025

Did the leaders debate reignite voter interest or just stoke the culture wars?

As the federal election campaign reaches its midpoint, patterns in media coverage and public attention are beginning to shift. Early social engagement was driven by cost-of-living pressures, energy policy, and political point-scoring, but has waned following the first leaders debate, despite this forum providing leaders the opportunity to set the agenda and strategies of the major parties. So how has coverage focus evolved since the first debate and are audiences still engaging with the campaign or switching off?

Social media engagement ahead of the federal election has been sharp and personal. It focused less on policy and more on identity and representation. From debates on topics such as  immigration to housing stress and culture, social media has driven a values-first narrative. But while early attention  was strong, both media coverage and social engagement have started to wane in the weeks since the campaign launched. The first leaders debate briefly reignited attention—trust, identity, and media—but coverage patterns suggest a shift away from daily blow-by-blow reporting towards broader social and cultural tensions.

As the federal election campaign nears its halfway mark, last week’s media highlights show a contest still struggling to cut through. Key moments included the first leader’s debate, the Treasurers Debate, the energy showdown at the National Press Club, and Senator Jacinta Price’s Perth appearance with Peter Dutton, which drew attention for its MAGA-style rhetoric.  The first leaders debate was billed as a chance to reset the race—but for many viewers, it reinforced existing divides. Media attention around the debate momentarily lifted visibility for all major parties—but the spike was short-lived. The only party that has seen continued increases in social media engagement is the Liberal Party. The Liberal Party’s sustained rise in social media engagement may be linked to its digital-first strategy, including an AI-generated campaign ad spruiking a fuel excise cut and a meme-style diss track targeting Anthony Albanese—tactics designed to capture online attention and drive shareability.

@abcnewsaus

The Liberal party have released a “diss rap” targeting Prime Minister Anthony Albanese. Reporting by Zac Schroedl. Personalise your news and stay in the know with the ABC NEWS app via the link in our bio. #Liberals #DissTrack #FederalElection #AusVotes #KendrickLamar #Drake #PeterDutton #SussanLey #ElectionCampaign #Rap #AnthonyAlbanese #LiberalParty

♬ original sound – ABC News Australia – ABC News Australia

The Liberals also pitched a $1200 tax cut, Labor attacked their WFH backflip, and the Greens pushed housing and tax reform. Meanwhile, Dutton warned of a Labor-Greens-Teal alliance. Coverage suggests public engagement is driven more by polarising moments and political theatre than detailed policy.

When the election campaign officially kicked off, cost-of-living pressures dominated the news agenda. Fresh off the back of the federal budget, it’s no surprise that affordable healthcare, lower gas and energy prices, and tax cuts were the key messages party leaders wanted to land with voters. But coverage quickly pivoted. In the past week, foreign diplomacy—particularly how each leader would manage Donald Trump—has surged in prominence. While Trump’s role in tariff threats has made headlines, his influence on the broader election narrative goes beyond trade. Media reporting has increasingly centred on Albanese and Dutton’s capacity to navigate a potential Trump presidency, with ideological alignment, national security, and economic fallout all in play. The first leaders’ debate was expected to refocus the campaign on domestic issues. However, it briefly touched on international concerns, with Prime Minister Anthony Albanese addressing the potential economic impact of Trump’s proposed tariffs. Albanese described these tariffs as an “act of economic self-harm” that would dampen global growth, highlighting the intertwining of foreign policy with domestic economic concerns. This suggests that sustained attention is more likely when domestic issues are reframed through the lens of foreign diplomacy, and national identity.

In the social media landscape, Trump was a flashpoint in election-related conversation. His influence—real or perceived—was quickly linked to the Liberal Party, with MAGA-style rhetoric and Trumpian policy cues gaining traction online. These narratives tend to escalate on platforms where ideological alignment and cultural grievance amplify engagement. But it wasn’t all imported culture wars—the federal budget, and the Liberal Party’s fuel excise rebuttal, also drove significant social chatter. In recent weeks, comparisons between major party messaging and Trump-era policy—from international student caps and nuclear energy to debates about school curricula—have continued to dominate discussion.

The first leaders’ debate briefly touched on foreign policy, with Albanese warning Trump’s tariffs could hurt global growth, while Dutton framed it as a test of strong leadership. Domestically, Dutton’s renewed push for nuclear power reignited social media debate—drawing comparisons to Trump-era policies and fuelling discussion about Australia’s energy future. At the same time on social media, promises like HECS cuts, free TAFE, and more funding for public schools sparked genuine engagement, especially among younger voters and education workers, showing that practical, future-focused policies can still cut through. Compared to the start of the campaign, where cost-of-living dominated as a top-line concern, the conversation has expanded: audiences are now weighing both hip-pocket issues and the national values shaping Australia’s future.

While the debate itself tended to be overshadowed by frustrations about access and media control, a few political undercurrents still surfaced. Anthony Albanese drew some positive mentions, but reactions were far from policy-focused. The Liberal Party’s early claim of victory became a point of humour, with several users likening it to Trump-style misinformation tactics. Disillusionment with the major parties ran deep, with repeated calls to “break the donor-fuelled duopoly” and shift support toward independents or smaller parties. Still, these reactions seem more like a symptom of broader voter cynicism than a sign of energised political engagement, reflecting broader themes around the declining trust.

The leaders’ debate didn’t reset the race—it refracted it, spotlighting how media coverage is now shaped less by policy detail and more by polarising symbols and cultural cues. As election day nears, the contest for attention is revealing just as much about media strategy and voter fatigue as it is about party platforms.

Discover more of our political news services

Share

Similar articles

object(WP_Post)#7505 (24) { ["ID"]=> int(49871) ["post_author"]=> string(2) "75" ["post_date"]=> string(19) "2026-09-09 02:19:40" ["post_date_gmt"]=> string(19) "2026-09-09 02:19:40" ["post_content"]=> string(17112) "

Audiences are no longer finding information through traditional search engines that favour established news outlets. AI models now highlight highly relevant and contextual information to audiences to often include niche and regional publications alongside major news media. This change challenges the old media hierarchy around tiered publications and pushes organisations to reconsider how and where they need to show up to stay visible in an AI-first world. 

Yes, organisations must focus on optimising their own content for LLMs, but will that always drastically increase the chances of AI models picking up your page? Probably not always. Smart strategy means targeting the specific publications your actual target audience reads — because those are the sources AI models retrieve when answering niche questions. 

It’s closer to digital PR than SEO

Generative Engine Optimization (GEO) is changing how brands approach online visibility. For years, traditional SEO meant focusing on your own site—optimising keywords, building backlinks, and improving on-page content. But AI models work differently. Instead of just using your website, these AI engines rely on trusted third-party sources to answer questions. This shift is taking place  gradually, of course. LLMs increasingly source from earned media (where it is accessible) and even offsite links from trusted sites. Owned media is still where the organisation has maximum control of how it’s own content travels, but a pivotal strategy shift is needed to match what AI models are picking up and citing.

To succeed with AI search, comms professionals need to think more like a digital PR strategist than a SEO expert. The best way to stand out is by earning mentions, quotes, and citations in the external publications your audience—and the AI systems they use—trust most. This does not make a distinction between Tier 1 or Tier 2 media. If AI models are crawling sites that mention an organisation, but the organisation does not acknowledge or even know those sites are being prioritised by LLMs, they risk falling behind in being the right kind of visible. 

To make this strategy work, looking beyond common metrics like traffic to the site or domain authority is not enough. Even a respected industry site will probably not influence AI answers as much if its content is behind a paywall or blocked from search engines. For AI visibility, accessibility to the site or page, structured data that can be crawled, and strong audience alignment are important. Since AI systems use both slow training cycles and fast real-time web searches (RAG), being featured on accessible, relevant niche sites helps an organisation show up accurately when models learn and when they search the web in real time. 

Why is Tier 2 media punching at Tier 1 weight?

According to Isentia's report How AI is destabilising trust and reputation amongst audiences, LLMs cite industry and trade publications about twice as often as traditional news sources. Company content and industry press make up over 60% of the share of voice LLMs use, while traditional news is twice as likely to generate negative sentiment. Thus, tier 1 outlets no longer automatically dominate AI-generated responses and may sometimes have the opposite effect.

Two main factors are driving this shift in which media is picked up by LLMs:

  • The paywalled problem was further expanded on by Dr Momoko Fujita during the Digital News Report: Australia webinar that news organisations must figure out how to make paywalled content easily readable by LLMs. By bridging this gap, these organisations can ensure that AI tools deliver accurate, high-quality reporting rather than missing out on premium content. If not, high-quality coverage may never reach the model. Isentia’s Prashant Saxena, VP of Revenue and Insights, SEA, during a recent partner event with IABC APAC on Why AI Visibility is the next reputation frontier illustrated a paywalled Bloomberg story, for example, that was accurately summarised details it could read at the top level, but fabricated details about raised guidance, even though guidance had been cut. This is because it could not read the rest of the article and tried its best to assume what it can with the information that’s accessible.
  • Specificity outweighs prestige. Tier 2, trade, and specialist publications are often more accessible, focused, and likely to provide the concrete, citable facts models need. Amy Chappell, Vuelio's Head of Insights Strategy, found a similar trend across sectors in her report on the visibility of supermarkets in the UK “ The role of AI, LLMs, and earned media in shaping reputation” and noted that supermarkets were most often cited by trade publications like The Grocer and Grocery Gazette, not national newspapers. Trade press stories, being more focused and well-sourced, provide models with clearer, more citable facts than broader national articles. This doesn’t mean that Tier 1 coverage does not matter — CEOs value front-page exposure because it remains highly influential. However, relying only on tier 1 hits now means missing significant AI visibility opportunities.

Cited vs consulted: LLMs read a hundred sources, but cite only a few

Which type of media gets cited relies upon how AI models scan different pages. If these models are citing much more niche media outlets, we can assume that a lot of these pages that are consulted could be a part of very relevant Tier 2 media that ends up actually getting cited, and that we’re seeing more and more examples of in AI answers.  At the IABC APAC and Isentia webinar on measuring brand visibility in AI answers, Prashant Saxena, Isentia's VP of Revenue and Insights for SEA, stated that in the search era "we would get sources on our page one, page two, mostly page one", and people would click through to form their own opinions. The combined click-through rate in that era was 35 to 40 per cent. Nowadays, he says, "it's just four to five per cent" — since LLMs provide a smooth, ready-made answer and "most of us aren't really checking the citations".

Communications teams now face a new consideration: the distinction between sources that are consulted and those that are cited. At the IABC APAC and Isentia webinar, Takeo Apitzsch, Hoffman Agency’s Chief Digital and AI Officer, explained that AI models scan hundreds of pages to generate an answer but cite only a select few to users. This means that the audience sees only a small, curated portion of the sources that actually influenced the AI's response and a lot of what actually shapes the AI answer doesn’t get visible credit. Therefore, organisations need to make sure they reach out to those publications that AI models can actually crawl and audiences trust the most. 

What does this mean for communications professionals?

We are seeing four practical shifts:

  • Rebuild your tier list based on what LLMs actually cite, not on internal assumptions. A so-called “low-priority” trade publication or niche forum may contribute more to your AI visibility than a national outlet you have long targeted.
  • Keep your reshuffled tier list fresh, not just correctly ranked. In Why is content freshness the new currency for AI visibility? we discuss that a page that hasn't been updated in eighteen months is far more likely to drop out of AI answers altogether, no matter how well it once performed. Getting the right tier 2 outlets on side is only half the job done. Feeding them (and your own owned channels) on an ongoing basis is the other half.
  • Treat consistency as an essential. The largest gap between an organisation’s claims and what an LLM will confidently state is often due to inconsistencies between owned content and third-party coverage. When this occurs, the model may stop providing factual answers altogether.
  • Shift your focus from share of voice to share of mind. It is now less about how much you are discussed and more about whether the systems mediating the most have got the correct information about your organisation.If the system holds the wrong version, your audience may never access the right one.

Structurally, as Ashley Knapp, Head of Brand and Corporate Affairs, East Asia at Schneider Electric noted during the webinar, these efforts can no longer remain siloed. Owned, earned, shared, and paid media have traditionally been managed by separate teams. Now, because of AI visibility, this required a unified approach, as models do not distinguish between departments but are first to detect inconsistencies. 

This also means reconsidering the PESO (paid, earned, shared and owned) strategy deployed by organisations since the way that LLMs access and prioritise them has changed. They prioritise brevity in content due to the high costs of GPUs and data centres. As a result, the shortest, clearest, and most trusted answers are favoured which benefits brands with strong reputations. Earned media remains important, but its influence now depends more on the credibility of the analyst than the platform. Shared content amplifies messages more than ever but is also where misinformation spreads fastest. Paid media is becoming more prominent in some models, though brands are still learning how this impacts visibility.

Media monitoring companies are becoming strategic AI visibility consultants

This shift requires media monitoring companies to evolve. Tracking mentions and sentiment across media channels has been central to media intelligence, but AI visibility has added a new dimension to this.  This means monitoring not only what is said about an organisation, but also which sources AI models use when answering questions about that organisation, and assessing how current, authoritative, and consistent those sources are. This gives media monitoring organisations an opportunity to own what they’ve developed and also be thought leaders in this space. Stakeholders value the “so what” advice much more than just knowing “this is what is being said about you in the media”.

Lumina AI View addresses this by tracking which sources ChatGPT, Gemini, Claude, and other models cite when representing an organisation, benchmarks citations against competitors, identifies narrative shifts before they reach stakeholders, and regularly scores AI visibility against four reputation pillars: Direction, Performance, Integrity, and Innovation, These pillars have always supported reputation management, now applied to a largely unseen audience.

If you're weighing up where a tool like this sits alongside the rest of your stack, our own comparison, Best AI Tools for PR & Comms Teams (2026), breaks down how AI-assisted coverage, measurement, crisis response and reporting tools stack up, Lumina included.

Because that’s really the mindset shift comms teams, and the firms advising them both need to make. As Takeo put it on the IABC APAC and Isentia webinar: “I fear that this is the mindset shift communications teams and their advisors must adopt. I fear that AIs will be your secondary, and if not, at least equal… audience in the future.” Beyond human visibility, reputation is about being accurately represented by the systems that mediate access to your audience, which is an additional layer that cannot be trivialised anymore. 


Want to see which sources are shaping how AI describes your organisation? Get in touch about Lumina AI View.

" ["post_title"]=> string(97) "How relevant is Tier 1 and Tier 2 media hierarchy in impacting how organisations show up in LLMs?" ["post_excerpt"]=> string(243) "The hierarchy that exists between Tier 1 & 2 publications today is being challenged. AI models are the new way audiences discover information requiring organisations to rethink how they show up to remain visible in an AI-mediated environment. " ["post_status"]=> string(7) "publish" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(4) "open" ["post_password"]=> string(0) "" ["post_name"]=> string(96) "how-relevant-is-tier-1-and-tier-2-media-hierarchy-in-impacting-how-organisations-show-up-in-llms" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2026-09-09 02:24:17" ["post_modified_gmt"]=> string(19) "2026-09-09 02:24:17" ["post_content_filtered"]=> string(0) "" ["post_parent"]=> int(0) ["guid"]=> string(32) "https://www.isentia.com/?p=49871" ["menu_order"]=> int(0) ["post_type"]=> string(4) "post" ["post_mime_type"]=> string(0) "" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" }
Blog
How relevant is Tier 1 and Tier 2 media hierarchy in impacting how organisations show up in LLMs?

The hierarchy that exists between Tier 1 & 2 publications today is being challenged. AI models are the new way audiences discover information requiring organisations to rethink how they show up to remain visible in an AI-mediated environment.

object(WP_Post)#12069 (24) { ["ID"]=> int(49595) ["post_author"]=> string(2) "75" ["post_date"]=> string(19) "2026-08-26 03:39:30" ["post_date_gmt"]=> string(19) "2026-08-26 03:39:30" ["post_content"]=> string(3210) "

Would you trust a brand more if an AI model recommended it? For many, the answer is yes – and it’s changing the very nature of PR & Comms.

Our latest report digs into the changing nature of trust, as audiences turn to AI models for quick answers instead of going to organisations or media outlets directly, with AI fast becoming the final stop in the comms cycle. 

This report unpacks:

  • Why trust has shifted, and where audiences are having these conversations
  • Why AI has become the last stop in the comms cycle
  • Methods for staying on top of your brand trust and reputation

To access the full report, fill in the form below:

Discover our Lumina AI suite here.


" ["post_title"]=> string(63) "How AI is destabilising trust and reputation amongst audiences?" ["post_excerpt"]=> string(144) "Learn how LLMs reshape brand perception and actionable steps organisations can take to maintain trust and reputation in the new information era." ["post_status"]=> string(7) "publish" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(4) "open" ["post_password"]=> string(0) "" ["post_name"]=> string(62) "how-ai-is-destabilising-trust-and-reputation-amongst-audiences" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2026-08-26 03:46:01" ["post_modified_gmt"]=> string(19) "2026-08-26 03:46:01" ["post_content_filtered"]=> string(0) "" ["post_parent"]=> int(0) ["guid"]=> string(32) "https://www.isentia.com/?p=49595" ["menu_order"]=> int(0) ["post_type"]=> string(4) "post" ["post_mime_type"]=> string(0) "" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" }
Blog
How AI is destabilising trust and reputation amongst audiences?

Learn how LLMs reshape brand perception and actionable steps organisations can take to maintain trust and reputation in the new information era.

Ready to get started?

Get in touch or request a demo.