COVID-19 outbreak highlights communications gap with multicultural communities
The surge in COVID-19 cases in South-western Sydney has brought to the fore the difficulties that government and private organisations have in communicating with multicultural communities. Not for the first time, in this period of rapid daily, and sometimes hourly change, non-English speaking communities have been left behind in conversations about restrictions, government support and health information. One of the many things that COVID-19 has highlighted is the importance of co-operation and a community-wide effort, and that requires effective communication. Too often we have failed to meet the challenge of communicating with multicultural communities – which comes at a cost for all of us.
Being a first-generation migrant myself, with non-English speaking Australian grandparents and growing up in a bilingual household I have seen firsthand the challenges of communication with Australian communities which originally came from other countries. I have seen my grandparents struggle with feelings of misrepresentation, a lack of awareness of government programs, an inability to keep up with current affairs.
My grandparents are deeply Australian, not in a stereotypical sense, but in the sense that they love this country. They regularly tell me how grateful they are to have been taken in when they needed a new start, how proud they are of their citizenship and Australia’s sporting, economic and other achievements, and how happy they are of the opportunities Australia has bestowed upon their children and grandchildren.
And despite this they cannot fully let go of their past. Love for one’s adopted home does not override the human instinct towards nostalgia, the acknowledgement and love of one’s roots, and certainly not the cultural influences, traditions and unique viewpoints of one’s home and history. My grandfather still loves Russian vodka (although he also developed a love of VB), my grandmother is still devout in her Russian orthodox faith, they still tell stories of the beauty of the Volga, and the superiority of produce straight from Moldovan farms. Yet both talk about Australian politics, think deeply about how they want to vote and cheered with equal vigour both the success of the Australian World Cup team in 2006 and the Russian UEFA European Championship team in 2008.
They naturally form a community with those who speak their language and share some part of their background and history. But this community is no less Australian because it is different than either someone from metropolitan Melbourne or remote rural Queensland. What makes us all Australian is not language or a set of stereotypical behaviours involving barbecues and TABs, or a love AFL or cricket, but a shared desire to see Australia succeed. The most recent census data in 2016 showed 21% of households spoke a language other than English at home. This is a huge market that is overlooked by English-only media monitoring and communications strategies. This market has very different needs and often viewpoints that are not met or reflected by English-language media coverage.
A recent report by the Labor Party on multicultural engagement provided first-hand accounts of people from multicultural communities struggling to access government services, understand government programs and navigate the difficulties of setting up a business. The Royal Australian College of General Practitioners (RACGP) worried about the communication to multicultural communities regarding telehealth services set up during the COVID-19 pandemic, and that these communities would delay meeting their health needs. The ACCC highlighted the fact that multicultural communities were likely to lose over twice as much money on individual scams and that these scams were tailored and targeted towards them.
The report also discussed the negative effects of English-language media communication about those communities, describing a story of a returning international student who had visited China during the Chinese New Year, just as COVID-19 was starting to spread. The Chinese-Australian community rallied together, encouraged the students to stay home and did their grocery shopping and other tasks for them to help them isolate, long before any official program was in place. There was a sense not only of a responsibility to the Australian community, but also that their community was under suspicion and being framed negatively in the media and they needed to work together to protect their image.
This story reveals something that is prevalent if one reviews the difference between multicultural media and mainstream media discussion of the same topics. Mainstream media too often talks about these communities, rather than to or within these communities. English-speaking media for many non-English speaking communities feels like reading international news to get information about Australia. It doesn’t understand their communities and doesn’t communicate with them, rather it too often largely communicates about them.
In culturally and linguistically diverse media one can find articles on how people might navigate loving the country of their birth and their adopted home at the same time during a period of heightened tensions between the two nations. Articles like these written directly within these communities, speaking to these communities, provide great insight into the difficulties these communities face.
There is significant work to be done by Australian companies and government departments to improve their outreach to culturally and linguistically diverse communities and a great opportunity to improve the efficiency of services and connect with a large swathe of the Australian population. For organisations, talking to communities that have felt underrepresented, misrepresented and misunderstood for so long, and trying to understand them through greater engagement with their in-language media can not only help access a wider range of the population, but build trust and credibility in an under-utilised space.
Government organisations are starting to understand this, the ACCC launched targeted campaigns to warn communities of specific scams targeting them. ASIC, in its 2019-2020 strategy for small businesses made specific mention of outreach to multicultural communities to help inform people of their role in assisting, engaging and helping to protect small business, while also helping them access the resources they need to improve their financial acumen. Meanwhile, the Victorian state government spent 7.8% of its media and campaign budget on multicultural media in 2019-2020, up from 3.5% ten years earlier.
There is momentum in this direction, and culturally and linguistically diverse focused communications strategies, media monitoring and analysis is hopefully one way that organisations can make that push to reach all sections of the Australian community.
Loren is an experienced marketing professional who translates data and insights using Isentia solutions into trends and research, bringing clients closer to the benefits of audience intelligence. Loren thrives on introducing the groundbreaking ways in which data and insights can help a brand or organisation, enabling them to exceed their strategic objectives and goals.
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. InWhy 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.
"
["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.
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: