What an interesting year! I’m not sure how many end of year wraps are going to start that way, but it’s the best way I can think to open up on what I’ve seen this year. For me, 2020 was the year that the core principles of a good communicator became clear to see. It’s rare that you get to experience the same event across the world and compare and contrast different approaches and their effectiveness.
Last week we hosted our final webinar of the year with a panel of media experts across Australia and New Zealand, and it gave me the chance to reflect on what 2021 might look like. Rather than a trend list I thought I would outline some key themes that will continue into 2021.
Listening:
During 2020, call out culture continued to grow while everyone was in their homes and consuming more information. Online social movements have “cancelled” celebrities, influencers and brands due to behaviour or values that don’t reflect those of their key online audiences. On the other side of this, there was also an increase in divisive rhetoric, conspiracy theories and misinformation. As a communicator, it’s crucial to not be singular in the type of information you consume and to consider if you are across new platforms, different audiences and opposing points of view in your own media consumption.
Crisis: Respond and Adapt with Clarity, Compassion and Creativity:
I have always believed and advised that leading with compassion and transparency promotes authentic communication, which I know is a point most communicators agree with, just sometimes it can be hard to convince stakeholders of that same point of view. It’s always clear in crisis who has a bank of trust to draw on and who doesn’t, and when you couple this with some audiences growing increasingly wary of governments and media, it’s important that the trust is built and maintained consistently outside of a crisis.
During the crisis itself, we’ve seen the need to be incredibly clear and transparent this year. Public health information can be complex and needs to be translated and applied to a wide audience, in the languages and formats that work best for those audiences rather than the communicator. Governments have created new frameworks that have become vernacular, and I know I know way more about viruses and immunology than I ever thought I would.
The Year of the experts:
I have directly taken this idea from Patrick Crewdson, the editor in chief at Stuff (you can listen to this here) At the beginning of the year I would have struggled to name the Chief Medical Officers of major countries in the world, this week I made a team quiz questions about them, and have put an image of t-shirts with the face of Dr Ashley Bloomfield (Director General of Health in New Zealand) on them in a number of presentations this year. I think this illustrates a sentiment that has existed for journalists for years: as communications structures have expanded, they want access, and they want to hear directly from experts. Audiences have echoed this in 2020 through high viewership of entire press conferences and live streams from public officials. Creating a supportive communications environment that can allow experts to be heard and embrace their role in the media can take work, and a bit of evidence and training (especially in a raw and unfiltered media environment), but I hope it continues into 2021 – it only helps to build trust and transparency.
This is just scratching the surface of what was quite a year, and one I’m sure we all won’t forget anytime soon. In spite of what was a tough year for many, it’s pleasing that communications has been given an opportunity to prove the value on a broad scale.
I want to sign off with some holiday reading and resources (because there’s nothing quite like some measurement reading on the beach!)
AMEC (International Association for the Measurement and Evaluation of Communication) hosts a month of great content and events on communications measurement each November and it’s the chance to hear from experts all around the world. This content is all available virtually and on-demand here: https://amecorg.com/measurement-month/2020-mm-events/
There’s something relevant here for everyone, from influencers and google studio to those just trying to get their head around research and evaluation. If beach homework isn’t your thing, bookmark the site and come back to it with fresh eyes in January.
Ngaire Crawford leads Insights and Research at Isentia, driving innovation in measurement strategy and product development across the Pulsar group. With nearly two decades of experience in communications research, she champions the power of insight to tell richer stories, shape smarter decisions, and prove the true value of communications. A passionate advocate for meaningful data and inclusive storytelling, Ngaire believes great measurement doesn’t just report impact, it creates it.
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.
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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:
