Blog post
March 24, 2026

Answering your questions from the AI as a stakeholder webinar

AI has become a powerful stakeholder in its own right — from being just another ‘technological advancement’ to an active contributor to modern-day communications, that’s massively changed the media landscape today.

Isentia hosted an essential conversation with Lisa Main (Director, Main Bureau), Dr Nici Sweaney (Founder and Director, AI Her Way), Prashant Saxena (Isentia’s VP of Revenue and Insights, SEA), and Ngaire Crawford (Isentia’s Director of Insights, ANZ). Together, they explored how AI reshapes the world of communications and corporate affairs all the while figuring out how to manage and strategically engage with it.

In this session, we covered:

  • Understanding AI’s behaviour and influence as a digital stakeholder.
  • Navigating the unique challenges and opportunities AI presents as a new “audience.”
  • The long-term impact of AI and LLMs on the industries central to modern communicators.

Following the webinar, our panellists took the time to answer the most insightful questions from our attendees that we couldn’t get to during the live session. Here are their expert perspectives.

Ethical governance and human-centric adoption: perspectives from Dr Nici Sweaney

As the Founder and Director of AI Her Way, Dr Nici Sweaney advocates for a strategic approach to AI that prioritises human intent over technical capability. The questions directed to her focused on the ethical foundations of AI, how organisations should structure their internal AI strategy, and practical ways to start using agents today.

Q: Could you please shed a little light on what ethical AI in your language means?

Ethical AI, to me, is about two things working together: avoiding harm and actively doing good. It’s not just “don’t break anything” — but genuinely asking, does this create value for the business, for the people using it, and for the broader world? Transparency, equity, and accountability are the pillars. Transparency means being honest with your audience and colleagues about when AI is involved. Equity means asking who this helps and who it leaves behind, as AI scales existing biases. Finally, accountability means humans stay in the loop. AI should inform decisions, not make them. When the “why” is clear — like saving a team time to focus on strategy — you are using AI with integrity.

Q: Should AI adoption be owned by IT or Internal Communications? I see staff intranets being overtaken by AI and this has implications for how employees are communicated with.

My answer is probably not what IT wants to hear. AI is part of your infrastructure, so IT must be involved for security and guardrails. However, the strategy behind adoption is fundamentally a human problem, not a technical one. I advocate for a cross-functional “coalition” that brings IT, HR, communications, and strategy to the same table. If you create a dedicated AI leadership role, that person should sit closer to human-centric functions like HR and communications. The hardest part of adoption isn’t the technology; it’s the people, the culture, and the narrative you build around it internally.

Q: What are the most effective ways to address colleagues’ concerns about using AI agents in the workplace — particularly around trust, accuracy, and job security?

First, acknowledge that the fear is real; it is a biological response to an unprecedented rate of change. Trust is built through honesty. Pretending AI won’t displace roles destroys trust, so be honest about how the landscape is shifting. What actually moves people is showing, not telling. Show them how AI can solve their specific “pain points” — the tedious, joyless tasks that don’t add value. When people see AI as an “empowered choice” that uplifts their work rather than replacing their judgment and strategic thinking, buy-in follows. Build confidence with small wins first.

Q: What are some simple AI agents that you would recommend communications professionals experiment with setting up?

Most professionals don’t need complex autonomous agents yet; they need custom bots and automated workflows. The magic is in understanding your process first. Some practical starting points include:

  • Daily Briefings: A task that pulls from your calendar, email, and news to deliver a summary each morning.
  • Meeting Prep: Automated notes that pull context and past correspondence before a meeting, and transcription tools that turn recordings into action items afterwards.
  • Content Repurposing: A custom bot trained on your “voice” that can turn one talk or newsletter into 15+ social media assets and blog snippets.
Q: Our team members are using AI daily, but I know this is not safe as data is transferred back and forth. Should we create rules and ask people to sign IP protection?

Answer: Your instinct is right. If your team uses free consumer tools, your data may be used to train future models. You should move to enterprise-grade tools like Claude for Teams, Microsoft Copilot, or ChatGPT Enterprise, which offer contractual data protections. You should also build an AI Usage Policy that defines which data is public, internal, or restricted, and map AI rules to those classes. In Australia, we recommend aligning with the EU AI Act — the most comprehensive framework available — to future-proof your organisation.

Synthetic authenticity and the new media ecosystem: Perspectives from Prashant Saxena

Prashant Saxena, Isentia’s VP of Revenue and Insights for SEA, approaches AI through the lens of psychological bonding and media structural shifts. His insights address the changing role of media and the technical ways we must now communicate to satisfy AI as a new audience.

Q: Given that trust in media is dropping and media themselves are using AI more, what is the role or value media can have now?

Media’s value is shifting from being the “trusted narrator” for humans to being the “training signal” for AI. When AI models generate answers, they weight authoritative media sources much more heavily than random web content. Even as human trust erodes, media’s structural influence on AI-generated information is growing. For communicators, “earned media” now serves two audiences simultaneously: the humans who read it and the machines that learn from it. Publications with strong editorial standards become more valuable because AI systems use domain authority and editorial signals as quality proxies.

Q: How does AI rank or prioritise its sources and how do you see this shaping the earned media strategy for brands?

AI models don’t “rank” sources like Google does. They weight information based on source authority, recency, consistency, and structured data quality. If five credible outlets report the same fact, that fact becomes a “high-confidence training signal.” This means volume across credible sources matters more than a single “big hit.” For your strategy, consistency of messaging across all placements is vital because AI looks for corroboration. Factual, entity-rich statements will be picked up more reliably than narrative-heavy feature writing.

Q: With the question of trust — where does the psychology come into it when AI uses a cute nickname or ‘remembers’ your day? Is it harder to remain dispassionate?

This is the core of my PhD research. It is what I call “synthetic authenticity.” AI systems deploy cues like warmth and memory that we evolved to interpret as human. These trigger “parasocial bonding” — the same mechanism that makes you trust a friend’s recommendation. The danger is that cognitive awareness (knowing it’s AI) doesn’t override the emotional feeling. We need a new kind of literacy that teaches people to recognise when their “trust response” is being activated by design rather than by a genuine relationship.

Q: Should we be changing the format of communications to cater for AI as an audience, such as media releases in Q&A format?

Yes. This is a very practical move. AI models extract information more reliably from structured formats. A Q&A format gives the AI clear question-answer pairs that map to how people query systems. You should also focus on “AI-readable claims” — entity-rich, factual statements. Instead of saying “We are committed to sustainability,” say “Our Singapore operations reduced carbon emissions by 34% between 2023 and 2025.” The second version is a verifiable fact an AI can actually use and cite.

Q: PR professionals traditionally monitor media coverage through agencies like Isentia to gauge sentiment. With AI as a stakeholder, how do we monitor ‘its sentiment’?

This is the new frontier. Traditional monitoring tracks what humans publish; AI sentiment monitoring tracks what AI systems say about your brand when asked. Since there is no single “AI sentiment” (ChatGPT, Grok, and Claude all give different answers based on their training), you need to monitor across platforms. We are developing capabilities to systematically query these platforms to see how their narratives change over time and identify which source materials are driving those answers.

Q: Regarding ethics and agendas in AI learning — what are the differences between models like ChatGPT and Grok, and how does this affect our brand narrative?

Every model reflects the values, training data choices, and alignment decisions of its creators. ChatGPT (OpenAI) tends towards cautious, balanced responses with strong content guardrails. Conversely, Grok (xAI) was explicitly designed to be less filtered, sometimes surfacing perspectives that other models suppress. Claude (Anthropic) prioritises honesty and nuance. For communicators, this means your brand’s narrative varies by platform; you must monitor across multiple models because the same question about your brand will receive materially different answers depending on which tool is used.

Q: With many major news organisations blocking AI crawlers, how should we navigate content creation to ensure we still influence AI-generated answers?

Major publishers like the New York Times and Reuters have blocked AI crawlers, creating a gap in training data. When authoritative journalism is unavailable, AI models may fill that gap with lower-quality content or brand-owned content. For communicators, this means your “owned content” — such as your website, blog, and structured data — carries proportionally more weight in AI-generated answers. Your media targeting strategy now needs to account for which outlets are AI-accessible, as they will be disproportionately influential in shaping your narrative.

Analytical interrogation and the search for authority: Perspectives from Ngaire Crawford

Ngaire Crawford, Isentia’s Director of Insights for ANZ, emphasises the role of the analyst. Her approach is characterised by a “rhythm of interrogation,” arguing that the most effective way to use AI is through constant questioning and a focus on high-authority inputs.

Q: Is AI already part of your daily work or habit? If so, how are you using it and what are your best practices?

I was initially very sceptical, but it is now part of my every day. I use models like Claude and Gemini to workshop conference outlines, plan education programmes, update code, and structure strategic thinking. My best practice advice is to develop a “rhythm of interrogation.” Don’t just accept the first answer; ask for evidence and challenge the output. While AI saves time on technical tasks like coding, for strategic work it simply shifts the “mental load.” You spend the same amount of time, but the depth and quality are significantly improved because you aren’t starting from a blank page.

Q. PR professionals traditionally monitor media coverage through agencies like Isentia to guage what stakeholders think about a brand. How do we monitor ‘AI sentiment’ and the information that feeds these models?

It’s important to know that models are optimised to give the most useful answer, not necessarily the most accurate one. They are pattern-completing, not fact-checking. Because model responses are not fixed and change based on the conversation, I suggest focusing on the “controllable inputs” that feed them. This includes your own website, company material, Wikipedia data, and review sites (including employee reviews). Ensuring these bases are telling the intended story is the absolute best starting point for managing AI “sentiment.”

Q: How does AI prioritise its sources and how does this shape earned media strategy?

There is no “PageRank” to reverse-engineer here. Models are shaped by what was prominent and widely cited in their training data. Practically, this means a shift from volume to authority. A hundred pieces of low-quality coverage do less work than ten pieces in genuinely credible outlets (major mastheads, industry publications, or your own well-structured site). The question for the modern communicator isn’t “did we get coverage?”, it’s “does the coverage that exists, taken as a whole, tell a coherent and credible story?” AI reads the whole picture, not just the highlights reel.

Q: Now that OpenAI is opening up advertising, how much will it cost for a sentiment boost?

Honestly? We don’t know yet. The commercial layer of AI is being figured out in real time. The moment someone wonders if they are getting the “best” answer or a “sponsored” one, trust erodes. However, we still click Google ads, so it will likely happen. What’s important is that organisations that “earned” their reputation through authoritative presence before the ad market caught up will be in a much stronger position than those trying to buy a shortcut later.

The path forward for the modern communicator

The insights from our panellists make one thing clear: AI is no longer a tool of the future; it is a stakeholder of the present. To lead with credibility in this new era, communicators must pivot from chasing volume to building authority. Whether it is through adopting a rigorous ethical framework, optimising content for AI readability, or maintaining a “rhythm of interrogation” with the tools we use, the goal remains the same: ensuring our brand narratives are coherent, credible, and human-led.

The tools have finally caught up to the ambitions of our industry. Now, it is up to us to provide the architect’s blueprint for how they are used.


Interested in viewing the whole recording? Watch our webinar here.

Alternatively, contact our team to learn more insights into meaningful measurement, KPIs and communicating using the right dataset.

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Why PR and comms teams need to take LLM visibility seriously — and what to do about it

The next time a journalist, investor or potential customer wants to know about your organisation, it’s now increasingly likely they won’t Google you. They'll ask an AI.

They'll type a question into ChatGPT, Claude or Gemini, something like "Who are the leading renewable energy companies in Australia?" or "What's the best PR agency for healthcare in Singapore?" and the AI will give them an answer. The question is whether your own organisation shows up in that answer.

The implications are significant for communications professionals, whether they’re in the agency-side working with clients or in-house managing a brand. The rules of reputation and discovery are being rewritten, and there’s a new kind of playbook that we all need to adapt to. That’s what’s going to take us forward.

The shift no one saw coming, but perhaps should have

For decades, earned media has been the backbone of credibility. A strong piece in a respected outlet signalled trust, authority and relevance. This hasn't particularly changed, but the way that coverage gets used has.

Large language models (LLMs) are trained on vast amounts of publicly available content - news articles, company websites, industry reports, social media, expert commentary. When someone asks an AI a question, it synthesises all of that material into a single answer. If an organisation has a strong, consistent, well-sourced presence across those channels, it is more likely to show up. If it doesn't, it becomes invisible and is absent from the conversation entirely.

Gartner's latest predictions for Chief Communications Officers underline how serious this shift is. They forecast that as LLMs increasingly replace traditional search, PR and earned media budgets will double by 2027. What they say is that this is a communications challenge, one that requires PR expertise to build trust, secure quality coverage, and maintain consistent messaging across stakeholders.

Their research also predicts that by 2029, 45% of CCOs will be using narrative intelligence technologies to monitor reputation amid rising disinformation, a recognition that the old keyword-based approach to media monitoring simply can't keep up with the way stories now form, spread and multiply. 

The AI-generated content loop and why it matters

One of the less obvious risks in this new landscape is what happens when AI starts feeding on itself.

Catherine Arrow, Executive Director of the PR Knowledge Hub, raised this point during Isentia's recent Inside the AI Shift webinar. As she explained, "AI can identify and interpret some publicly available commentary. The difficulty is that we have to be careful about what it is actually reading. You can already see this in AI overviews where the system may refer to online discussion without digging deeply enough into whether the original sources are genuine, reliable or themselves AI-generated. So we end up with AI nested inside AI, nested inside AI."

That creates a real problem for anyone in communications. If the content landscape is increasingly populated by AI-generated material which is optimised to be found by algorithms rather than to inform real people, then the signals that LLMs rely on to build their answers become less trustworthy. Human judgement, original thinking and genuine expertise become harder for these systems to find, precisely because they're being drowned out by content that was designed to game them.

Catherine puts it simply, "People can become immune to this kind of content because it does not sound like the way we speak to each other, nor does it reflect the way genuine relationships are built. Then, when conflict or outrage is layered on top, the environment becomes even harder to interpret."

For PR and comms teams, it's not enough to produce more content. The right content needs to be produced, one that is original, expert-led, and well-placed in the channels and formats that LLMs are most likely to surface.

What this means in practice

So what does it actually look like to build LLM visibility into your communications strategy? It starts with the fundamentals, but applied with new intent:

  • Expert commentary placed in credible publications. 
  • Thought leadership that's genuinely distinctive, not a rehash of what everyone else is saying. 
  • Consistent messaging across channels. 
  • Media coverage that's authoritative enough for an AI system to treat it as a reliable source.

This is where the gap between media monitoring and media intelligence becomes critical. Monitoring tells you what's been said. Intelligence tells you how stories are forming, which perspectives are shaping them, and where your organisation sits within those narratives — including how AI systems are representing you.

Dr Nici Sweaney, Founder and Director of AI Her Way, made this distinction sharply during Isentia's AI as a New Stakeholder webinar. "What will set people apart, and what AI cannot replicate is the human lens. The judgment, the relationships, the institutional knowledge, the strategic read of a room. The organisations that lean into supporting their people to harness these tools, rather than just deploying the tools, will be the ones best placed.”

That's an important framing. The answer to AI disruption is to get clear on what only humans can do and then make sure the tools we’re using actually support that.

Staying credible when the noise is deafening

There's a temptation, when faced with a challenge like this, to throw more content at the problem – more posts, more articles, more releases. But Catherine Arrow points out the risks of that approach.

"Maintaining credibility and authenticity means being yourself and not allowing AI to suffocate your identity. That will become harder to do as digital twins, synthetic voices and other tools make it easier for organisations to use it as a mask. The real challenge is not so much maintaining credibility. It is about maintaining humanity, empathy, kindness and a genuine wish to connect with others beyond the AI-intermediated space.”

That advice matters just as much for organisations as it does for individuals. Brands that let AI do their thinking, generating bland, interchangeable content at scale, will find themselves blending into the noise rather than cutting through it. The brands that show up in LLM answers will be the ones with a clear, consistent, well-evidenced point of view.

Dr Nici Sweaney reinforced this from the operational side. "Ethical use is not about not using AI. It’s about using it with intention, honesty, and a clear sense of what good looks like on the other side.”
She was also direct about the risks of rushing in, "Don’t add new shiny AI projects on top of already overloaded teams. That creates resentment, not buy-in. Start by solving the problems people already have."

The cultural dimension

There's another layer to this that often gets overlooked and that’s the cultural one.

Catherine Arrow raised important concerns about how different AI systems can distort or flatten cultural context. Many of the most widely used models are shaped by US language, commercial assumptions and social norms. Chinese models operate within a different political and cultural framework. For organisations working across the Asia-Pacific region, it directly affects how the brand, messaging and the market are understood and represented by AI.

"Different AI systems may distort cultural context by privileging dominant languages, simplifying complex meanings, mistranslating concepts, omitting local histories or reproducing the worldview of their developers and training environments. They may flatten culture by making everything sound the same.”

For communicators operating across diverse markets, this means paying close attention to where content sits, who produced it, and whether the AI systems the audiences are using can actually interpret it with the nuance it deserves.

Where Isentia's platform fits with its new toolkit for AI visibility

This is precisely the challenge that Isentia's Lumina suite was built to address. Lumina is an intelligent suite of AI tools trained on the language, workflows and realities of modern public relations and communications, designed to empower, not replace, the human element of communications strategy.

Isentia's Lumina AI View feature will allow organisations to track how their brand, competitors and key topics are described by leading LLMs, with auditable claims, citations and transparency with regards to the sources. It's the difference between wondering whether AI is getting your story right and actually being able to see for yourself. These aren't generic AI features bolted onto a monitoring tool. They're intelligence systems built for the way communicators actually work.

The bottom line

The communications landscape has shifted. AI isn't just a tool the team might use, it's a stakeholder in its own right, actively shaping how an organisation is discovered, understood and evaluated.

For PR and comms professionals, the priorities are to ensure experts, commentary and evidence are placed widely enough for LLMs to find them and include them in their answers. Intelligence is imperative and required to how narratives are forming across both traditional media and AI platforms. All of this needs to be done without losing the human credibility that makes communications worth paying attention to in the first place.

As Dr Nici Sweaney put it, "The people who get the most from AI aren’t the ones who use the most tools, they’re the ones who understand their work deeply enough to know exactly where AI can add the most leverage."

That's the opportunity. The question is whether we’re set up to take it.


To explore how Isentia's Lumina suite can help your team navigate AI visibility, get in touch or discover Lumina.

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If AI can’t find you, neither can your stakeholders

We explore why LLM visibility should be a priority for PR and comms teams — and why harnessing AI, not just deploying it, is what matters.

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What 71 stories, 400+ perspectives, and 50 million audience impressions reveal about the media narratives shaping the 2026–27 Federal Budget.


The 2026–27 Federal Budget was released on 12 May and included some of the most ambitious policy changes in years. 

Labor Treasurer Jim Chalmers described it as a budget of ‘reform and resilience’, and the media coverage that followed reflected just how much there was to unpack.

We used Lumina, our AI-powered media intelligence suite, to surface the biggest stories, map different perspectives, and identify the key drivers behind each narrative. This clustered over 48 hours before and after the Budget into 71 different stories, more than 400 perspectives and the total audience reach topped 50 million cumulative views. 

Below are the five stories that stood out, what the different perspectives tell us, and what communicators should be watching out for.

Key stories at a glance

Property Tax Reform — Two evenly matched perspectives: affordability for buyers vs. reduced housing supply. Key drivers: Anthony Albanese, Jim Chalmers, Master Builders Australia, Property Council

The Policy Reversal — Government says circumstances changed; opposition says trust was broken. Key drivers: Angus Taylor, Bill Shorten, Peta Credlin, Sean Kelly

NDIS Changes — Sustainability concerns meet advocacy from families and disability organisations. Key drivers: Katy Gallagher, People with Disability Australia, ACOSS

Market Reaction — Investors moved ahead of the speech; banks fell, miners rose. Key drivers: BHP, CSL, DroneShield, Tony Sycamore (IG)

Small Business Support — Permanent write-off welcomed, but owners want more help with rising costs. Key drivers: Jim Chalmers, CPA Australia, Xero

Australia’s biggest property tax change in a generation

The centrepiece of this budget was a major overhaul of property investment tax. It was the most covered story of the night, and the perspectives on the announcement were split right down the middle.

The Government positioned the reforms as a step toward fairness. Negative gearing will be restricted to newly built properties from July 2027, and the 50% CGT discount will be replaced with an inflation-indexed model. 

Furthermore, a 30% minimum tax will now apply to distributions from discretionary trusts. Treasurer Jim Chalmers and Prime Minister Anthony Albanese reiterated that these changes will aid a projected 75,000 Australians to buy their first home over the next decade. This perspective accounted for about 50% of coverage across the story (ABC Online).

Industry groups like the Master Builders Australia and the Property Council warned the changes would reduce new housing supply by 35,000 homes, push up rents, and discourage investment. 

These perspectives made up approximately 50% of total coverage. That near-perfect split is notable. In most policy debates, one side tends to lead in terms of coverage, yet here, the two perspectives are running neck and neck 

That balance tells us the debate around these reforms is far from settled. Neither side has won the narrative.

Why it matters for communicators: This is going to be a long-running conversation. Both sides have credible data. If your organisation has a stake in property, construction, or financial services, now is the time to develop your position and prepare for sustained engagement.

The policy reversal and what it means for trust

Behind that policy detail, however, was a more political story. The government had made promises before the 2025 election that it would not change negative gearing or CGT. This budget announcement made changes to both policies, and the coverage explored what that means.

The Government’s explanation around the changes took up about 43% of coverage. Previous Labor Minister and now Vice-Chancellor of the University of Canberra, Bill Shorten argued that the housing situation had worsened since the election ,and the government had a responsibility to act. Unsurprisingly, Prime Minister Anthony Albanese held the same position. In his interviews, Shorten pointed to the earlier redesign of the stage three tax cuts as an example of a policy change that voters ultimately accepted.

Political commentators offered an analytical view, making up about 40% of coverage. Former Labor adviser Sean Kelly and others noted that the fallout from changing a position depends on context, and that history offers examples of both successful and costly reversals.

The opposition’s framing accounted for about 18% of coverage so far, as we wait for their formal response to the Budget next week. Liberal leader Angus Taylor and his colleague Michaelia Cash described the move as a trust issue. A leaked government document giving Labor MPs talking points to explain the change added another dimension to the story (The Australian).

Why it matters for communicators: Past commitments stay in the public record. For communicators working on policy-related messaging, it’s worth thinking about how your stakeholders weigh trust against outcomes, especially as this story continues to develop.

NDIS changes spark a deeply personal conversation

The NDIS story stood out in Budget coverage for a different reason. It was one of the most emotionally resonant conversations of the night.

The government framed its changes as essential for the scheme’s long-term sustainability, and this perspective made up about 58% of coverage. Ministers pointed to cost growth and fraud as reasons to tighten eligibility, with the Fraud Fusion Taskforce positioned as the mechanism to protect genuine participants while saving $37.8 billion over four years (Sydney Morning Herald).

Disability advocacy groups responded with concern, accounting for about 42% of coverage. Organisations like People with Disability Australia highlighted that over 160,000 participants could be affected, many of them children. 

The Australian Council of Social Services (ACOSS) noted the budget also lacked additional support for people on income support. By budget night, advocacy groups had organised a press conference and gathered more than 13,000 petition signatures. This was a story where the personal weight of the coverage mattered more than the volume. 

Why it matters for communicators: Personal stories and advocacy will shape this conversation more than policy. If you work in health, disability, or social services, this is one to monitor closely and maintain the human element in the approach.

The market moved before the speech

One of the more interesting stories of budget day was how the share market reacted before the Treasurer even stood up to speak.

The ASX 200 fell across the day. Banks were under pressure because of their exposure to residential mortgages, with analysts pointing to the risk of falling property prices if the tax reforms reduced investor demand. 

Rising oil prices from the Middle East added to the mood (NEWS.com.au). And earlier in the week, Australian stock market stalwart CSL dropped over 16% on a separate profit warning, dragging the healthcare sector with it.

But mining stocks went in the opposite direction, with BHP hitting a record high on strong commodity prices for copper and iron ore. Different parts of the economy were reading the same budget in very different ways.

Why it matters for communicators: When investors move before an announcement, it tells you the narrative is already established. For organisations with listed exposure or investor-facing communications, the property reform story is one to address proactively.

Small business: welcome news, but not the whole answer

Making the $20,000 instant asset write-off permanent was a positive headline, but the coverage revealed a gap between the announcement and business owners’ lived experience.

The government’s framing dominated, making up about 75% of coverage. The write-off sat alongside a broader $3.5 billion tax relief package, which Treasurer Chalmers called part of the most comprehensive productivity push in decades.

But the remaining quarter of coverage tells a different story. Xero research showed only 35% of small businesses were confident the budget would address their challenges. Many described the $20,000 threshold as too low for the investments they actually need to make, especially given rising fuel and material costs. 

The broader sense was that while the write-off is helpful, it doesn’t change the fundamentals of a tough operating environment.

Why it matters for communicators: Headline announcements and on-the-ground sentiment don’t always match. For industry groups and advocacy organisations, grounding your messaging in real-world experience will resonate more than repeating the numbers.

Looking at the budget through comms: what does it mean for strategy and messaging?

There are two factors that emerge as key considerations.

First, the property tax conversation is set to continue for the months ahead. Both sides have credible arguments and strong stakeholder backing; these sentiments will undoubtedly be reinforced by the Opposition next week. If your organisation is connected to housing, property, or financial services in any way, a long-term narrative strategy will serve you better than a one-off reaction.

Second, keeping an eye out for how the election reversal narrative evolves is important. It will become a reference point for future government commitments. For anyone working on government-related messaging, it’s worth considering how your audiences balance trust with outcomes. Media outlets are actively searching for inconsistencies – as are social media users – so any change must be clearly explained and a credible narrative developed.

How budget perspectives shape the media landscape

The 2026-27 Federal Budget was a budget that asked big questions and looked to a new future. The media coverage showed a public working through what these changes mean, with perspectives spread evenly across the biggest stories of the night.

For communicators, the value is in looking beyond the headlines. Understanding the different perspectives, the people and organisations driving them, and the patterns connecting them is what turns a reactive media response into a strategic one.

To explore these kinds of insights for your own industry, discover what Lumina can surface for you. For more insights from the Isentia team, fill in the form below and we’ll get in touch.


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The latest stories and perspectives from a budget that broke the rules

The 2026 Federal Budget has landed, and what PR and comms professionals need to observe is how the media conversation has split into dozens of competing narratives depending on who’s telling the story.

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