Answering your questions from the AI as a stakeholder webinar

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.

Nikita Gundala

Content Marketing Executive, APAC

Nikita Gundala manages brand marketing and thought leadership for Pulsar Group across the SEA and ANZ markets. With over three years of first-hand experience in the influencer marketing and PR industries, she specializes in translating real-time insights and audience intelligence into actionable content. Nikita holds a master’s in Marketing and Digital from ESSEC Business School, Singapore. She has contributed to the wider industry conversation by co-authoring articles and reports for The Business Times Marketing Interactive.

Key Stories, Key Drivers

Here’s a quick overview:

▸ Campus Antisemitism at the Royal Commission — Pro-Palestinian groups, Jewish advocacy groups, and the federal government each put a different framing on the same hearings. Key drivers: Nasser Mashni, Yasmine Johnson, the Australian Union of Jewish Students, Jason Clare, TEQSA.

▸ The Labor–Greens Tax Deal — Government and Greens call it fairness for first-home buyers; finance and business groups call it policy on the run. Key drivers: Jim Chalmers, Nick McKim, the Self-Managed Super Fund Association, the Australian Chamber of Commerce and Industry.

▸ Pauline Hanson's Monoculture Speech — A push for cultural unity that critics called divisive, followed by a real slide in the polls. Key drivers: Pauline Hanson, Paul Hogan, Murray Watt, Newspoll, Redbridge.

The Royal Commission on campus anti-semitism

The Royal Commission on Antisemitism and Social Cohesion’s hearings on university campuses was the biggest story by far. In less than a week, it drew 33 perspectives and 453 media items, reaching over 628k audiences. The story’s size came from the many institutions involved—student groups, representative bodies, and the federal government—each offering their own view on the same testimony.

Pro-Palestinian advocacy groups had the widest reach, making up about a third of all coverage. Spokespeople like Yasmine Johnson from Students for Palestine and Nasser Mashni from the Australia Palestine Advocacy Network told the commission their campus protests are a legitimate justice movement. They also raised concerns that criticism of government policy is being confused with antisemitism, which they say limits open debate.

Jewish student and staff groups also received significant coverage, making up about a fifth of the total. The Australian Union of Jewish Students described campuses where some students feel hesitant to attend and highlighted gaps in how universities handle complaints and support those affected. Most of this coverage came from wire services and was widely shared across news outlets like The Australian or the Midwest Times.

The federal government provided a third perspective, with similar coverage. Education Minister Jason Clare said universities had been slow to act and announced plans to tighten governance standards. This includes clearer anti-racism policies covering both antisemitism and Islamophobia. Reports also noted that TEQSA, the regulator, warned universities about outside groups joining campus protests, and the government’s antisemitism envoy suggested universities could face funding cuts if they do not do enough.

The Labor-Greens Tax Deal

The second-biggest story was more focused but still managed to stir strong reactions. Labor’s deal with the Greens to close a borrowing loophole for self-managed super funds, in return for Greens support on capital gains tax and negative gearing changes, led to 22 perspectives and 232 media items, reaching nearly 177k audiences.

The government, supported by the Greens, presented the deal simply — it closed a loophole that allowed wealthy investors to use their super funds to compete with first-home buyers at auctions. Treasurer Jim Chalmers cited a 2014 recommendation to support the change, and Greens treasury spokesman Nick McKim called it a win against "wealthy property investors."

The Greens, however, took a tougher stance and received similar coverage for saying the deal was only a partial win. They argued that allowing existing arrangements to continue would let Labour protect wealthy investors rather than renters, and said the housing crisis would now be "squarely of Labor's design." This shows that support from a governing partner does not always mean they are satisfied, as Country News highlighted.

Finance and business groups pushed back with nearly as much coverage. The Self-Managed Super Fund Association and the Australian Finance Industry Association said the borrowing rules did not pose a systemic risk and argued that regulators should focus on "aggressive marketing" and property spruiking, not legitimate investors. The Australian Chamber of Commerce and Industry warned that the wider capital gains tax changes could hurt business investment. ABC News gave the most detailed account of this perspective, noting the sector was "surprised" by how the deal was made.

Pauline Hanson’s monoculture speech

This story had the fewest perspectives (just seven) but still reached nearly 236k people through 210 media items. That’s a bigger audience than the tax story, which had three times as many viewpoints.

The story began when Pauline Hanson used a National Press Club speech to argue that Australia should replace multiculturalism with a single "monoculture." She cited Paul Hogan and the Socceroos as examples. The backlash was quick and unexpected and Hogan himself called her a "pelican" and said her views were racist. His response ended up shaping the story more than her monoculture speech.

What makes this story notable is what happened afterward. Two polls, Newspoll and Redbridge, showed One Nation’s primary vote dropping by about two points (Dairy News Australia) and Hanson’s personal approval falling ten points into negative territory. Labor regained a narrow lead and Labor minister Murray Watt quickly described the numbers as a "reality check,". This framing spread almost as widely as the original speech, as the Bendigo Advertiser reported.

The speech and the poll results are really one story seen from three sides — Hanson’s message, her critics’ reactions, and Labor’s use of the polling. Each angle received similar coverage, showing that the speech missed its mark and gave the government a useful talking point.

How does this inform PR & Comms Strategy?

First, the number of perspectives in a story is important. A story with many viewpoints, like the antisemitism hearings, needs a different monitoring approach than one with just a few, because the loudest voices might not always be the most important.

Second, pay attention when several perspectives are about the same size, as in the tax deal. If no single viewpoint stands out, the issue is likely still being debated. It’s a good idea to check back after some time instead of treating the first coverage as the final answer.

Third, compare any polarising message to the Hanson example before recommending it to a client. The numbers show that a divisive message can get attention but still turn public opinion against the speaker.

Conclusion

What links these stories is how much is lost when they are reduced to just two sides. The antisemitism hearings, the tax deal, and Hanson’s polling drop were all more complex than their main headlines suggested.

That’s why it’s valuable to track a story by its different perspectives and key drivers. See what Lumina can reveal for your industry or clients, and check out more analysis like this on the Isentia blog.

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Who really shaped Australia’s latest social cohesion debates?

See how Isentia’s Lumina tracked 62 perspectives across 3 major Australian stories, revealing how media coverage really spreads and who ends up controlling the narrative.

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There is a new frontier where public perception is shaped: Large Language Models. Right now, LLMs are answering critical questions about your organisation. What are they saying? And more importantly, which sources are shaping those answers?

To navigate this landscape, public relations professionals don't need generic tools, but rather technology that speaks their language, and addresses the realities of a changed media and informational landscape.

That is why we're unveiling Lumina AI View, the latest addition to our intelligent suite of AI tools from Isentia. Trained specifically on the workflows and challenges of modern PR & communications, Lumina AI View helps you understand exactly what AI knows about you, and how it learned it.

A new standard for AI visibility

AI View tracks your citation strength and source quality alongside those of your competitors, giving you a clear view of where you hold authority and where you have gaps.

Lumina AI View maps your AI reputation from the ground up, allowing you to:

See which sources matter: When tools such as ChatGPT or Gemini discuss your organisation, which outlets do they cite? Track your source footprint over time and view the impact of key target media on how you’re discussed. We measure your citation strength and source quality alongside those of competitors, giving you a clear view of where you have authority and where you have gaps.
Gain industry-specific insight: Your competitors get cited from Financial Times and Bloomberg. You get cited on Reddit. Each brings opportunity – and risk. Discover how you measure up against industry standards, and target the sources that actually influence how AI represents you.
Catch narrative shifts early: AI responses change when new sources appear, sentiment shifts, or old controversies resurface. Get alerts when citation patterns change suddenly, before they impact the way you’re perceived by stakeholders.

Measure your progress: From media monitoring to full media intelligence

Lumina AI View is built on the principle that insights get stronger with repeated measurement. To help you maintain a clear view of your reputation, our proprietary scoring system provides regular updates that show you:

Evolving trends in how sources cite your organisation
Competitive standing and benchmark metrics
Where models differ in information presented, and sources cited

Whether you run it weekly, on-demand, or whenever you need a check-in, patterns will emerge, trends will become clear, and you will build a baseline that makes any sudden narrative changes both comprehensible and the prerequisite to action.

Lumina AI View is part of Lumina AI, a comprehensive suite of AI tools built specifically for communicators. Our Lumina suite evolves traditional media monitoring into narrative intelligence, enabling you to truly understand how perceptions form, evolve, and impact your reputation.

Get in touch to register your interest and see what Lumina AI View can do for you.

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Blog

Introducing Lumina AI View: AI Visibility Built for PR & Comms

Lumina AI View, the latest in Isentia’s AI suite, is trained on PR & comms workflows to help you understand what AI knows about you — and how it learned it.

Ready to get started?

Get in touch or request a demo.

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