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We spoke at Marketing Interactive's PR Asia 2025 recently in Singapore around authenticity, trust and how these are at a strain, specifically in this new AI-powered world. We were amongst top leaders in the PR industry who touched upon how crisis and reputational threats need to be dealt with authentically. Most importantly, companies must be ready for any kind of crisis communications to be activated with statements from senior leadership, without a sense of "doing everything reactively", i.e., the logistics need to be in place so that teams have enough time to be responsive rather that reactive.

Audience perceptions of AI: do we know what's real?

Russ Horell, Chief Revenue Officer, APAC touched upon a few cases that set the tone around how audiences have not been able to clearly identify which online content is real and have ridden the wave until someone figures it out. The two main examples that were touched upon were around how Mia Zelu, a virtual influencer on Instagram became the face of Wimbledon this year, until everyone realised she's not real.

The other case was around former Astronomer CEO Andy Byron's fake statement that was circulated - although not AI, it gives us an insight into how trust in CEOs is at an all time low, with this incident taking it further underground. In this world of fakes, audiences have given up on trying to decide what's real. This needs to be urgently addressed by PR leaders when it comes to brand communications, especially during a crisis.

Our CEO for Pulsar Group, Joanna Arnold was in attendance of the speaking session and at our booth to support and motivate as always. This gave us an extra level of confidence to interact with the visitors at the booth and to speak with them about who we are, what we do and more insight into our content.

Assigning cues to audience reactions

With all this in mind, we wanted to understand how leaders, specifically PR leaders can own their content strategy and decision making when it comes to responding effectively.We analysed posts by top executives and c-suite leaders on LinkedIn and audience behaviour to those posts. We then assigned cues - cues that identify which post is the most authentic in terms of cultural relevance, identity, tone & style, trust, information accuracy etc. Prashant Saxena, Vice President, Revenue & Insights, SEA expanded upon how these cues can be utilised to increase engagement 3-fold. This transforms authenticity from subjective performance into an executable framework that any leader can deploy. The pattern is clear, and posts with multiple authenticity cues consistently outperform those relying on tone alone.

Booth interactions

Jenna Wang, Business Development Director and Christian Chan, Business Development Manager for Isentia, Singapore were having engaging and insightful discussions with attendees, considering the topic at hand is an important one with an almost "what to do" playbook that leaders can use effectively in their communications. We knew many would be keen on understanding and wanting to know more as a follow up to the speaking session. Nikita Gundala, SEA Marketing Lead, managed the content and the logistics around the booth display along with timely updates on our social media.

We had a wonderful experience at PR Asia this year and we look forward to being a part of (and hosting) more such events where we can bring together industry leaders to understand how they navigate new challenges and what can be done about them.

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Interested in learning more? Email us at info@isentia.com

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A World Of Information Without Noise 

Big data is more than just a buzzword. It’s one of the biggest challenges and opportunities facing almost every industry, business and brand today. With the potential value that it holds, investment in big data, machine learning and AI will be crucial for any business that wants to remain relevant through the ages.

Big Data

noun : extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.

Each day 2.5 quintillion bytes of data is generated – a number that continues to grow exponentially. While we have seen improvements in the collection of data over recent years, the ability to synthesize meaning from this data is demanding more from engineers and their technology than ever before.

The problem that we face is sorting through these huge chunks of data to separate the noise from what is important to individuals and their organisation. While automation has offered speed, simplicity and efficiency, the ‘why’ is where the untapped value and excitement lies.

“Contextualisation is key. It's not about just collecting data, it’s about how that data can provide clear information that enables and inspires action”

Richard Spencer, Chief Marketing Officer at Isentia.

Rather than reflecting on past performance, answering the ‘why’ has the potential to lead action that focuses on influencing the tomorrow.
Beyond big data, the 'why' behind AI and machine learning may raise new questions. For instance the wider interplay behind machine learnings ability to  translate to a language without any knowledge or assumptions about that language.

As teams start to ask these questions, the data starts to be reimagined. The perception of a data point transforms into breadcrumbs of a narrative that can tell a bigger story, and ultimately influence our thinking.

The question is, when big data becomes manageable and meaningful – how fast will it move into being predictive? And even beyond this, be able to simulate what is ‘likely’ to happen.

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It’s official: artificial intelligence has arrived. But how will this disruptive technology transform businesses in the near future?

After more than a few false starts, artificial intelligence (AI) is finally here, and it’s powerfully disrupting the way business is done. We don’t need to ask if or when businesses will adopt AI – the question is where and how widely it will be employed.

AI is already a big player in the technology industry. In particular, there is a growing use of AI in IT’s backroom functions like cybersecurity and tech support. A Tata Consultancy Services (TCS) survey of 835 company executives found that nearly half of respondents were using AI to detect and fend off intrusions – the most frequent use of the technology. But a number of other industries are also opting for AI.

Early adopters

In entertainment, companies like Netflix and Amazon are using machine learning to help their movie recommendation engines. Health care has seen myriad applications, including virtual assistants for doctors, apps that can interpret test results and even AI-based spine surgery technology. In the financial sector, AI has been put to work in regulatory compliance and fraud prevention – PayPal uses a combination of its own AI program and human analysts to combat fraud, for example, and HSBC has teamed up with Silicon Valley startup Ayasdi to automate anti-money-laundering investigations.

Worldwide spending on cognitive and AI systems is expected to reach $12.5 billion this year, according to IDC, a whopping increase of 59.3 percent over 2016. Much of this growth is powered by use cases like the examples above. But there’s another area where AI is rapidly being adopted: automated customer service agents, or chatbots as they’re more commonly known.

Customers now expect AI to be used by companies and they are comfortable interacting with the technology (up to a point). Research from HubSpot found that nearly half of people are happy with the idea of buying products from a chatbot. Perhaps more importantly, 40 percent of respondents said they were indifferent about receiving customer support from either a chatbot or human – provided they got the help they needed fast and easily.

Dealing with data

Whether patrolling a computer network for intrusions or trawling through financials for signs of fraud, AI is most often employed to intelligently handle vast amounts of data quickly. “AI is best deployed in companies with significant amounts of data and robust data systems,” says Andrea Walsh, Isentia’s CIO.

Gartner predicts that, in 2018, half a billion users will save two hours a day as a result of AI-powered tools. Every time a business gains efficiencies, it saves money – and that is AI’s chief benefit.

AI’s smarter processing power is also helping companies generate more quality leads on new customers, using IBM’s Watson AI, for example. Finding, contacting and closing new sales is a time and resource-heavy activity. But AI-based sales assistants can tirelessly work on reaching out to people, while intelligently analyzing data on leads. This can then be effectively communicated with point-of-sale staff.

When employees hear the word “efficiency,” they often assume it will lead to lay-offs. While there is no question that some jobs will be replaced by AI programs, the naysayers are largely exaggerating their mass-redundancy predictions.

AI is a data-cruncher, and it is often employed to take care of something that didn’t even exist 30 years ago: big data. When it accomplishes its analysis, a human is still needed to interpret the results, such as in cybersecurity and anti-fraud scenarios. Even in the case of customer service chatbots, these will mostly be applied to routine queries and simple support functions, augmented by human representatives for complex problems. “AI should not stand alone as a technology,” say Walsh.

Enhancing existing infrastructure

As with all industrial revolutions, AI will create jobs even as it replaces them. There are already glaring shortfalls in STEM-trained employees across the world, and that’s likely to continue as the rapid pace of technological transformation outruns educational reforms. But eventually, new generations will be trained and educated to do jobs created by innovative technologies like AI.

Any business can benefit from AI programs, but when it comes to how broadly they adopt AI, companies need to look at how the technology can augment their existing capabilities. Instead of replacing staff, current AI should be used to support them and put their invaluable human minds to the best use, saving tedious, data-crunching work for the machines. For customers, AI needs to be a helpful, timesaving addition to their experience, and companies should never try to create the false impression that a human is doing the work. People are ready for AI; companies need to be too.

Andrea Walsh, Isentia's Chief Information Officer

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A weekly tracker tracing the stories, figures and policies driving media and social coverage in the 2026 New Zealand General Election across TV, Radio, Newspaper, Magazine, X, Facebook, Instagram, TikTok, Threads and Forums. This edition covers conversations and coverage from 28th October - 3rd November 2026, highlighting what’s shaping the election conversation.

1. Election Conversation

Media = news coverage. Social = all public posts across X, Facebook, Instagram, TikTok, Threads and Forums - everyone posting, not just media outlets.

2. Media Issue of the Week

Vote Splitting Divides the Centre-Right in the Final Week

The argument took off after an RNZ-Reid Research poll put National below a quarter of the party vote. Former National and ACT leader Don Brash then ran advertisements in the Herald telling National supporters to give their party vote to ACT or NZ First instead. The reasoning was that National was expected to win more electorate seats than its party vote entitled it to, so extra party votes for National would not add any MPs. That situation is known as an overhang.

ACT and NZ First both confirmed they had approved the ads, and businessman Harry Mowbray ran a separate "Split Your Vote" website with a similar message. National complained to the Electoral Commission about the website, which was taken down and then put back up with changes. Christopher Luxon criticised his coalition partners' involvement and warned that a party vote for anyone but National risked a Labour-led government. Winston Peters defended splitting the vote as a normal part of how MMP works, and Labour said the row showed division on the right. Te Pāti Māori is taking a similar approach on the left, asking supporters to focus on the electorate vote.

This was one of the biggest political stories of the week. About one in eleven election items in the news covered it in the headline or summary, and many more discussed it further down the article. Coverage started on 29 October and stayed strong through the weekend, with newspaper and TV coverage highest on 2 and 3 November. It matters because it put the voting rules and the relationship between the coalition partners at the centre of the final week, when parties would normally be making their closing policy pitches.

On social media it was a smaller part of the conversation, and the tone was mixed rather than angry. Many posts explained how an overhang works, urged supporters to split their vote or replied directly to Luxon, and the share of negative posts was a little below the weekly average. Because it is about how to vote and not about a policy, it is not linked to a party issue below.

3. What's happening across media and social?

Share of each channel's own conversation, so the two bars are directly comparable

"Social" is all public posts across X, Facebook, Instagram, TikTok, Threads and Forums - not just media organisations' own accounts.

Most frequent presenters and newspapers: The most frequent presenters this week were Dale Husband (Waatea), Sean Plunket (The Platform), Ryan Bridge (Three) and Chris Chang and Tova O'Brien (TVNZ 1). Among newspapers, Otago Daily Times, New Zealand Herald and Daily Post ran the most election coverage.

Widest-reach accounts: Among the accounts that posted most often about the election, those with the widest reach were the New Zealand Herald, RNZ, Chris Lynch Media and the Taxpayers' Union. Parties' and leaders' own accounts are not included.

The issue agenda was very similar in the news and on social media. Cost of living came first, followed by the economy, health and law and order, in the same order on both sides. Cost of living took a somewhat bigger share of social conversation than of news coverage. Law and order has dropped to fourth now that the gang photo row that kept it at the top last week has faded.

The mix of parties differed more. National and NZ First took the biggest shares of social conversation, while National and Labour took the biggest shares of news coverage. NZ First was much more visible on social media, where many posts were about giving a party vote to NZ First or splitting the vote. The Greens had a similar share on both sides.

4. Party Share of Conversation

Shown for seven parties. Te Pāti Māori and the Opportunity Party (TOP) are included because both featured in the week's polling and vote-splitting coverage. Shares add up to 100% of the seven shown. Share of conversation measures attention, not polling, and is not a sign of electoral success.

5. Top candidates this week

Share of mentions among the five candidates shown

Christopher Luxon led the field, mainly because of the vote-splitting row and the poll showing National under pressure. He criticised ACT and NZ First for their part in the ads, brought in former prime minister John Key to campaign for the party, and said the finance portfolio would stay with National.

Winston Peters came second, with a slightly bigger share of social conversation than of news, after defending vote splitting. Chris Hipkins was more prominent in the news than on social media, helped by Labour's manifesto launch and his comments on the divisions on the right.

Chloe Swarbrick featured for the Greens' wealth tax and for her response to National's attack advertisements. David Seymour featured for ACT's part in the vote-splitting ads, the contest in Epsom and speculation about whether he could become finance minister. Mentions measure how much someone is being talked about, not how they are polling.

6. Election Issues

Top 4 themes this week

Share of mentions among the four themes shown

What's driving conversation about each party?

Each party's top issues this week in social conversation, ranked by how much they were discussed

Issues are ranked from social posts. Counts are not shown because the numbers for a single party and issue are small.

7. Issues to Watch

1. The vote-splitting argument is likely to continue until election day. National is still asking supporters to give both votes to National, while ACT and NZ First have defended their position. How much it affects party votes may only be clear once the results come in, and it could then shape the talk about overhang seats and coalition negotiations.
2. Changes to the enrolment rules are another live issue. People can no longer enrol once early voting has opened. There are questions about how many people who are not enrolled will turn up to vote and how many special votes will need to be counted. Those questions are likely to return when the results are announced.
3. Questions about who would run the economy are likely to grow as coalition talks come into view. Luxon has said the finance portfolio stays with National, while there has been plenty of speculation about whether Seymour could take the role. Cost of living is the biggest issue in both the news and on social media, so promises on tax and spending are likely to stay in the conversation.

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If you want to find out more about how Isentia can help you understand the NZ media landscape, please reach out to us here.