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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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In a post-AI world where misinformation spreads faster than facts, trust in leadership has hit an all-time low. According to the latest Edelman Trust Barometer, we are witnessing a steep decline in how much the public trusts CEOs and institutions. So, how do leaders rebuild that capital?

In a recent webinar hosted by Isentia, we explored the critical role of authenticity as the pathway to trust. Moderated by Paik San, Head of Insights (Malaysia & Emerging Markets) at Isentia, the panel featured Kim Dy, Head of Brand & Communications for UnionDigital Bank, and Malathi Pillay, Director of Brand Equity & Communications at Malaysia Rapid Transit Corporation Sdn Bhd. Together with Isentia’s Prashant Saxena, VP, Revenue and Insights, SEA they unpacked how brands can navigate a low-trust environment by being human, consistent, and genuinely empathetic.

Here are the key takeaways from the discussion.

1. Authenticity is currency and trust is wealth

Prashant Saxena kicked off the session by grounding the abstract concept of trust in a practical framework. He noted that while trust is the ultimate "wealth" a brand possesses—protecting it during crises, authenticity is the daily "currency" one must invest to build that wealth.

Isentia’s data suggests that many leaders suffer from an "Authenticity signal poverty"—posting content that lacks social proof, information credibility, or cultural fit. To combat this, communication must rely on the "Three Ps":

• Proof: Is the information accurate and verifiable?
• Place: Does it resonate culturally with the specific audience?
• People: Is there endorsed trustworthiness?

2. During a crisis, "glossy" narratives fail

One of the most powerful insights came from Malathi Pillay at MRT Corp, who manages the reputation of massive public infrastructure projects, emphasized that trust isn't built in big moments, but through the consistency of day-to-day behavior. Her advice for staying authentic is to avoid the trap of "motherhood statements", words that don't really resonate with the common audiences.

She explained that stating a vision like "transforming mobility" is often lost on the audience. To make the brand promise authenticity, one must provide context.

"We always try to support our messaging with specific examples... We talk about that university student that lives in Kajang, who is now able to get to his university in Kota Damansara in one smooth ride within 45 minutes." — Malathi Pillay.

By grounding the narrative in specific, relatable human benefits, like saving time or creating local jobs, brands can bridge the gap between corporate goals and public reality. She also mentions how misinformation does not always have to be dealt with bold statements. Quiet corrections also go a long way in maintaining consistency in our media comms.

3. The "human compass" in tech and banking

Kim Dy from UnionDigital Bank addressed the challenge of humanising a traditionally cold and intimidating industry: banking. For a digital bank where customers may never speak to a human, the brand voice must do the heavy lifting.

Kim introduced the idea of a "human compass"—a framework ensuring every notification, app interface, and social post is helpful, clear, and optimistic.

"People trust people, not logos. Authenticity means speaking the language of your customers, and staying away from jargon in an industry that is unwelcoming and very intimidating." — Kim Dy

She shared a real-world example where a deepfake of a brand ambassador surfaced promoting gambling. Instead of hiding, the bank acted with speed and transparency, proving that trust isn't built in good times alone, but is earned by how you face problems head-on and when audiences actually see the steps taken to better the brand's reputation and earn back trust.

Both panelists agreed that the role of a leader has shifted. In the past, authority meant firmness. Today, authority requires empathy.

• From the public Sector: Malathi noted that when leaders address concerns (like project costs), they must validate the public's anxiety first before diving into technical explanations. "Empathy must always come before explanation," she advised.
• From the private Sector: Kim argued that authority doesn't mean being the loudest voice; it means being the most responsible one. She encourages leaders to move away from corporate scripts and share personal reflections to cut through the noise.

4. Balancing AI speed with human sincerity

As the panel concluded, the conversation turned to the role of AI.

Prashant highlighted a "speed vs. sincerity" dilemma facing modern communicators. His solution was to let data provide the authority, but let leadership provide the empathy. Malathi added that while AI is a tool we all use, leaders must have the discipline not to let it replace human judgment.

In her closing remarks, Paik San summarises that the secret to building lasting trust is coherence. It is the alignment of what you say, what you do, and how you make your audience feel over time.

Whether you are managing a digital bank or the infrastructural capabilities of public transport, the rules of engagement have changed. In a noisy world, the most cutting-edge strategy a leader can employ is simply being human.

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

Alternatively contact our team to learn more insights into authenticity, leadership and why trust is on a decline.

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