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.
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.
Loren is an experienced marketing professional who translates data and insights using Isentia solutions into trends and research, bringing clients closer to the benefits of audience intelligence. Loren thrives on introducing the groundbreaking ways in which data and insights can help a brand or organisation, enabling them to exceed their strategic objectives and goals.
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.
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.
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.
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.
Interested in learning more? Email us at info@isentia.com
" ["post_title"]=> string(80) "PR Asia 2025: how authenticity is the new currency for PR leaders in this AI era" ["post_excerpt"]=> string(0) "" ["post_status"]=> string(7) "publish" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(4) "open" ["post_password"]=> string(0) "" ["post_name"]=> string(74) "pr-asia-2025-authenticity-new-currency-ensuring-trust-in-a-blurred-reality" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2025-08-27 05:04:58" ["post_modified_gmt"]=> string(19) "2025-08-27 05:04:58" ["post_content_filtered"]=> string(0) "" ["post_parent"]=> int(0) ["guid"]=> string(32) "https://www.isentia.com/?p=41613" ["menu_order"]=> int(0) ["post_type"]=> string(4) "post" ["post_mime_type"]=> string(0) "" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" }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 […]
Decision making
You may not trust a computer to make important decisions for you, but it can help guide your choices. Committed to read more in 2018? Amazon will analyse your previous purchasing behaviour to recommend books you might like. If you’d simply like to reconnect with old friends or spend more time with new ones, Facebook will flag friend suggestions for you. If you’re in the market for a new job this year, let LinkedIn’s algorithms suggest jobs you may be interested in or people you should be networking with. Embrace these tools to help cut through the noise and then use your own insight to make decisions on a narrowed, personalised field.
Be more punctual
If you are perennially late and have vowed to be more punctual in 2018, Google Maps is your new best friend, helping you avoid time-sucking activities like getting lost in parking lots or being caught in heavy traffic. Using data from your smartphone, Google is able to provide you with directions to where you parked your car. On the road, Google will analyse your position together with anonymised data from other smartphones to suggest the fastest route to your destination. If driving full-stop is your peeve, then you will be pleased to hear that California authorities will allow self-driving cars to be tested alongside cars driven by humans on roads this year. Experts predict this could result in a 90% reduction in accidents (which will arouse all sorts of ethical debates as to whether humans will still be able to drive cars), 75% less cars on the road and reduce the work commute by almost half.
Boost creativity
With the rise of machine learning comes the fear of job losses. “The development of full artificial intelligence could spell the end of the human race,” Stephen Hawking told the BBC.
An Oxford University survey suggested that 47 per cent of the world’s jobs could be replaced within decades. Autonomous cars present one example of how jobs in transport and logistics may be replaced by robots. With this uncertainty comes the understanding that routine work is far more likely to be automated than jobs requiring skills like creativity or emotional intelligence. Machines may be adept at processing large volumes of data, but they can’t make insightful or creative decisions. The good news is that as machines become smarter, humans are freed from mundane tasks and can become more creative. If you’re in a small business, using accounting products like Xero to manage your financial reporting. This allows you to turn your attention to business boosters like problem solving, improving customer service or creating new products. If you’re in big business, tools like Amazon Transcribe or Amazon Translate can perform laborious tasks like producing and translating documents with lightning speed and accuracy, allowing you to focus on big picture thinking like strategy and profitability.
Stay on top of current affairs
In my work at Isentia, we use machine learning to process seven million news items each day. Not long ago this was a task relegated to humans with the mind-numbing task of flipping through newspapers in search of stories that might relate to a client. Machines trawl video, audio and digital content across more than 5,500 new sites at a rate of 234 stories per second and present meaningful summaries to clients in real-time. Whether a story breaks on Twitter and then spills across news platforms and onto television and radio, machine learning can track and analyse how a story evolves with 99% accuracy. Use these tools to stay on top of the issues or people relevant to your industry – in real time.
Make your mark in 2018
The robots aren’t ‘coming’, they are well and truly here. Without realising, we interact with ‘smart’ technology at almost every touch point of our daily lives. As a technologist, I am excited by machine learning not only because I see its profit boosting value, but also for how much it can improve our working lives each and every day.
If you learn one thing this year, take the time to discover how AI can help you be a more creative and productive version of you in 2018.
Headquartered in Sydney, Australia, Isentia is a media intelligence company operating since 1982. The company is backed by over 1,200 employees with 18 offices across Australia, New Zealand, Asia, Europe and the US. Isentia provides more than 5,000 clients, including many of the world’s leading brands, companies and governments, with media intelligence software and services that help drive more informed and timely business and communication decisions.
Originally featured on Women Love Tech.
" ["post_title"]=> string(60) "Tips For Success: Make A Robot Your Partner In Crime In 2018" ["post_excerpt"]=> string(211) "As artificial intelligence (AI) transitions from novel to normalised in 2018, there are many ways you can integrate advanced technology into your day-to-day life, making you more productive at work and at home. " ["post_status"]=> string(7) "publish" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(4) "open" ["post_password"]=> string(0) "" ["post_name"]=> string(59) "tips-for-success-make-a-robot-your-partner-in-crime-in-2018" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2019-09-25 03:04:04" ["post_modified_gmt"]=> string(19) "2019-09-25 03:04:04" ["post_content_filtered"]=> string(0) "" ["post_parent"]=> int(0) ["guid"]=> string(36) "https://isentia.wpengine.com/?p=1986" ["menu_order"]=> int(0) ["post_type"]=> string(4) "post" ["post_mime_type"]=> string(0) "" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" }As artificial intelligence (AI) transitions from novel to normalised in 2018, there are many ways you can integrate advanced technology into your day-to-day life, making you more productive at work and at home.
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.
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.
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.
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
" ["post_title"]=> string(51) "Transformative tech: What to expect from AI in 2018" ["post_excerpt"]=> string(134) "It’s official: artificial intelligence has arrived. But how will this disruptive technology transform businesses in the near future?" ["post_status"]=> string(7) "publish" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(4) "open" ["post_password"]=> string(0) "" ["post_name"]=> string(50) "transformative-tech-what-to-expect-from-ai-in-2018" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2019-06-25 08:12:16" ["post_modified_gmt"]=> string(19) "2019-06-25 08:12:16" ["post_content_filtered"]=> string(0) "" ["post_parent"]=> int(0) ["guid"]=> string(36) "https://isentia.wpengine.com/?p=1971" ["menu_order"]=> int(0) ["post_type"]=> string(4) "post" ["post_mime_type"]=> string(0) "" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" }It’s official: artificial intelligence has arrived. But how will this disruptive technology transform businesses in the near future?
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:
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.
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.
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.
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.
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.
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:
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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."
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.
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 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.
Get in touch or request a demo.