ANZ businesses urged to prioritise AI readiness & strategy
Jeremy Pell, Area Vice President for ANZ at Elastic, stresses that AI has reached what he describes as a "critical inflection point." "AI has evolved from basic automation to intelligent systems that can connect enterprise applications and workflows," Pell explains. The success of such systems, however, depends on their ability to access structured and unstructured data rapidly and accurately. This evolution, he asserts, is visible in daily life through applications such as Uber's ride-matching and food delivery platforms, which leverage Elastic's Search AI technology to provide faster, more personalised, and context-aware services worldwide.
Pell also notes AI's increasingly critical role in cybersecurity. "Cybersecurity teams must leverage generative AI to strengthen defences against threats like deepfakes and phishing," he maintains. Enhanced search powered by AI is enabling organisations to reduce false positives in threat detection, accelerating both the identification and resolution of incidents. This, Pell believes, is shifting the security landscape and offers a major advantage to proactive businesses willing to embrace these tools.
As the technology becomes more integrated and influential, Pell points to the growing responsibility that comes with such progress. The Business Council of Australia's AI Agenda, for instance, sets forth ambitious goals to position the country as a global AI leader by 2028, focusing on digital infrastructure, skills, and the safe adoption of AI across industries. While AI's potential to reshape industries and improve quality of life is significant, Pell believes its true value will only be realised on open, adaptive platforms capable of offering real-time, holistic data insights. "At Elastic, we're proud to empower organisations to harness this new era of AI with confidence and agility," he says.
A complementary perspective comes from Kumar Mitra, Executive Director, CAP & ANZ, ISG, at Lenovo. Mitra heralds AI Appreciation Day as a "timely reminder that AI is no longer a distant frontier – it's a business-critical priority." Citing Lenovo's CIO Playbook 2025, developed with IDC, Mitra notes that more than 63% of Australian CIOs view aligning AI to business strategy as their top priority. Despite this, he points out, 58% of those surveyed identify data infrastructure as their principal barrier to advancing AI programmes. "It's clear that scaling AI isn't just about capability – it's about readiness," he insists.
Lenovo sees the path forward in what Mitra terms "Hybrid AI" – a distributed, flexible approach to running AI workloads wherever they deliver the greatest value, whether in the cloud, on-premises, or at the edge. Such agility addresses both security concerns and varying business needs. "AI done right can drive both economic and human progress," he adds, citing examples from transforming supply chains and accelerating healthcare diagnostics to enabling inclusive solutions for people with disabilities. For Mitra, it is essential for organisations to move beyond small-scale pilots and instead embed AI as a core component of their growth and inclusion strategies, realising its potential for "sustainable growth, inclusion, and real-world impact."
Both Pell and Mitra agree that the promise of AI lies not only in innovative applications but in strategic vision and robust infrastructure. As organisations in Australia and around the world mark AI Appreciation Day, the industry emphasis is on collaboration, responsible stewardship, and investment in systems that will enable AI to drive meaningful progress well into the future.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Techday NZ
9 hours ago
- Techday NZ
Sensitive data exposure rises with employee use of GenAI tools
Harmonic Security has released its quarterly analysis finding that a significant proportion of data shared with Generative AI (GenAI) tools and AI-enabled SaaS applications by employees contains sensitive information. The analysis was conducted on a dataset comprising 1 million prompts and 20,000 files submitted to 300 GenAI tools and AI-enabled SaaS applications between April and June. According to the findings, 22% of files (total 4,400) and 4.37% of prompts (total 43,700) included sensitive data. The categories of sensitive data encompassed source code, access credentials, proprietary algorithms, merger and acquisition (M&A) documents, customer or employee records, and internal financial information. Use of new GenAI tools The data highlights that in the second quarter alone, organisations on average saw employees begin using 23 previously unreported GenAI tools. This expanding variety of tools increases the administrative load on security teams, who are required to vet each tool to ensure it meets security standards. A notable proportion of AI tool use occurs through personal accounts, which may be unsanctioned or lack sufficient safeguards. Almost half (47.42%) of sensitive uploads to Perplexity were made via standard, non-enterprise accounts. The numbers were lower for other platforms, with 26.3% of sensitive data entering ChatGPT through personal accounts, and just 15% for Google Gemini. Data exposure by platform Analysis of sensitive prompts identified ChatGPT as the most common origin point in Q2, accounting for 72.6%, followed by Microsoft Copilot with 13.7%, Google Gemini at 5.0%, Claude at 2.5%, Poe at 2.1%, and Perplexity at 1.8%. Code leakage represented the most prevalent form of sensitive data exposure, particularly within ChatGPT, Claude, DeepSeek, and Baidu Chat. File uploads and risks The report found that, on average, organisations uploaded 1.32GB of files in the second quarter, with PDFs making up approximately half of all uploads. Of these files, 21.86% contained sensitive data. The concentration of sensitive information was higher in files compared to prompts. For example, files accounted for 79.7% of all stored credit card exposure incidents, 75.3% of customer profile leaks, and 68.8% of employee personally identifiable information (PII) incidents. Files accounted for 52.6% of exposure volume related to financial projections. Less visible sources of risk GenAI risk does not only arise from well-known chatbots. Increasingly, regular SaaS tools that integrate large language models (LLMs) - often without clear labelling as GenAI - are becoming sources of risk as they access and process sensitive information. Canva was reportedly used for documents containing legal strategy, M&A planning, and client data. Replit and were involved with proprietary code and access keys, while Grammarly and Quillbot edited contracts, client emails, and internal legal content. International exposure Use of Chinese GenAI applications was cited as a concern. The study found that 7.95% of employees in the average enterprise engaged with a Chinese GenAI tool, leading to 535 distinct sensitive exposure incidents. Within these, 32.8% were related to source code, access credentials, or proprietary algorithms, 18.2% involved M&A documents and investment models, 17.8% exposed customer or employee PII, and 14.4% contained internal financial data. Preventative measures "The good news for Harmonic Security customers is that this sensitive customer data, personally identifiable information (PII), and proprietary file contents never actually left any customer tenant, it was prevented from doing so. But had organizations not had browser based protection in place, sensitive information could have ended up training a model, or worse, in the hands of a foreign state. AI is now embedded in the very tools employees rely on every day and in many cases, employees have little knowledge they are exposing business data." Harmonic Security Chief Executive Officer and Co-founder Alastair Paterson made this statement, referencing the protections offered to their customers and the wider risks posed by the pervasive nature of embedded AI within workplace tools. Harmonic Security advises enterprises to seek visibility into all tool usage – including tools available on free tiers and those with embedded AI – to monitor the types of data being entered into GenAI systems and to enforce context-aware controls at the data level. The recent analysis utilised the Harmonic Security Browser Extension, which records usage across SaaS and GenAI platforms and sanitises the information for aggregate study. Only anonymised and aggregated data from customer environments was used in the analysis.
Scoop
13 hours ago
- Scoop
Statement On AI In Universities From Aotearoa Communication & Media Scholars Network
We speak as a network of Aotearoa academics working in the inter-disciplines of Communication and Media Studies across our universities. Among us we have shared expertise in the political, social and economic impacts of commercially distributed and circulated generative artificial intelligence ('AI') in our university workplaces. While there is a tendency in our universities to be resigned to AI as an unstoppable and unquestionable technological force, our aim is to level the playing field to promote open critical and democratic debate. With this in mind, we make the following points: For universities… · AI is not an inevitable technological development which must be incorporated into higher education; rather it is the result of particular techno-capitalist ventures, a context which needs to be recognised and considered; · AI, as a corporate product of private companies such as OpenAI, Google, etc., encroaches on the public role of the university and its role as critic and conscience, and marginalises voices which might critique business interests; For researchers… · AI impedes rather than supports productive intellectual work because it erodes important critical thinking skills; instead, it devolves human scholarly work and critical engagement with ideas–elements vital to our cultural and social life–to software that produces 'ready-made', formulaic and backward looking 'results' that do not advance knowledge; · AI promotes an unethical, reckless approach to research which can promote 'hallucinations' and over valorise disruption for its own sake rather than support quality research; · AI normalises industrial scale theft of intellectual property as our written work is fed into AI datasets largely without citation or compensation; · AI limits the productivity of academic staff by requiring them to invent new forms of assessment which subvert AI, police students and their use of AI, or assess lengthy 'chat logs', rather than engage with students in activities and assessments that require deep, critical thinking and sharing, questioning and articulating ideas with peers; For students… · AI tools create anxiety for students; some are falsely-accused of using generative-AI when they haven't, or are very stressed that it could happen to them; · AI tools such as ChatGPT are contributing to mental-health crises and delusions in various ways; promoting the use of generative-AI in academic contexts is thus unethical, particularly when considering students and the role of universities in pastoral care; · AI thus undermines the fundamental relationships between teacher and student, academics and administration, and the university and the community by fostering an environment of distrust; For Aotearoa New Zealand… · AI clashes with Te Tiriti obligations around data sovereignty and threatens the possibility of data colonialism regarding te reo itself; · AI is devastating for the environment in terms of energy and water use and the extraction of natural resources needed for the processors that AI requires. Signed by: Rosemary Overell, Senior Lecturer, Media, Film & Communications Programme, The University of Otago Olivier Jutel, Lecturer, Media, Film & Communications Programme, The University of Otago Emma Tennent, Senior Lecturer, Media & Communication, Te Herenga Waka Victoria University of Wellington Rachel Billington, Lecturer, Media, Film & Communications Programme, The University of Otago Brett Nicholls, Senior Lecturer, Media, Film & Communications Programme, The University of Otago Yuki Watanabe, Lecturer, Media, Film & Communications Programme, The University of Otago Sy Taffel, Senior Lecturer, Media Studies Programme, Massey University Leon Salter, Senior Lecturer, Communications Programme, University of Auckland Angela Feekery, Senior Lecturer, Communications Programme, Massey University Ian Huffer, Senior Lecturer, Media Studies Programme, Massey University Pansy Duncan, Senior Lecturer, Media Studies Programme, Massey University Kevin Veale, Senior Lecturer, Media Studies Programme, Massey University Peter A. Thompson, Associate Professor, Media & Communication Programme, Te Herenga Waka/Victoria University of Wellington Nicholas Holm, Associate Professor, Media Studies Programme, Massey University Sean Phelan, Associate Professor, Massey University Yuan Gong, Senior Lecturer, Media Studies Programme, Massey University Chris McMillan, Teaching Fellow, Sociology Programme, University of Auckland Cherie Lacey, Researcher, Centre for Addiction Research, University of Auckland Thierry Jutel, Associate Professor, Film, Te Herenga Waka, Victoria University of Wellington Max Soar, Teaching Fellow, Political Communication, Te Herenga Waka Victoria University of Wellington Lewis Rarm, Lecturer, Media and Communication, Te Herenga Waka | Victoria University of Wellington Tim Groves, Senior Lecturer, Film. Te Herenga Waka, Victoria University of Wellington Valerie Cooper, Lecturer, Media and Communication, Te Herenga Waka | Victoria University of Wellington Wayne Hope, Professor, Faculty of Design & Creative Technologies, Auckland University of Technology Greg Treadwell, senior lecturer in journalism, School of Communication Studies, Auckland University of Technology Christina Vogels, Senior Lecturer, Critical Media Studies, School of Communication Studies, Auckland University of Technology
NZ Herald
a day ago
- NZ Herald
China dominates the global market for electric vehicles, batteries and solar panels - all invented in the US
Electric vehicles Once, it looked like America's roads would be filled with electric cars. The US inventor William Morrison developed the first successful electric car in 1890, and interested urbanites soon began converting stables to charging ports. By the early 1900s, about one-third of all vehicles on the road were electric. In New York City, a cab company called the Electric Vehicle Company operated electric vehicles with exchangeable batteries, like an early form of Uber or Lyft. At the time, however, many rural areas still lacked reliable electricity: it wasn't until the 1930s that widespread electrification got under way. Oil companies, though, had already created a network to distribute fuel across the country. 'A lot of rural America was still using gasoline for stoves and kerosene for home lighting,' said David Kirsch, a professor of management and entrepreneurship at the University of Maryland. 'You could buy it at many, many general stores across the country.' That made fuel engines more convenient for consumers. The internal combustion engine was improving much faster than battery technology. The Ford assembly line allowed the new fuel cars, like the Model T, to be produced more quickly. By the 1930s, there were only a tiny number of EVs on the road. More than 50 years later, the country had another chance. California said it would require automakers to sell a certain amount of electric vehicles. General Motors built the EV1, a small two-seater sedan that became quickly popular in the state. But when the California regulators backed off the plan in the mid-1990s, GM quietly repossessed the vehicles and discarded them. The US would continue to focus on fuel cars. It was that dominance in fuel-powered cars that initially motivated China to move into EVs more than a decade ago. Around 2010, China's Minister of Science and Technology, Wan Gang, began pushing the country to branch out into electric cars. American companies were already dominating combustion engines, and the country was looking for technologies that its companies could dominate over the next few decades. Between 2010 and 2023, China rolled out a huge bank of subsidies to encourage EV adoption. Interested buyers could get a rebate on an EV of up to 60,000 yuan, or roughly US$8000 ($13,600) – a huge benefit in a country where the average new car costs just US$23,000. EV owners also were exempt from sales tax and received a special coloured licence plate (green instead of blue) that allowed them to bypass the years-long wait for a licence. Manufacturers also received boosts, including tax breaks and faster permitting and siting for factories that produced EVs and batteries. According to one estimate from the Centre for Strategic and International Studies, the Chinese Government poured around US$231 billion into EV adoption – and that's likely an underestimate. The investments paid off. In 2010, both China and the US were selling just over 1000 EVs a year. Last year, the US sold 1.2 million – while China sold 6.4 million. And as Congress cuts EV incentives, the divide is likely to widen. 'There's a real danger of the US becoming more technologically isolated in the automotive sector,' said Ilaria Mazzocco, deputy director and senior fellow in Chinese business and economics at the Centre for Strategic and International Studies. Lithium-ion batteries Batteries followed a similar trajectory to electric vehicles. In the early 1970s, M. Stanley Whittingham, then a scientist at Exxon, created the first functional lithium-ion battery – a design that was later improved upon by John Goodenough at the University of Oxford and the Japanese scientist Akira Yoshino at Asahi Kasei Corp. Initially, the new technology became popular in the 1990s in electronics such as early laptops and cellphones – they were compact and reliable. By the early 2000s, the batteries began making their way into a new generation of electric cars. An American company called A123 was an early manufacturer of lithium iron phosphate batteries with enough capacity to power a car. In 2009, the Department of Energy gave the company hundreds of millions of dollars in a grant under the American Recovery and Reinvestment Act. But the US wasn't boosting the sales of EVs, and early battery companies struggled to find a toehold in a market dominated by fuel-powered cars and trucks. A123 went bankrupt and was later purchased by a Chinese company. By the early 2010s, as China boosted its sales of EVs, the country was also pouring billions of dollars into battery technology and battery manufacturing. At the same time, the country invested in processing critical minerals like cobalt, nickel and graphite – adding stability to the complex battery supply chain. In 2021, the technology got another boost: China began to require that companies add 10 to 30% battery storage to the grid for each gigawatt of wind or solar coming online. Battery production surged. 'It just exploded,' said Iola Hughes, head of research at Rho Motion, a battery research firm and part of the consulting firm Benchmark Mineral Intelligence. Today, China boasts 85% of the world's global capacity for battery cell manufacturing. For EV batteries, the picture is even starker: China holds 94% of the market share for producing lithium iron phosphate batteries. Solar panels For decades, solar panels were a distinctly American creation. In 1954, scientists at Bell Labs created the world's first commercially viable solar cell, which converted 6% of incoming light into electricity. By the 1970s, solar was booming in the US. The country was in the midst of an oil crisis, and the federal Government directed millions of dollars into research and development of solar. Scientists and engineers from around the world flooded into the US to develop solar technologies. President Jimmy Carter had 32 panels installed on the roof of the White House. According to one estimate, 95% of the world's solar industry in 1978 was based in the US. But in the 1980s, everything changed. President Ronald Reagan slashed funding for renewables and research and development into solar power. 'It was really ideological,' said Greg Nemet, professor of public affairs at the University of Wisconsin at Madison. 'They cut the solar budget by 85% within a couple of years.' Germany and Japan filled the vacuum left by American leadership, gobbling up experienced engineers and scientists. Then, in the early 2000s, European countries began offering huge subsidies for installations of wind and solar. Chinese companies saw an opportunity – and started building millions of panels. 'There was a lot of growing demand in the early to mid-2000s, thanks to all these incentives in Europe, and a lot of entrepreneurs in China just set up factories to serve that demand,' Mazzocco said. After the 2008 financial crisis, Europe shut down those subsidies as the continent shifted towards austerity. But unlike the US decades before, China decided to continue to support the development of solar power. 'The Chinese Government stepped in,' Mazzocco said. So far, China has invested US$50b in new solar power production, and the country now accounts for about 80% of the global solar supply chain. Today, eight of the top 10 solar panel manufacturers are based in China. The other two are in India and Singapore. Experts say that the country's success is based on two things: reliable policy and a push to adopt the new technologies. 'I look across the period from say '69 to the present – what strikes me is how inconsistent we have been with policy,' said Kirsch. 'The Chinese have just cleaned our clock by having consistent policy.' At the same time, China pushed consumers to adopt the technologies even as they encouraged manufacturers to build them. 'Technologies succeed when you combine a technological opportunity with a market opportunity,' said Nemet. Despite all of the US inventions, Nemet says, the country never focused on making sure there was enough domestic demand for those technologies. 'The US was really good at creating these technological opportunities – but we just weren't supporting the market side enough,' he said.
