AI

Tech companies are blaming massive layoffs on AI

Uri Gal, Professor in Business Information Systems, University of Sydney In the past few months, a wave of tech corporations have announced significant staff cuts and attributed them to efficiency gains driven by artificial intelligence (AI). Companies such as Atlassian, Block and Amazon have announced they would lay off thousands of employees due to increased reliance on AI. The narrative these companies offer is consistent: AI is making human labour replaceable, and responsible management demands adjustment. The evidence, however, tells a more nuanced story. The automation story is partly true Genuine disruption is visible in specific corners of the labour market, though the scale of that disruption is commonly overstated. Research from Anthropic published earlier this month shows that although many work tasks are susceptible to automation, the vast majority are still performed primarily by humans rather than AI tools. Moreover, some occupations are more exposed to displacement than others: computer programmers sit at the top of the list, followed by customer service representatives and data entry workers. Yet even within the most exposed occupations, AI use is still limited. The aggregate economic data reflects this reality. A 2025 Goldman Sachs report estimated that if AI were used across the economy for all the things it could currently do, roughly 2.5% of US employment would be at risk of job loss. That’s not a trivial number. However, the report notes that workers in AI-exposed occupations are currently no more likely to lose their jobs, face reduced hours, or earn lower wages than anyone else. The report does note early signs of strain in specific industries. Goldman Sachs identifies sectors where employment growth has slowed that align with AI-related efficiency gains. Examples include marketing consulting, graphic design, office administration and call centres. In the tech sector, US workers in their 20s in AI-exposed occupations saw unemployment rise by almost 3% […]

How CTEM, AI, and access control redefine OT security in 2026

By Carlos Buenano, Field CTO for OT, Armis As we step into 2026, AI-driven adversaries, supply chain fragility, and relentless digitisation are forcing Operational Technology (OT) security to mature into a force to be reckoned with. Here’s what 2026 looks like: AI-Powered adversaries demand autonomous defence AI is no longer an abstract threat vector; it’s an operational force multiplier that attackers are leveraging with frightening results. We’re witnessing adversaries use autonomous agents to probe networks, map exposed devices, and launch dynamic exploitation campaigns that run continuously. In 2026, those systems will act autonomously: isolating compromised segments, or enforcing multifactor re-authentication for operators under suspicious conditions. In OT, where minutes can mean millions, automation will be the only meaningful defence. CTEM becomes the operational centre of gravity A few years ago, “CTEM” was just another Gartner acronym. In 2026, it’s the organising principle for any serious OT security program. CTEM represents a shift from periodic vulnerability management to continuous, risk-based exposure assessment and management across hardware, firmware, network paths, and even supply-chain dependencies. But the key difference this year is context. We’re aligning exposures with what actually matters; the physical process, the human safety implications, and the potential operational impact. The cybersecurity landscape in 2026 is clearly set for a strong and necessary integration where vendors leverage the strengths of CTEM to directly inform actionable firewall enforcements, workflows, and reporting. This narrative is driven by the final “Mobilisation” step of the CTEM cycle, which demands that validated, confirmed high-priority exposures leads to an immediate, automated remediation. Specifically for firewalls, this means a CTEM platform will no longer just issue a general alert but will use its deep, risk-based context to trigger a Security Orchestration, Automation, and Response (SOAR) playbook that instantly pushes a micro-segmentation policy or a temporary block rule to […]

Building psychologically safe, high-performance cultures: Why ISO 45003 matters for NZ manufacturing

From December issue, NZ Manufacturer www.nzmanufacturer.co.nz Theresa Grainger, General Manager, The Lean Hub Every manufacturing site I visit, whether it is a busy factory floor or a small specialised workshop, I believe has one universal truth and that is that people want to feel valued, supported, and safe to share their ideas and do meaningful work. This is where ISO 45003 adds real value, released in 2021 as the world’s first global standard dedicated to managing psychosocial risks and it has become increasingly relevant as organisations recognise that wellbeing and high performance go hand in hand. Building on the foundation established by ISO 45001, ISO 45003 extends workplace safety into an area many organisations still find challenging to define and measure: the mental, emotional, and social conditions of work. It provides guidance for creating environments where people can not only perform well but genuinely thrive. At its core, ISO 45003 is about both preventing harm and protecting workers from psychosocial risks before they escalate. It encourages organisations to take a proactive approach, identifying early warning signs and addressing the root causes of stress or conflict, and designing work environments that reduce the likelihood of harm. The standard offers not just compliance guidance, but a roadmap for building resilient, high-performing and people-centric operations. Personally, this is where it really resonates for me, I love what it represents because it speaks to something I have witnessed again and again in my work: when we design workplaces around people, when we honour their wellbeing, their voices, and their value, the entire organisation lifts. It is also deeply aligned with the principles of Lean and Continuous Improvement, at its heart, Lean isn’t just about eliminating waste, it is about creating environments where people can collaborate openly, feel safe to speak up and bring their […]

3d rendering humanoid robot with ai text in ciucuit pattern

Could a ‘grey swan’ event bring down the AI revolution? Risks we should be preparing for

Cameron Shackell, Sessional Academic, School of Information Systems, Queensland University of Technology The term “black swan” refers to a shocking event on nobody’s radar until it actually happens. This has become a byword in risk analysis since a book called The Black Swan by Nassim Nicholas Taleb was published in 2007. A frequently cited example is the 9/11 attacks. Fewer people have heard of “grey swans”. Derived from Taleb’s work, grey swans are rare but more foreseeable events. That is, things we know could have a massive impact, but we don’t (or won’t) adequately prepare for. COVID was a good example: precedents for a global pandemic existed, but the world was caught off guard anyway. Although he sometimes uses the term, Taleb doesn’t appear to be a big fan of grey swans. He’s previously expressed frustration that his concepts are often misused, which can lead to sloppy thinking about the deeper issues of truly unforeseeable risks. But it’s hard to deny there is a spectrum of predictability, and it’s easier to see some major shocks coming. Perhaps nowhere is this more obvious than in the world of artificial intelligence (AI). Putting our eggs in one basket Increasingly, the future of the global economy and human thriving has become tied to a single technological story: the AI revolution. It has turned philosophical questions about risk into a multitrillion-dollar dilemma about how we align ourselves with possible futures. US tech company Nvidia, which dominates the market for AI chips, recently surpassed US$5 trillion (about A$7.7 trillion) in market value. The “Magnificent Seven” US tech stocks – Amazon, Alphabet (Google), Apple, Meta, Microsoft, Nvidia and Tesla – now make up about 40% of the S&P 500 stock index. The impact of a collapse for these companies – and a stock market bust – would be devastating at a global level, not just financially but also in terms of dashed hopes […]

AI for Manufacturing Operations: It’s the bus you can’t afford to miss

Gareth Mitchell, Associate Partner, IRIS by Argon & Co Manufacturing globally faces relentless pressure for operational excellence, efficiency, and resilience. Over the past five years, Artificial Intelligence (AI) has emerged as a revolutionary innovation and a true economic engine reshaping modern manufacturing. As companies encounter supply chain disruptions, predictive maintenance needs, and real-time quality demands, AI adoption is becoming essential. However, much confusion remains about the economics of AI. Below, we demystify this confusion and explain why integrating AI into your strategy is both the smartest and most cost-effective path for leaders focused on competitiveness and capturing new value. AI is expected to add approximately $7 trillion USD to global GDP over the next decade, mainly by automating tasks, increasing productivity, and driving new value creation. IRIS by Argon & Co is already sees significant ROI across planning, supply chain, document and spend intelligence, and manufacturing efficiency. However, AI adoption represents a fundamental shift in how businesses create value and how labour may be structured in the future. AI’s cost-saving potential is profound, and exceedingly more high-ROI use cases appear across industries. AI has in some cases increased productivity by 40% and delivered cost reductions through AI automation and optimization. Businesses see stark improvements when AI automates repetitive actions, allowing workers to focus on higher-value tasks. The types of real-world use cases IRIS and its clients are developing show real AI-enabled efficiencies, such as reduced error rates, predictive AI reasoned planning, and automation of routine service tasks, all which lead to substantial improvements at all levels of the P&L. Besides economic advantages, early AI adopters gain multiple competitive edges. Early adopters benefit from foundational AI infrastructure that supports future innovation and ongoing productivity. AI-driven companies are focused on productivity gains and disciplined ROI, enabling faster data-driven decisions, better productivity, […]

AI is peeling back the layers of ‘low-value’ work

Kenny Ching, Senior Lecturer, Business School, University of Auckland, Waipapa Taumata Rau As generative artificial intelligence (AI) advances at breakneck speed, it is upending assumptions about which jobs are “safe” from automation. Disruption now extends well beyond manual or routine work into white-collar roles once considered untouchable. Tools such as ChatGPT, Claude and Midjourney can produce policy briefs, analytical reports, software code, design assets and marketing copy in seconds. Even in specialised domains, systems such as PolicyPulse can generate structured briefs and thematic syntheses – tasks that once required teams of experts. If AI can so easily replicate large swaths of professional output, how much of the economy rests on work that creates the appearance of value rather than tangible impact? And could New Zealand – anchored in sectors rooted in physical work, human judgement and essential services – be structurally better placed to thrive? AI’s exposure effect A 2023 Goldman Sachs report estimated generative AI could automate work equivalent to 300 million full-time jobs globally. The highest exposure is in administrative, legal and other information-heavy sectors. In 2024, the International Monetary Fund warned that economies reliant on high-skilled services – such as education, law and finance – face both job losses and rising inequality. This echoes author David Graeber’s concept of “bullshit jobs” – roles that add little genuine value. Between 2000 and 2018, most net job growth came from low productivity service sectors such as marketing, consulting and corporate administration. These are precisely the kinds of tasks AI can now perform in seconds. The OECD has noted routine information processing jobs face the greatest risk. AI is not only replacing roles – it is revealing how insubstantial many of them were. Some argue finance illustrates this reality starkly: intended to allocate capital efficiently, the sector has expanded beyond its productive purpose. Businessman Adair Turner famously called much of […]

Building the Foundation: Preparing Your Manufacturing Business for AI Success

-Adam Sharman, CEO LMAC Group APAC The manufacturing sector stands at the precipice of an AI revolution that promises to transform everything from production efficiency to supply chain management. Yet for many business leaders, the question isn’t whether to adopt AI, but how to prepare their organisations to extract maximum value from these powerful technologies. The answer lies not in the sophistication of the AI itself, but in the quality of the foundation upon which it’s built. The Data Foundation Imperative Before any AI system can deliver meaningful insights, your manufacturing operation must first establish a robust data infrastructure. This begins with conducting a comprehensive audit of your existing data landscape. Map out where data is generated across your operation—from sensor readings on the factory floor to inventory management systems, quality control metrics, and customer order patterns. Many manufacturers discover they’re sitting on vast amounts of valuable data that remains siloed across different departments and systems. The key is achieving data integration and standardisation. Legacy systems often speak different languages, storing similar information in incompatible formats. A machine’s operational data might be recorded in one system while maintenance records exist in another, making it impossible for AI to identify patterns between equipment performance and maintenance needs. Investing in data integration platforms that can unify these disparate sources creates the coherent dataset that AI algorithms require to function effectively. Data quality represents another critical pillar. AI systems amplify the characteristics of the data they’re trained on—if your data contains errors, inconsistencies, or gaps, your AI will perpetuate and magnify these problems. Implement rigorous data validation processes, establish clear data governance protocols, and create systems for continuous data quality monitoring. This might involve automated checks for outliers, regular audits of data entry processes, and establishing clear accountability for data accuracy across teams. […]

From Survive to Thrive: FMCG Strategies for Growth and Profitability in 2025

From NZ Manufacturer magazine, February 2025. Chris Foord, Partner, Argon & Co New Zealand As we look forward to 2025 the outlook for business and NZ are improving. Many businesses in 2024 were focused on the “survive till 2025” mindset, controlling costs and avoiding discretionary spend. Very few though forgot about the consumer/customer and the need to continue to serve, surprise and delight with excellent product, service and pricing. Most FMCG businesses will be looking to return to better margin positions in 2025 and indications are favourable that this is achievable. The inflation beast has been tamed, so interest rates have fallen and are predicted to drop further (albeit not by a huge amount) through 2025. Business sentiment is on the rebound. Consumer confidence is at its highest level for two years, which in turn improves business confidence. Whilst the signs are positive, navigating from the survival mindset to a thrive mindset doesn’t happen without intent. So, what are some helpful tips to consider as FMCG businesses transition into what should be a period of growth, and importantly how to create value and embed sustainable profitability. Here are some areas to consider and explore: Align operations to execute your business strategy Plan to drive profitable growth Unlock, deliver and celebrate quick wins Create and embed a continuous improvement culture AI: Proof of Value Align operations to execute your business strategy Operations is where the rubber hits the road for your business strategy. Are your operational teams involved in the key decisions as you launch new products, drive innovation, review range, pricing and promotional plans? If not, they should be. They operationalise strategy, plans and tactics into reality. Get them onboard early and you will realise value faster and more effectively. Plan to drive profitable growth Continue your focus on productivity. […]

Feeding the Machine

From: September issue of NZ Manufacturer www.nzmanufacturer.co.nz The Hidden Human Labour Powering A.I. Callum Cant, James Muldoon, Mark Graham For readers of Naomi Klein and Nicole Perlroth, a myth-dissolving exposé of how artificial intelligence exploits human labour, and a resounding argument for a more equitable digital future. Silicon Valley has sold us the illusion that artificial intelligence is a frictionless technology that will bring wealth and prosperity to humanity. But hidden beneath this smooth surface lies the grim reality of a precarious global workforce of millions labouring under often appalling conditions to make A.I. possible. This book presents an urgent, riveting investigation of the intricate network that maintains this exploitative system, revealing the untold truth of A.I. Based on hundreds of interviews and thousands of hours of fieldwork over more than a decade, Feeding the Machine describes the lives of the workers deliberately concealed from view, and the power structures that determine their future. It gives voice to the people whom A.I. exploits, from accomplished writers and artists to the armies of data annotators, content moderators and warehouse workers, revealing how their dangerous, low-paid labour is connected to longer histories of gendered, racialised, and colonial exploitation. A.I. is an extraction machine that feeds off humanity’s collective effort and intelligence, churning through ever-larger datasets to power its algorithms. This book is a call to arms that details what we need to do to fight for a more just digital future.

Q & A:Sean Doherty Advanced Manufacturing,Callaghan Innovation

How can Advanced Manufacturing take NZ forward? Advanced manufacturing involves the use of technology to supercharge the manufacturing sector. Already an incredibly pivotal part of our nation’s economy and operations, there is real value to be found in unlocking the full potential of our manufacturers. The implementation of smart products and processes such as artificial intelligence, robotics and 3D printing are just some of the key ways we can look to automate, digitise and further develop operations. New Zealand hopes to reach the level of manufacturing represented by Industry 4.0 – a blueprint made up of a series of government initiatives from around the world. As a nation, reaching this goal would propel the nation forward in several critical ways. Manufacturers can harness new technologies to revolutionise their products and processes, effectively increasing their quality of output, and driving productivity forward. Economically, this creates an increase in profitability, enhances market competitiveness, and helps to generate higher-value jobs by automating lower-level tasks. Fostering innovation, this strengthens our supply chain resilience, and reduces our dependence on foreign sources. We can also work towards realising our full potential as a ‘clean, green New Zealand’, by encouraging resource-efficient, environmentally friendly practices. We are not a country rich with natural resources, except for dairy, horticulture and agriculture. We once made cars and TV sets. When that stopped it couldn’t be started again. So where can Advanced Manufacturing help to turn things around? Market demand, competition, global economic conditions and access to raw materials play crucial roles in the ability for a country to operate in a highly competitive industry – which is largely why dairy, horticulture and agriculture are particular strengths for New Zealand. However, advanced manufacturing holds endless possibilities for improvement. As we increase our capabilities, this certainly creates new opportunities for growth […]

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