Latest news with #hyperscalers
The Australian
19 hours ago
- Business
- The Australian
Rise of the digital workforce: rethinking work in the age of agentic AI
What is perceived as science fiction today becomes mainstream tomorrow – and transformative the day after. Such is the progression of generative AI, and now, agentic AI. We may not have all the answers yet. But the questions are becoming clearer. And the organisations that ask them early – and act boldly – will shape the future of work for the better. As Professor Ethan Mollick said recently, 'The time to begin isn't when everything becomes clear – it's now, while everything is still messy and uncertain. The advantage goes to those willing to learn fastest.' The pace at which AI is evolving is staggering. Agentic AI – autonomous systems capable of reasoning, learning, and acting independently – are no longer a theoretical concept. Agents are already executing human tasks, orchestrating workflows, and adapting through interactions with both humans and other agents. It's only getting faster as enterprise software players, hyperscalers, platform providers, frontier labs and new agentic product start-ups are innovating and releasing capabilities into market at a blistering pace. The short of it really is that we've well and truly entered a new era of transformation – and what we're witnessing is the rise of a digital workforce. To harness its full potential, we must move beyond outdated paradigms – especially the one-to-one thinking that equates digital labour to human labour in direct substitution. Human capacity is finite. Digital labour is not. It's a limitless, scalable, always-on capacity that can multiply effort, insight, and creativity at a scale and speed that previously was not possible. When we break this outdated paradigm, and rethink how we work, the opportunities look very different. Stu Scotis, National GenAI Lead at Deloitte Australia Picture a marketing team empowered by AI agents capable of simulating hundreds of thousands of campaigns, then surfacing the top-performing strategies for a human to evaluate. Or a sales force supported by thousands of virtual assistants, each tailoring offers to individual customer profiles based on real-time analysis of preferences, history, and behaviour. Or a finance team where CFOs have thousands of digital finance analysts. These examples are just a starting point, and exciting as they are, even these are constrained by today's thinking of structure and work. We're not just talking about automation for productivity – it's a reinvention of how we work. It demands a wholesale redesign of how we think about workflows, roles, and even how value is created. This is happening now and if you're following this space closely, you'll have seen headlines with high-profile CEOs setting directives on AI usage by employees with AI first strategies. We're also seeing examples of even bolder moves with some organisations merging HR and IT departments as the line between managing technology and managing people becomes increasingly blurred with agents. These organisations are going beyond surface-level integration and not just bolting AI onto existing systems – they are reimagining those systems entirely. They are looking at core functions such as customer service, product development, HR, and operations to be restructured and redesigned to take full advantage of AI's capabilities. Looking ahead, leadership roles also need to be redesigned as we consider the digital workforce. To date, leadership has been built around managing people, now we need managers who orchestrate fleets of AI agents as well as human teams. Setting clear expectations, evaluating outputs, and defining what 'good' looks like are quickly becoming core competencies for leaders as they take on accountability to transform their organisations with AI. Another essential question for every organisation is this: how far will you allow automation to proliferate? The capability is here – but are your systems, culture and people prepared? Agentic AI can perform complex tasks end-to-end, but without clear governance and ethical guidelines, it can introduce real risk. The path forward involves deliberate decisions about where to retain human oversight, where to build in safeguards, and how to ensure transparency in automated processes. What the end state looks like when functions, organisations or even sectors are redesigned around AI is not yet clear. But waiting isn't an option. Those who progress the fastest will gain significant, if not impassable, competitive advantage. We might not want to be in a race with AI – but we are. It's a global race, and the stakes are high. Productivity, competitiveness and economic growth are all on the line. And as the pace of technological change accelerates, so must our ability to act with clarity and intent. The race leaders will be those who are already laying the groundwork to rebuild, rethink and reinvent around AI. We've got a lot more to say about how organisations should be planning to shape the future of work with a sustained focus on delivering scale and value. Watch this space! Stu Scotis is National GenAI Lead at Deloitte Australia. - Disclaimer This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication. About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee ('DTTL'), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. Please see to learn more. Copyright © 2025 Deloitte Development LLC. All rights reserved. -
Bloomberg
3 days ago
- Business
- Bloomberg
High Risk and High Reward of Undersea Cables
Undersea cables carry 99% of the world's internet traffic, but how do these cables work, and are they worth the investment? Google's first employee of its subsea unit, Jayne Stowell weighs in on how the company paved the way for hyperscalers to take over an industry once controlled by telecom giants. (Source: Bloomberg)
Bloomberg
4 days ago
- Business
- Bloomberg
Air Traffic Control, Undersea Cables, International Students
This week, why fixing the US air traffic control system won't happen overnight and the Trump administration's plan to fix it. Plus, how hyperscalers have taken over the business of undersea cables to support our growing data needs. Later, a look into the role of international students in the educational industrial complex and innovation ecosystem. (Source: Bloomberg)
CNA
5 days ago
- Business
- CNA
Marvell forecasts second-quarter revenue above estimates on strong demand for custom AI chips
Marvell Technology forecast second-quarter revenue above Wall Street estimates on Thursday, betting on strong demand for its custom chips powering artificial intelligence workloads in data centers. Demand for custom AI chips continues to fuel growth, while networking chips and electro-optics have also seen robust order momentum. These advancements help hyperscalers seeking to scale their infrastructure to support AI workloads. Marvell said in its post-earnings call that it expects AI tailwinds to remain strong, driven by robust hyperscaler spending, new sovereign data center projects, and the expansion of emerging market players expanding the market, opening up growth opportunities. Revenue from Marvell's data center segment, which accounts for 76 per cent of the company's total revenue, stood at $1.44 billion in the first quarter. The company's carrier and enterprise networking segments have also gradually recovered following a period of inventory correction. "We believe the custom silicon business will be the primary growth driver over the next 3-5 years, contributing positively to operating profits despite lower gross margins," said Angelo Zino, analyst at CFRA Research. Zino added that the upcoming custom silicon webinar on June 17 could serve as a catalyst by potentially showcasing TAM expansion opportunities and new customer wins in CY26. However, the consumer end market remained weak for the company, with revenue falling 29 per cent sequentially to $63.1 million due to seasonality in gaming demand. The industrial segment also struggled, reporting a 12 per cent sequential decline in revenue. Shares of the company fell about 2 per cent in extended trading. The company expects second-quarter revenue to be $2 billion, plus or minus 5 per cent compared with analysts' average estimate of $1.98 billion, according to data compiled by LSEG. In May, Marvell said it was postponing its previously scheduled investor day conference due to a "dynamic macroeconomic environment." It reported revenue of $1.9 billion for the quarter ended May 3, compared to analysts' average estimate of $1.88 billion.
Reuters
5 days ago
- Business
- Reuters
Chipmaker Marvell forecasts second-quarter revenue above estimates
May 29 (Reuters) - Marvell Technology (MRVL.O), opens new tab forecast second-quarter revenue above Wall Street estimates on Thursday, betting on robust demand for custom chips powering artificial intelligence workloads in data centers. Demand for custom AI chips continues to fuel growth, while high-performance networking chips and electro-optics have also seen robust order momentum. These advancements help hyperscalers manage the exponential increase in data traffic generated by AI applications. Revenue from Marvell's data center segment, which accounts for 76% of the company's total revenue, stood at $1.44 billion in the first quarter. The company expects second-quarter revenue to be $2 billion, plus or minus 5% compared with analysts' average estimate of $1.98 billion, according to data compiled by LSEG.
