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Government must put in hard yards to anchor the underwater industry in the UK

It was a year of change for much of the world. Elections held in more than 60 countries – many of which yielded seismic results – have irreversibly shifted the political dial and no sector, subsea or otherwise, is free from the shocks. Fiscal and economic uncertainty have been part and parcel of the UK […]

It was a year of change for much of the world. Elections held in more than 60 countries – many of which yielded seismic results – have irreversibly shifted the political dial and no sector, subsea or otherwise, is free from the shocks.

Fiscal and economic uncertainty have been part and parcel of the UK in recent years and, sadly, that appears to be one of the few things that isn’t changing.

There is a dark cloud over much of the country, but even within that there are more than a few rays of light.

Among the headline findings to emerge from Global Underwater Hub’s recently released 2024 Business Survey was that the UK’s underwater industry has grown by 15% since 2019, and is now worth £9.2bn and supports 51,000 jobs.

The mood in the subsea supply chain is relatively buoyant, with over half (57%) of respondents to our survey confident that roadblocks to success can be overcome, while overall market prospects remain high, spurred on by the wide range of opportunities across the subsea sector, most notably offshore energy.

Everyone should be enthused by the fact that we have a sector ripe with potential and capable of steering the energy transition right on our doorstep. But things are rarely that simple.

Without firm government action to ensure project certainty and attract sustained investment, these unmatched potential risks are being squandered.

Optimism about supply chain capacity is being overshadowed by growing unease over project timelines.

Industry stakeholders believe that 62% of projects will face delays, eroding the confidence needed to align investment and business strategies.

With only 11% of surveyed companies seeing sufficient policy and financial commitment, many UK-based firms are weighing up the prospect of relocating overseas.

Decisive action at the highest level is needed, or else the UK risks exporting not just technology and expertise, but the high-paying jobs and economic benefits they generate.

GUH’s ask of government is simple: deliver an industrial strategy that leverages the UK’s underwater industry’s excellence, maximises its competitive advantage, and ensures it maintains its edge in global markets.

This strategy must include clear policies, timely approvals, and robust financing mechanisms to translate concepts into completed projects.

The stakes are high. The sector’s ability to service a mix of underwater markets is a unique advantage that could make the UK a hub for clean energy and industrial innovation. But this requires an investment-friendly environment, something that is sorely lacking.

Without this, our world-leading position will erode, along with the share of the jobs and wealth the industry creates.

Looking ahead, February is a pivotal month in the subsea calendar when our annual, flagship exhibition and conference – Subsea Expo – takes place at P&J Live.

This is when we unite the underwater industry to showcase innovation and foster collaboration.

The key themes from our survey will be discussed in our sessions, offering an invaluable chance to dive into the issues affecting our supply chain against the backdrop of massive opportunity.

GUH will be encouraging policy-makers to visit Aberdeen for the conference, where they will be able to see first-hand how vibrant and innovative the UK’s underwater sector is.

The UK government is committed to growing the economy and the country’s underwater industry – be that across energy, defence, aquaculture or telecommunications – can play a major role in achieving further significant growth. But only if we have positive market signals that allow subsea companies to make investment decisions.

Neil Gordon is the chief executive of trade body, Global Underwater Hub

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Sovereign AI and National Infrastructure Policy JLL frames artificial intelligence infrastructure as an emerging national strategic asset, with sovereign AI initiatives representing an estimated $8 billion in cumulative capital expenditure by 2030. While modest relative to hyperscale investment totals, this segment carries outsized strategic importance. Data localization mandates, evolving AI regulation, and national security considerations are increasingly driving governments to prioritize domestic compute capacity, often with pricing premiums reaching as high as 60%. Examples cited across Europe, the Middle East, North America, and Asia underscore a consistent pattern: digital sovereignty is no longer an abstract policy goal, but a concrete driver of data center siting, ownership structures, and financing models. In practice, sovereign AI initiatives are accelerating demand for locally controlled infrastructure, influencing where capital is deployed and how assets are underwritten. For developers and investors, this shift introduces a distinct set of considerations. Sovereign projects tend to favor jurisdictional alignment, long-term tenancy, and enhanced security requirements, while also benefiting from regulatory tailwinds and, in some cases, direct state involvement. As AI capabilities become more tightly linked to economic competitiveness and national resilience, policy-driven demand is likely to remain a durable (if specialized) component of global data center growth. Energy and Sustainability as the Central Constraint Energy availability emerges as the report’s dominant structural constraint. In many major markets, average grid interconnection timelines now extend beyond four years, effectively decoupling data center development schedules from traditional utility planning cycles. As a result, operators are increasingly pursuing alternative energy strategies to maintain project momentum, including: Behind-the-meter generation Expanded use of natural gas, particularly in the United States Private-wire renewable energy projects Battery energy storage systems (BESS) JLL points to declining battery costs, seen falling below $90 per kilowatt-hour in select deployments, as a meaningful enabler of grid flexibility, renewable firming, and

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Lenovo unveils purpose-built AI inferencing servers

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Microsoft will invest $80B in AI data centers in fiscal 2025

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John Deere unveils more autonomous farm machines to address skill labor shortage

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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