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Unlocking transferable skills and embracing the energy expansion

The energy industry is transforming. With the global push towards renewable energy, there’s a growing need to address the concerns of workers in traditional sectors like oil and gas. One of the key topics in this conversation is the idea of “transferable skills.” The notion that skills acquired in one sector can be effectively utilized […]

The energy industry is transforming. With the global push towards renewable energy, there’s a growing need to address the concerns of workers in traditional sectors like oil and gas.

One of the key topics in this conversation is the idea of “transferable skills.” The notion that skills acquired in one sector can be effectively utilized in another is not just a possibility; it’s necessary for a smooth and just transition — or, as JAB Recruitment prefers to call it, an energy expansion.

Transition versus expansion: seizing opportunities with courage

The term “energy transition” often carries connotations of risk and uncertainty, particularly for those in the oil and gas sector. However, the team at JAB Recruitment looks at it differently. Rather than a transition that implies a shift from one sector to another, JAB believes that today’s industry offers opportunities for an across-the-board energy expansion. This includes traditional oil and gas, and renewable energy sources like offshore wind, carbon capture, and hydrogen.

The value of oil and gas skills in renewables

Robert Gordon University’s UK Offshore Energy Workforce Transferability Review found that over 90% of the UK’s oil and gas workforce have a medium to high skills transferability score and are well positioned to work in adjacent energy sectors. This statistic underscores the potential for cross-sector skills application. For instance, workers experienced in offshore oil and gas projects are often well placed for roles in offshore wind, carbon capture, and hydrogen projects—sectors that are seeing significant growth and investment.

The oil and gas workforce need not see the energy expansion as a career cliff edge. The expansion will happen over decades, allowing workers to adapt, upskill, and find their place in a growing energy landscape. It’s not about leaving behind the skills and expertise honed over the years; rather, it’s about applying them in a new context.

Looking at it from the renewable energy perspective, the message for employers is: don’t write off the oil and gas talent pool.

Jab Recruitment's Chris Black. © Supplied by Jab recruitment
Jab Recruitment’s Chris Black.

Overcoming barriers: training and perception

A major hurdle in the energy expansion is the perception of high retraining costs and the misunderstanding of the relationship between oil and gas and renewables. It’s crucial to dispel the myth that moving between these sectors requires prohibitively expensive training.

Yes, training and some new safety certifications will be required for new roles like it usually is for any new job. But, for oil and gas workers, many of the core skills required will likely be in place already. That means new training time might be counted in hours rather than days or weeks. Also, training opportunities today are more accessible than ever, often available in online, bite-sized formats that fit into busy working lives.

The issue isn’t just about the practicalities of retraining but also about the emotional and psychological impact of the word “transition.” For many in the industry, the word suggests the decline of industries like coal mining and steelwork, where workers were left behind as the world moved on. Therefore, the narrative needs to shift from one of risk to one of opportunity.

Mobilising a just expansion

JAB Recruitment recognises that oil and gas workers have valuable skills and may require funding routes for training and has a unique app powered by Moblyze to make the energy expansion as seamless as possible.

Using AI, the platform instantly matches you with job opportunities across the energy spectrum. The advanced algorithm analyses your skills and certifications, and then recommends jobs that fit your qualifications, including those in sectors you might not have considered before. It even identifies the training you might need for a role in a new sector, where you can get that training, and the grants available to you. This real-time matching is revolutionising how to find jobs. It’s no longer about searching for jobs; the jobs will find you.

The future: toward an all-energy workforce

The goal is the creation of an all-energy workforce that can perform across various energy sectors. This workforce flexibility is already happening in sectors like subsea where workers regularly cross over between oil and gas and offshore wind projects. The same applies in CCUS and Hydrogen.  JAB is recognised as the market leader in this space, partnering with clients to accelerate the evolution of energy talent.  This trend will grow, creating a fully adaptable workforce ready to tackle the energy challenges of tomorrow.

A major driver in creating an all-energy workforce will be the development of an offshore skills passport that will allow workers to move seamlessly between oil and gas and renewable projects. However, challenges remain, particularly in aligning certifications and training standards across different sectors and geographies. An offshore skills passport would require collaboration across countries and organisations. It’s a task that is complex but essential.

Answering the call

For the energy sector to truly expand it’s important to communicate the wide range of opportunities available to the existing workforce. In this, JAB Recruitment is leading the way – not only by diversifying services but also by supporting clients in this journey.

The energy expansion is an opportunity to innovate, grow, and create a sustainable future. The skills that have built the oil and gas industry are far from obsolete – they are the foundation upon which the new energy landscape will be built.


Find out more from Jab Recruitment.

Or download the JAB App via the Apple Store or Google Play.

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Expand Energy Corp. said Domenic “Nick” Dell’Osso, Jr. stepped down as chief executive officer as the largest US natural gas producer plans to relocate its headquarters to Houston from Oklahoma City in mid-2026. Michael Wichterich, Expand’s chairman, will assume the role of interim CEO while the board searches for a permanent replacement, the company said Monday in a statement. Dell’Osso will serve as an external adviser for an unspecified period. “The relocation, which will primarily focus on the executive leadership team, will strengthen Expand Energy’s relationships with key industry and commercial partners,” the company said in the statement. Moreover, “virtually all Oklahoma City employees will be unaffected” by the change in headquarters, beyond those executive leaders, Wichterich told employees in an internal email seen by Bloomberg. Expand’s shares dropped as much as 8.9%, the most since July. The abrupt change in leadership comes less than six months after the Chief Financial Officer Mohit Singh left the company, which cited his “termination without cause.” RBC Capital Markets equity analyst Scott Hanold, who said he met with Expand’s leadership Monday morning, wrote in a note to clients that the conversation indicated “there were no disagreements or anything improper” and the executive change is the result of Dell’Osso choosing to stay in Oklahoma City. Expand’s board of directors views the move of executive functions to Houston as “urgent” to supporting “marketing efforts and commercial efforts,” Hanold said. Dell’Osso joined Chesapeake Energy, which was renamed Expand Energy after acquiring rival driller Southwestern Energy, in 2008 after working as an investment banker at Jefferies. WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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Equinor Divesting Full Onshore Position in Vaca Muerta Basin

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BofA Report Compares Big Oil Cos

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BP Halts Share Buybacks

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NetBox Labs ships AI copilot designed for network engineers, not developers

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US pushes voluntary pact to curb AI data center energy impact

Others note that cost pressure isn’t limited to the server rack. Danish Faruqui, CEO of Fab Economics, said the AI ecosystem is layered from silicon to software services, creating multiple points where infrastructure expenses eventually resurface. “Cloud service providers are likely to gradually introduce more granular pricing models across cloud, AI, and SaaS offerings, tailored by customer type, as they work to absorb the costs associated with the White House energy and grid compact,” Faruqui said.   This may not show up as explicit energy surcharges, but instead surface through reduced discounts, higher spending commitments, and premiums for guaranteed capacity or performance. “Smaller enterprises will feel the impact first, while large strategic customers remain insulated longer,” Rawat said. “Ultimately, the compact would delay and redistribute cost pressure; it does not eliminate it.” Implications for data center design The proposal is also likely to accelerate changes in how AI facilities are designed. “Data centers will evolve into localized microgrids that combine utility power with on-site generation and higher-level implementation of battery energy storage systems,” Faruqui said. “Designing for grid interaction will become imperative for AI data centers, requiring intelligent, high-speed switching gear, increased battery energy storage capacity for frequency regulation, and advanced control systems that can manage on-site resources.”

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Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

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Operationalizing AI at Scale: Google Cloud on Data Infrastructure, Search, and Enterprise AI

The AI conversation has been dominated by model announcements, benchmark races, and the rapid evolution of large language models. But in enterprise environments, the harder problem isn’t building smarter models. It’s making them work reliably with real-world data. On the latest episode of the Data Center Frontier Show Podcast, Sailesh Krishnamurthy, VP of Engineering for Databases at Google Cloud, pulled back the curtain on the infrastructure layer where many ambitious AI initiatives succeed, or quietly fail. Krishnamurthy operates at the intersection of databases, search, and AI systems. His perspective underscores a growing reality across enterprise IT: AI success increasingly depends on how organizations manage, integrate, and govern data across operational systems, not just how powerful their models are. The Disconnect Between LLMs and Reality Enterprises today face a fundamental challenge: connecting LLMs to real-time operational data. Search systems handle documents and unstructured information well. Operational databases manage transactions, customer data, and financial records with precision. But combining the two remains difficult. Krishnamurthy described the problem as universal. “Inside enterprises, knowledge workers are often searching documents while separately querying operational systems,” he said. “But combining unstructured information with operational database data is still hard to do.” Externally, customers encounter the opposite issue. Portals expose personal data but struggle to incorporate broader contextual information. “You get a narrow view of your own data,” he explained, “but combining that with unstructured information that might answer your real question is still challenging.” The result: AI systems often operate with incomplete context. Vector Search Moves Into the Database Vector search has emerged as a bridge between structured and unstructured worlds. But its evolution over the past three years has changed how enterprises deploy it. Early use cases focused on semantic search, i.e. finding meaning rather than exact keyword matches. Bug tracking systems, for example, began

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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

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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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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