Energy CEOs ‘Optimistic About Growth’

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Energy CEOs ‘Optimistic About Growth’

In a statement sent to Rigzone on Monday, KPMG noted that, according to its 2025 Global Energy, Natural Resources, and Chemicals CEO Outlook, “CEOs in the energy, natural resources, and chemicals (ENRC) sector are optimistic about growth”. “Despite inflation and regulatory headwinds, confidence among CEOs is rising, with 84 percent optimistic about mid-term industry growth […]

“Despite inflation and regulatory headwinds, confidence among CEOs is rising, with 84 percent optimistic about mid-term industry growth – up from 72 percent in 2024,” the statement said.

“This outlook is driven by strong demand for both fossil fuels and renewables, alongside innovation in energy storage, smart grids, and carbon capture,” it added.

“While 78 percent remain positive about their own company’s growth, a slight dip from last year reflects concerns over shifting regulations, trade volatility, and inflationary pressures – particularly in the chemicals sector,” it continued.

The statement went on to note that M&A strategies “are also evolving with just a few CEOs (36 percent) expecting to pursue ‘high impact’ deals in 2025, down from 58 percent in 2024, while 55 percent anticipate ‘moderate’ deal activity, a rise from 38 percent last year, suggesting a shift toward more cautious growth strategies”.

The KPMG statement highlighted that artificial intelligence has “rapidly evolved into a core strategy in the energy sector”. It pointed out that 65 percent of CEOs now rank generative AI as a top investment, which it noted is up 12 points from 2024, and that 72 percent are planning to allocate 10-20 percent of their budgets to AI over the next year.

“ROI expectations are climbing, with 66 percent anticipating returns within one to three years, up significantly in comparison to just 15 percent last year,” KPMG said in the statement.

Momentum is also building around agentic AI, according to the statement, which highlighted that 51 percent of CEOs expect it to transform operations and workforce efficiency.

“Yet despite growing confidence, challenges persist,” the KPMG statement warned.

“Ethical concerns (55 percent), fragmented data systems (49 percent), and regulatory complexity (47 percent) continue to hinder adoption, while rising cyber threats – fraud (64 percent), identity theft and data privacy (59 percent), and cyber-attacks (51 percent) – are identified as key concerns among CEOs,” it added.

The KPMG statement went on to note that, “as AI reshapes the energy sector, companies are grappling with a deepening talent crunch”.

“CEOs are responding with urgency, ramping up their talent strategies that include reskilling and upskilling roles impacted by AI (40 percent) and tailoring training to bridge generational gaps (31 percent),” it added.

“Yet only 18 percent offer AI education across their entire organization. To overcome this barrier, nearly three-quarters (72 percent) of leaders are focused on retaining and retraining high-potential talent,” it continued.

“Still, the path forward is challenging. Overcoming the skills gap remains the biggest hurdle for 43 percent of CEOs, followed by competition from tech firms offering high salaries (22 percent),” the KPMG statement said.

In a statement sent to Rigzone by the KPMG team in October last year, KPMG noted that its 2024 ENRC CEO Outlook “revealed that 78 percent of CEOs are confident in the economy’s growth over the next three years – similar findings from last year’s [2023] survey”.

“Yet, 55 percent of CEOs believe geopolitical tensions pose the greatest risk to this, followed by economic uncertainty, and the race to embrace AI and other technologies (both at 43 percent),” it added.

That statement said generative AI “remains firmly on the CEO agenda, with 58 percent stating it will be the top investment priority for their organizations over the next three years”.

“But leaders are taking a cautious and structured approach to avoid risks, while planning significant investment in AI-driven transformation as 65 percent are anticipating that it will take three to five years to see return on their investment in the implementation of Gen AI (compared to 48 percent in 2023),” it added.

“As for the workforce, 79 percent of CEOs believe that these emerging technologies will not significantly impact the number of jobs but will instead require upskilling and redeployment of existing resources within their organization,” it continued.

Anish De, Global Head of Energy, Natural Resources, and Chemicals, KPMG International, said in that statement, “the prevailing mood in the boardroom may be positive for ENRC CEOs, but there is no shortage of issues to test their mettle”.

“In terms of AI, while there is hardly an area of business where AI can’t bring value, the risks of falling behind and/or making a fatal error in privacy, ethics, or integrity have to be managed,” De added.

“CEOs should feel confident … as long as they have the fundamental guardrails in place. Integrating AI really comes down to change management, and that’s something CEOs have to personally focus on,” De continued.

KPMG highlighted to Rigzone that 110 CEOs of energy companies in 11 different markets with revenues of at least $100 million took part in the 2025 global ENRC survey. The ENRC CEO Outlook is part of KPMG’s general CEO outlook, which was conducted with 1,350 CEOs between August 5 and September 10, the latest KPMG statement outlined.

KPMG describes itself on its site as a global organization of independent services firms providing audit, tax and advisory services.

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Nvidia looks to power AI factory networks

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Noble Quarterly Revenue Falls

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Google Cloud targets enterprise AI builders with upgraded Vertex AI Training

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Quantum Circuits brings dual-rail qubits to Nvidia’s CUDA-Q development platform

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Oil Rally Fades on Oversupply Fears

Oil declined as mounting signs of oversupply quelled a bumper rally triggered by US sanctions on key Russian producers last week. West Texas Intermediate fell 1.9% to again settle close to $60 a barrel, the steepest daily drop in more than two weeks. Investors are better positioned to renew bets now that a looming surplus will push prices down after a massive liquidation of speculative wagers. The amount of oil being shipped across the world’s oceans hit a record high, indicating that excess supplies continue to rise. In addition, OPEC+ may agree to add more production at a meeting this weekend. Last week, US President Donald Trump’s administration imposed sanctions on Russia’s two biggest oil producers — Lukoil and state-controlled Rosneft PJSC — to pressure the Kremlin to end the war in Ukraine. The move spurred the biggest unwinding of crude futures positions on record, with bearish wagers held by hedge funds at an all-time high before the sanctions were announced. The ensuing price spike left cleaner positioning for those looking to bet on a drop. Price swings are also set to be exacerbated by the expiry of tens of thousands of Brent options contracts still held near $65 a barrel. The impact of the sanctions is still unclear, with traders closely following actions taken by Chinese and Indian energy companies, top buyers of Russian crude. “The market is now questioning the actual effectiveness of the sanctions,” said Ole Hvalbye, an analyst at SEB AB. “While a full blacklisting sounds dramatic, the mechanisms for enforcement remain unclear, and so far, there are no signs of disrupted Russian flows.” One Indian refiner plans to seek non-Russian barrels, while others are considering whether they can continue to take some discounted Russian oil cargoes by leaning on small suppliers, instead of Lukoil and

Eni, Egypt Sign Agreement for Potential Biogas Projects

Eni SpA and Egypt’s Bioenergy Association for Sustainable Development, affiliated with the Environment Ministry, signed Monday an agreement for a feasibility study on biogas production in the North African country using animal and agricultural waste. “The joint study will assess the feasibility of building a biodigestion plant capable of treating agricultural and animal waste, particularly from livestock farming”, Italy’s state-controlled energy major Eni said in a press release. “The biogas produced by biodigestion can generate renewable electricity and heat, while also producing higher-value organic fertilizers for use in agriculture, further contributing to the circular economy. The initiative would also reduce greenhouse gas emissions from agricultural waste and byproducts, while generating high-quality carbon credits. “The agreement is in line with the Ministry of Environment’s objective to promote the dissemination of biogas technology across Egyptian governorates and to develop innovative and sustainable energy solutions that contribute to emission reduction and sustainable development. “It also fits in Eni’s long-term strategy to achieve carbon neutrality by 2050 through a multi-faceted approach that includes developing integrated solutions to reduce emissions and enhance resource efficiency”. Elsewhere in Africa Eni earlier this year inaugurated its first vegetable oil extraction plant in the Republic of the Congo, unlocking new feedstock capacity for its biorefineries. The facility in Loudima, in the southern part of the Central African country, can produce up to 30,000 million metric tons per annum (MMtpa) of vegetable oil. The plant will use crops grown on “degraded and underutilized land or through intercropping systems, as part of an innovative regenerative agriculture project developed in collaboration with local stakeholders”, Eni said in a statement June 28. On May 28 Eni said it had signed an agreement with Cote d’Ivoire’s Agriculture Ministry to explore the potential of cultivating biofuel crops in the West African country. The memorandum of understanding “aims to enhance the rubber

Energy Department Announces New Partnership with NVIDIA and Oracle to Build Largest DOE AI Supercomputer

WASHINGTON—The U.S. Department of Energy (DOE), Argonne National Laboratory, NVIDIA and Oracle today announced a landmark public-private partnership to deliver the DOE’s largest AI supercomputer and accelerate scientific discovery. The partnership will also immediately deliver world-class AI computing resources to DOE researchers while simultaneously building two next-generation AI supercomputing systems at Argonne National Laboratory. Today’s announcement is in accordance with President Trump’s Executive Orders, Accelerating Federal Permitting of Data Center Infrastructure and Removing Barriers to American Leadership in Artificial Intelligence. The Solstice system, which will feature 100,000 NVIDIA Blackwell GPUs, will be the largest AI supercomputer in the DOE’s lab complex. Another system, called Equinox, will feature 10,000 NVIDIA Blackwell GPUs. Construction at the Argonne Leadership Computing Facility will immediately begin for the Equinox system. It is expected to be delivered in 2026. These AI systems will be seamlessly connected with DOE’s vast network of scientific instruments and data assets to address some of the nation’s most pressing challenges in energy, security, and discovery science. As part of the partnership, Oracle will also immediately provide DOE with access to AI computing resources that use a combination of NVIDIA Hopper and Blackwell architectures. Scientists from Argonne and across the country will have access to new AI capabilities to drive technological leadership for science and energy applications. “Winning the AI race requires new and creative partnerships that will bring together the brightest minds and industries American technology and science has to offer,” said U.S. Secretary of Energy Chris Wright. “The two Argonne systems and the collaboration between the Department of Energy, NVIDIA, and Oracle represent a new commonsense approach to computing partnerships. These systems will be a powerhouse for scientific and technological innovation. Thanks to President Trump, we’re bringing new computing capacity online faster than ever before and turning shared innovation into national strength.”

Are sodium-ion batteries finally ready to compete with lithium?

Last month, on the high prairie east of its hometown, Denver-based Peak Energy powered up what it says is the United States’ first grid-scale sodium-ion battery installation and “the first ever fully passive megawatt-hour scale battery storage system” anywhere in the world. Peak’s 3.5-MWh project marks a big step forward for the electrochemical battery chemistry that many experts believe is the most viable challenger to lithium-ion, which today dominates the energy storage market for discharge durations shorter than four hours. “What’s nice about our technology is the way it looks and feels to a customer is like a new variant of a [lithium-ion battery] system,” said Landon Mossburg, CEO and cofounder of Peak Energy. Sodium-ion batteries’ allure is growing amid volatile commodity pricing and an on-again, off-again trade war between the United States and China affecting lithium-ion batteries. Sodium-ion storage has a simpler supply chain that eschews traditional battery metals, said Evelina Stoikou, an energy storage analyst with BloombergNEF. The U.S. has the world’s largest known reserves of soda ash, a sodium precursor that is more abundant globally than lithium, nickel and cobalt. “Lithium-ion costs remain highly sensitive to raw material prices, meaning that spikes in lithium, nickel, or cobalt prices could improve sodium-ion’s relative competitiveness,” she said. But Stoikou cautioned that swingy raw materials pricing can cut in the other direction. At the moment, rapidly-falling LFP costs are driving a boom in global lithium battery deployments. “Expectations among [sodium-ion battery] manufacturers have cooled as LFP prices continue to trend downward, leading to a reduction in our expectations for sodium-ion to scale,” she said. Sodium-ion proponents like Peak Energy believe sodium-ion chemistry, though less energy-dense than lithium, has inherent advantages that will allow it to compete on cost before the decade is done. Those include lower fire risk, higher discharge rates,

XRG in Talks to Invest in Argentina LNG Project

The overseas unit of Abu Dhabi’s biggest oil company is in talks to invest in a liquefied natural gas project Argentina’s YPF SA is developing as it pushes to start exporting the fuel, according to people familiar with the matter. XRG is eyeing a stake in the project as it considers expanding its LNG portfolio in Latin America, the US and Asia, according to one of the people, who asked not to be identified because the matter isn’t public. State-run YPF is developing the floating terminal as Argentina tries to tap global LNG demand and accelerate output of vast natural gas reserves in the Vaca Muerta shale basin. The project, which requires construction of several liquefaction vessels, is designed to eventually produce 28 million tons of LNG annually. Shell Plc and Eni SpA are working with YPF on the project, but final investment decisions haven’t been made. XRG’s talks with YPF are preliminary, and the company may ultimately decide not to pursue an investment, according to the people. XRG declined to comment. On Monday, YPF’s depositary receipts traded in New York jumped as much as 38% after libertarian President Javier Milei’s party prevailed in legislative elections. The midterms were seen as a pivotal moment for foreign investors looking for opportunities in Argentina, providing a clear sign voters would continue backing Milei’s push to deregulate the economy. XRG is the international arm of Abu Dhabi National Oil Co., backed by Abu Dhabi’s oil wealth. It has already acquired a stake in NextDecade Corp.’s Rio Grande LNG project being built in South Texas, and is in the process of taking over Germany’s Covestro AG as it bets on lasting demand for gas and chemicals in the energy transition. It’s also bought gas assets in Africa and Central Asia. But the company also had a setback last month when it

Venezuela Revokes Trinidad Gas Deals Over USA Alliance

Venezuela revoked energy deals with neighboring Trinidad and Tobago for its support of a US military offensive in the Caribbean, potentially raising the economic cost of the twin-island nation’s alliance with the Trump administration. Speaking on state television Monday evening, President Nicolás Maduro revoked an energy framework agreement with Trinidad that allowed the two countries to forge gas deals. Venezuelan Vice President and Oil Minister Delcy Rodríguez had made the proposal earlier on Monday. “Faced with the Prime Minister’s threat to turn Trinidad into the aircraft carrier of the US empire against Venezuela, against South America, there is only one alternative,” Maduro said in his weekly program on state TV. “It is completely suspended.” Maduro said he would deliver the proposal to the Supreme Court, National Assembly and State Council to receive their recommendations before taking “a structural measure” very soon. Trinidad needs Venezuelan gas to replenish supply to the industrial backbone of its fragile economy. However, when Rodríguez first made the threat on Monday, Trinidad’s Prime Minister Kamla Persad-Bissessar told AFP that the country’s future “does not depend on Venezuela and never has.” Trinidad’s government has developed a “hostile attitude” and a “warlike plan” against Venezuela, Rodríguez said during the afternoon, by “siding” with the US’s “military agenda.” Persad-Bissessar has previously said she welcomed the US offensive on drug traffickers, calling for them to be killed “violently.” Her posture has alienated Trinidad from other English-language countries in the Caribbean that have insisted on maintaining the region as a “zone of peace.” Venezuelan rhetoric is escalating as the US advances a military campaign, blowing up purported drug boats and pointing a finger at Maduro and, increasingly, Colombian President Gustavo Petro for allegedly flooding the US with fentanyl and cocaine. The US is ramping up its deployment in the southern Caribbean, with a

IT shortcuts curb AI returns

Organizations must ensure the infrastructure is AI ready Infrastructure is another area where Cisco found a major difference. Pacesetters are designing their networks for future demands. Seventy-one percent say their networks can scale instantly for new AI projects. Roughly three-quarters of pacesetters are investing in new data center capacity over the next year. Currently, about two-thirds say their infrastructure can accommodate AI workloads. Most pacesetters (93%) also have data systems that are fully prepared for AI, compared with 34% of other companies. About 76% have fully centralized their in-house data, while only 19% of other companies have done the same. Eighty-four percent report strong governance readiness, while 95% have mature processes to measure the impact of AI. If ever there was a technological shift that requires the right infrastructure, it’s AI. AI generates a significant amount of data, needs large amounts of processes and low latency, high-capacity networks. Historically, businesses could operate with networks that operated on the premise of “best effort,” but that’s no longer the case. From the data center to campus to branch offices, in most companies, the network will require a refresh. Scaling AI requires the right processes When it comes to being disciplined, 62% of pacesetters have an established process for generating, piloting, and scaling AI use cases. Only 13% of other organizations (non-pacesetters) have reached this level of maturity. Most pacesetters say their AI models achieve at least 75% accuracy. Almost half also expect a 50% to 100% return on investment (ROI) within a year, far above the average. Cisco notes that over the past six months, pressure has been building for companies to show tangible ROI. Executives and IT leaders are pushing for results, and so are competitors. By contrast, most other companies are in early stages of readiness. Although 83% plan to

Qualcomm goes all-in on inferencing with purpose-built cards and racks

From a strategy perspective, there is a longer term enterprise play here, noted Moor’s Kimball; Humain is Qualcomm’s first customer, and a cloud service provider (CSP) or hyperscaler will likely be customer number two. However, at some point, these rack-scale systems will find their way into the enterprise. “If I were the AI200 product marketing lead, I would be thinking about how I demonstrate this as a viable platform for those enterprise workloads that will be getting ‘agentified’ over the next several years,” said Kimball. It seems a natural step, as Qualcomm saw success with its AI100 accelerator, a strong inference chip, he noted. Right now, Nvidia and AMD dominate the training market, with CUDA and ROCm enjoying a “stickiness” with customers. “If I am a semiconductor giant like Qualcomm that is so good at understanding the performance-power balance, this inference market makes perfect sense to really lean in on,” said Kimball. He also pointed to the company’s plans to re-enter the datacenter CPU space with its Oryon CPU, which is featured in Snapdragon and loosely based on technology it acquired with its $1.4 billion Nuvia acquisition. Ultimately, Qualcomm’s move demonstrates how wide open the inference market is, said Kimball. The company, he noted, has been very good at choosing target markets and has seen success when entering those markets. “That the company would decide to go more ‘in’ on the inference market makes sense,” said Kimball. He added that, from an ROI perspective, inferencing will “dwarf” training in terms of volume and dollars.

AI data center building boom risks fueling future debt bust, bank warns

However, that’s only one part of the problem. Meeting the power demands of AI data centers will require the energy sector to make large investments. Then there’s data center demand for microprocessors, rare earth elements, and other valuable metals such as copper, which could, in a bust, make data centers the most expensively-assembled unwanted assets in history. “Financial stability consequences of an AI-related asset price fall could arise through multiple channels. If forecasted debt-financed AI infrastructure growth materializes, the potential financial stability consequences of such an event are likely to grow,” warned the BoE blog post. “For companies who depend on the continued demand for massive computational capacity to train and run inference on AI models, an algorithmic breakthrough or other event which challenges that paradigm could cause a significant re-evaluation of asset prices,” it continued. According to Matt Hasan, CEO of AI consultancy aiRESULTS, the underlying problem is the speed with which AI has emerged. “What we’re witnessing isn’t just an incremental expansion, it’s a rush to construct power-hungry, mega-scale data centers,” he told Network World. The dot.com reversal might be the wrong comparison; it dented the NASDAQ and hurt tech investment, but the damage to organizations investing in e-commerce was relatively limited. AI, by contrast, might have wider effects for large enterprises because so many have pinned their business prospects on its potential. “Your reliance on these large providers means you are indirectly exposed to the stability of their debt. If a correction occurs, the fallout can impact the services you rely on,” said Hasan.

Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

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

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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

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

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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