WoodMac: Oil sector investment at risk amid tariff uncertainty, price volatility

Stay Ahead, Stay ONMINE

WoodMac: Oil sector investment at risk amid tariff uncertainty, price volatility

Wood Mackenzie’s report paints a picture of an industry caught between increasing surety about longer-term demand for its products, but excess supply and uncertainty in the near term. At current prices near $65/bbl, margins are dented but not enough to force dramatic budget or development plan changes, Wood Mackenzie said. Companies are likely to delay […]

Wood Mackenzie’s report paints a picture of an industry caught between increasing surety about longer-term demand for its products, but excess supply and uncertainty in the near term.

At current prices near $65/bbl, margins are dented but not enough to force dramatic budget or development plan changes, Wood Mackenzie said. Companies are likely to delay growth capex and discretionary spending to preserve financial leverage and shareholder distributions, an approach possible due to increased portfolio and balance sheet flexibility built in since 2021.

Meantime, the supply chain is bracing for impact. The service sector is preparing for potentially reduced activity and downward pressure on costs. But tariffs could drive up the sector’s input costs, forcing service companies to choose between market share and margin erosion in well-supplied markets. Depending on how the situation evolves, tariffs could increase costs in the US by up to 6% onshore and 15% offshore, according to the report.

Moreover, near-term oil demand and OPEC+ market strategy concerns have caused oil and gas company share prices to fall. Capital allocation decisions are more difficult when prices, costs, and cash flow look volatile. Consequently, Wood Mackenzie anticipates a year-on-year decline in global upstream development spend for the first time since 2020.

“US tight oil operators would be among the first to curb investment if prices slide further, given their inherent activity flexibility,” said Ryan Duman, director of Americas upstream at Wood Mackenzie.

“But international projects are also feeling the pinch, with some already facing delays and budget revisions. More significant budgetary action would occur if oil settled below $60/bbl for a month or longer. A drop towards or below $50/bbl would prompt decisive action from most operators,” he said.

Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Proof-of-concept bypass shows weakness in Linux security tools, claims Israeli vendor

Falco was blind to Curing, while Defender was unable to detect either Curing or a range of other common malware. Tetragon, on the other hand, was able to detect io_uring, but only when using Kprobes and LSM hooks, which Armo said are not used by default. According to Armo, the

Lenovo targets AI workloads with massive storage update

These systems are aimed at enterprises that want to use both AI and virtualized systems, since AI hardware is not virtualized but bare-metal. For example, the all-new Lenovo ThinkAgile Converged Solution for VMware, which combines the enterprise-class features of the ThinkAgile VX Series with the data-management capabilities of the ThinkSystem

AI plus digital twins could be the pairing enterprises need

3. Link AI with transactional workflows The third point of cooperation is the linkage of AI with transactional workflows. Companies already have applications that take orders, ship goods, move component parts around, and so forth. It’s these applications that currently drive the commercial side of a business, but taking an

As clock ticks, vendors slowly patch critical flaw in AMI MegaRAC BMC firmware

Dell, on the other hand, has confirmed that its systems are unaffected by the MegaRAC issue, since it uses its own Integrated Dell Remote Access Controller (iDRAC) in its servers. How could attackers exploit the flaw? A week after the patch was posted by AMI in March, Eclypsium, the company

FirstEnergy faces minimal direct tariff impact, but ‘uncertainty’ weighs on customers: CEO

FirstEnergy faces little direct exposure to the Trump administration’s tariffs on foreign imports, said Brian Tierney, FirstEnergy chair, president and CEO, during a Thursday earnings call. The utility company’s tariff exposure represents less than 0.2% on its $28 billion, five-year capital investment program, according to Tierney. “Proactive management of our supply chain since COVID has resulted in a diversified supplier base with little exposure to single-source suppliers,” he said, noting that most of the company’s operations and maintenance expense is labor. However, Tierney said he agreed with comments made by Beth Hammack, president and CEO of the Federal Reserve Bank of Cleveland, that tariffs add economic uncertainty — making it difficult for people to make investment decisions. “We don’t anticipate a significant impact from an income standpoint in the near-term associated with the near-term uncertainty that we’re dealing with,” Tierney said in response to an analyst question about a possible economic slowdown. “But the quicker there’s certainty from an investment cycle standpoint, I think the quicker we’ll be able to see people be able to make those investment decisions and get on with investing in their business, whatever the answer is from a tariff standpoint.” A report released Tuesday by the Cleveland Fed found that 64% of respondents to a February survey expected that their business would be affected by import tariffs. “Sizable majorities of respondents expected tariffs to increase both input costs and selling prices while decreasing demand for their products and services,” Cleveland Fed analysts said in the report. FirstEnergy’s industrial sales fell about 6% to 12.8 million MWh in the first quarter, down from 13.6 million MWh in the third quarter last year, according to the company’s earnings presentation. The dip is mainly from steel manufacturers slowing production related to automotive demand, said Jon Taylor, senior vice

PG&E foresees ‘bright future’ with lower prices, higher demand

Dive Brief: Pacific Gas & Electric expects to file a rate case with its lowest requested rate increase in a decade as the company continues to make strides toward cutting costs and improving its credit rating, CEO Patti Poppe told investors during a Thursday earnings call. Increased demand from prospective data center customers — which grew sharply — should help the company reduce residential rates, and PG&E does not expect to be heavily impacted by tariffs, according to Poppe. Company leaders held up a recent rating upgrade by Moody’s as proof of their progress, but cautioned that further improvements in the company’s credit score are unlikely pending legislation to reform California’s overwhelmed wildfire insurance fund. Dive Insight: With growing demand and possible legislative reforms in the works, Poppe expressed optimism about PG&E’s future even though the San Francisco-based company saw its first-quarter earnings decline slightly. Customers may remain skeptical of the company’s ability to deliver, but PG&E is on a path toward lower costs and more modest electric bills, she said. “We’re interrupting a pattern here in California for affordability for customers,” she said. “We know our customers don’t feel that yet, so there is a doubt that we can deliver on this but we are able to deliver, and we’ve delivered this year.” The company’s upcoming general rate case, which PG&E plans to initiate next month, will request the lowest increase in electric rates in a decade, Poppe said — and it doesn’t include the effects of other potential cost-saving developments, including the improved credit rating by Moody’s and growing electrical demand. PG&E’s regulatory framework, Poppe said, should allow the company to cut overall customer bills by 1% to 2% for every gigawatt of new demand from data centers. PG&E’s data center pipeline grew from 5.5 GW at the beginning

WTI Ends Higher But Logs Weekly Loss

Oil edged higher in a day of listless trading as investors parsed conflicting messaging on the progress of trade talks between the US and China. West Texas Intermediate futures rose to settle near $63 a barrel, but still notched their third weekly loss in the past four. Chinese authorities are weighing removing additional levies on a number of products including ethane, according to people familiar with the matter, as economic costs mount for certain industries. Shares in China’s top buyers of the fuel from the US jumped. Still, an agreement on trade between the US and China appears far off. President Donald Trump said Thursday that his administration was talking with China about trade, despite Beijing earlier denying the existence of negotiations and demanding that unilateral tariffs be revoked. The president later said that he wouldn’t drop tariffs on China unless “something substantial” is offered in return. Oil has dropped sharply this month on concerns that Trump’s sweeping tariffs and retaliatory measures from trading partners including China will cripple economic activity and throttle energy demand. In an effort to reassure US oil firms, Energy Secretary Chris Wright said that the trade turmoil will be fleeting and that the administration fully supports more crude output. “Our president is very clear and he wants lower energy prices,” Wright said during an interview with Bloomberg Television at an energy conference in Oklahoma City. Oil prices at $50 per barrel “in today’s world probably is not sustainable for our producers in this country.” The president “wants American industry and American consumers to thrive,” he added. The OPEC+ alliance has added to bearish headwinds by ramping up idled oil production, stoking fears of an oversupply. The group will meet on May 5 to discuss its output plans for June. Still, some metrics are pointing to

Trade War Is Diverting USA Petroleum Gas Cargoes Away From China

Multiple carriers of petroleum-based gases traveling from the US to China have begun diverting to other countries due to the intensifying trade war between the world’s two largest economies. Four cargoes of propane have shifted their routes from China to alternate destinations over the past week, bound for countries including Japan and South Korea, according to a report from analytics firm Vortexa. At least one cargo of ethane — which is used in plastics production — has been scrapped entirely, according to a person familiar with the matter. The diversions show the disruption to supply chains caused by the trade fight between the US and China, historically a major buyer of US ethane and petroleum gases. President Donald Trump has levied 145% tariffs on most US imports from China, and the US Trade Representative more recently imposed steep fees on Chinese-linked vessels seeking to access American ports. Eight Very Large Gas Carriers carrying US LPG were still on course for China as of this week, while the four diversions have all been recorded since April 17, according to Vortexa. Diverted vessels include the Zakher, Maple Gas, BW Gemini and Eiger Explorer, all departing from the US Gulf Coast. The G. Arete, a propane carrier, diverted to South Korea from China, while a chemical tanker named STI Notting Hill is also rerouting to South Korea, Vortexa said. The US exported about 310,000 barrels of propane to China per day in 2024, double the volume from a year earlier, according to East Daley Analytics. Spot ethane shipments may continue to be affected by the trade war, while committed cargoes are harder to unwind, the person said. Asia-bound flows of ethylene — used in plastics and industrial solvents — have already slowed because of seasonal factors but may be further reduced by the tariffs, the

Valero to shutter at least one of its California refineries

Lengthening legislative shadow Valero’s proposal for the Benicia refinery follows Phillips 66 Co.’s October 2024 confirmation that it will permanently cease conventional crude oil processing operations its 138,700-b/d dual-sited refinery in Los Angeles by yearend 2025 amid the operator’s determination that market conditions will prevent the long-term viability and competitiveness of the manufacturing site (OGJ Online, Oct. 17, 2024). Announcement of the Los Angeles refinery closure came on the heels of California Gov. Gavin Newsom’s Oct. 14, 2024, signing of legislation aimed at making the state’s oil refiners manage California’s gasoline supplies more responsibly to prevent price spikes at the pump. The legislation specifically provides the CEC more tools for requiring petroleum refiners to backfill supplies and plan for maintenance downtime as a means of helping prevent gasoline-price spikes that cost Californians upwards of $2 billion in 2023, Newsom’s office said. Introduced in early September 2024 in response to Newsom’s late-August proclamation convening the state’s legislature into special session “to take on Big Oil’s gas-price spikes,” the new legislation allows the state to require that refiners maintain a minimum inventory of fuel to avoid supply shortages that “create higher gasoline prices for consumers and higher profits for the industry,” the governor’s office said. While Valero did not reveal in its April 2025 statement any specific reasons for its decision on the Benicia refinery, in the wake of the market announcement, Brian W. Jones (R-Calif.) and Vince Fong (R-Calif.) both attributed the pending refinery closure to the legislation and policies heralded by Newsom and state regulatory departments. “Valero intends to shut down its Benicia refinery thanks to Newsom and radical Democrats’ extreme regulations and hostile business climate,” Jones said on Apr. 16, citing Phillips 66’s decision on the Los Angeles refinery and Chevron Corp.’s relocation of headquarters from San Ramon, Calif.,

US BOEM begins process to replace current OCS lease sale plan

US Interior Secretary Doug Burgum directed the Bureau of Ocean Energy Management (BOEM) to start developing a plan for offshore oil and gas lease sales on the US Outer Continental Shelf (OCS), including likely sales in a newly established 27h OCS planning area offshore Alaska in the High Arctic. The 11th National OCS program will replace the current 10th Program (2024–29), which includes only three oil and gas lease sales over 5 years—all in the Gulf, Burgum said in a release Apr. 18. BOEM will work to complete those sales, while it begins to develop the new program, he said. Earlier this month, Burgum directed BOEM to move forward a lease sale in the Gulf, starting with publication in June 2025 of a notice of sale. BOEM will soon publish in the Federal Register a request for information and comments which starts a 45-day public comment period that serves as the initial step in the multi-year planning process that details lease sales BOEM will hold in the coming years. The Federal Register notice will also outline BOEM’s new jurisdiction over the High Arctic planning area offshore Alaska, as well as new boundaries for existing planning areas, Interior noted. The request for information will not propose a specific timeline for future lease sales or outline the potential sale areas. Instead, it invites stakeholders to provide recommendations for leasing opportunities and raise concerns about offshore leasing. BOEM manages 3.2 billion acres in the OCS, including 2,227 active oil and gas leases covering about 12.1 million acres in OCS regions. Of these, 469 leases are currently producing oil and gas. BOEM earlier in April increased its estimate of oil and gas reserves in the US Gulf’s OCS by 1.30 billion boe from its 2021 estimate, bringing the total reserve estimate to 7.04 billion

Deep Data Center: Neoclouds as the ‘Picks and Shovels’ of the AI Gold Rush

In 1849, the discovery of gold in California ignited a frenzy, drawing prospectors from around the world in pursuit of quick fortune. While few struck it rich digging and sifting dirt, a different class of entrepreneurs quietly prospered: those who supplied the miners with the tools of the trade. From picks and shovels to tents and provisions, these providers became indispensable to the gold rush, profiting handsomely regardless of who found gold. Today, a new gold rush is underway, in pursuit of artificial intelligence. And just like the days of yore, the real fortunes may lie not in the gold itself, but in the infrastructure and equipment that enable its extraction. This is where neocloud players and chipmakers are positioned, representing themselves as the fundamental enablers of the AI revolution. Neoclouds: The Essential Tools and Implements of AI Innovation The AI boom has sparked a frenzy of innovation, investment, and competition. From generative AI applications like ChatGPT to autonomous systems and personalized recommendations, AI is rapidly transforming industries. Yet, behind every groundbreaking AI model lies an unsung hero: the infrastructure powering it. Enter neocloud providers—the specialized cloud platforms delivering the GPU horsepower that fuels AI’s meteoric rise. Let’s examine how neoclouds represent the “picks and shovels” of the AI gold rush, used for extracting the essential backbone of AI innovation. Neoclouds are emerging as indispensable players in the AI ecosystem, offering tailored solutions for compute-intensive workloads such as training large language models (LLMs) and performing high-speed inference. Unlike traditional hyperscalers (e.g., AWS, Azure, Google Cloud), which cater to a broad range of use cases, neoclouds focus exclusively on optimizing infrastructure for AI and machine learning applications. This specialization allows them to deliver superior performance at a lower cost, making them the go-to choice for startups, enterprises, and research institutions alike.

Soluna Computing: Innovating Renewable Computing for Sustainable Data Centers

Dorothy 1A & 1B (Texas): These twin 25 MW facilities are powered by wind and serve Bitcoin hosting and mining workloads. Together, they consumed over 112,000 MWh of curtailed energy in 2024, demonstrating the impact of Soluna’s model. Dorothy 2 (Texas): Currently under construction and scheduled for energization in Q4 2025, this 48 MW site will increase Soluna’s hosting and mining capacity by 64%. Sophie (Kentucky): A 25 MW grid- and hydro-powered hosting center with a strong cost profile and consistent output. Project Grace (Texas): A 2 MW AI pilot project in development, part of Soluna’s transition into HPC and machine learning. Project Kati (Texas): With 166 MW split between Bitcoin and AI hosting, this project recently exited the Electric Reliability Council of Texas, Inc. planning phase and is expected to energize between 2025 and 2027. Project Rosa (Texas): A 187 MW flagship project co-located with wind assets, aimed at both Bitcoin and AI workloads. Land and power agreements were secured by the company in early 2025. These developments are part of the company’s broader effort to tackle both energy waste and infrastructure bottlenecks. Soluna’s behind-the-meter design enables flexibility to draw from the grid or directly from renewable sources, maximizing energy value while minimizing emissions. Competition is Fierce and a Narrower Focus Better Serves the Business In 2024, Soluna tested the waters of providing AI services via a GPU-as-a-Service through a partnership with HPE, branded as Project Ada. The pilot aimed to rent out cloud GPUs for AI developers and LLM training. However, due to oversupply in the GPU market, delayed product rollouts (like NVIDIA’s H200), and poor demand economics, Soluna terminated the contract in March 2025. The cancellation of the contract with HPE frees up resources for Soluna to focus on what it believes the company does best: designing

Quiet Genius at the Neutral Line: How Onics Filters Are Reshaping the Future of Data Center Power Efficiency

Why Harmonics Matter In a typical data center, nonlinear loads—like servers, UPS systems, and switch-mode power supplies—introduce harmonic distortion into the electrical system. These harmonics travel along the neutral and ground conductors, where they can increase current flow, cause overheating in transformers, and shorten the lifespan of critical power infrastructure. More subtly, they waste power through reactive losses that don’t show up on a basic utility bill, but do show up in heat, inefficiency, and increased infrastructure stress. Traditional mitigation approaches—like active harmonic filters or isolation transformers—are complex, expensive, and often require custom integration and ongoing maintenance. That’s where Onics’ solution stands out. It’s engineered as a shunt-style, low-pass filter: a passive device that sits in parallel with the circuit, quietly siphoning off problematic harmonics without interrupting operations. The result? Lower apparent power demand, reduced electrical losses, and a quieter, more stable current environment—especially on the neutral line, where cumulative harmonic effects often peak. Behind the Numbers: Real-World Impact While the Onics filters offer a passive complement to traditional mitigation strategies, they aren’t intended to replace active harmonic filters or isolation transformers in systems that require them—they work best as a low-complexity enhancement to existing power quality designs. LoPilato says Onics has deployed its filters in mission-critical environments ranging from enterprise edge to large colos, and the data is consistent. In one example, a 6 MW data center saw a verified 9.2% reduction in energy consumption after deploying Onics filters at key electrical junctures. Another facility clocked in at 17.8% savings across its lighting and support loads, thanks in part to improved power factor and reduced transformer strain. The filters work by targeting high-frequency distortion—typically above the 3rd harmonic and up through the 35th. By passively attenuating this range, the system reduces reactive current on the neutral and helps stabilize

New IEA Report Contrasts Energy Bottlenecks with Opportunities for AI and Data Center Growth

Artificial intelligence has, without question, crossed the threshold—from a speculative academic pursuit into the defining infrastructure of 21st-century commerce, governance, and innovation. What began in the realm of research labs and open-source models is now embedded in the capital stack of every major hyperscaler, semiconductor roadmap, and national industrial strategy. But as AI scales, so does its energy footprint. From Nvidia-powered GPU clusters to exascale training farms, the conversation across boardrooms and site selection teams has fundamentally shifted. It’s no longer just about compute density, thermal loads, or software frameworks. It’s about power—how to find it, finance it, future-proof it, and increasingly, how to generate it onsite. That refrain—“It’s all about power now”—has moved from a whisper to a full-throated consensus across the data center industry. The latest report from the International Energy Agency (IEA) gives this refrain global context and hard numbers, affirming what developers, utilities, and infrastructure operators have already sensed on the ground: the AI revolution will be throttled or propelled by the availability of scalable, sustainable, and dispatchable electricity. Why Energy Is the Real Bottleneck to Intelligence at Scale The major new IEA report puts it plainly: The transformative promise of AI will be throttled—or unleashed—by the world’s ability to deliver scalable, reliable, and sustainable electricity. The stakes are enormous. Countries that can supply the power AI craves will shape the future. Those that can’t may find themselves sidelined. Importantly, while AI poses clear challenges, the report emphasizes how it also offers solutions: from optimizing energy grids and reducing emissions in industrial sectors to enhancing energy security by supporting infrastructure defenses against cyberattacks. The report calls for immediate investments in both energy generation and grid capabilities, as well as stronger collaboration between the tech and energy sectors to avoid critical bottlenecks. The IEA advises that, for countries

Colorado Eyes the AI Data Center Boom with Bold Incentive Push

Even as states work on legislation to limit data center development, it is clear that some locations are looking to get a bigger piece of the huge data center spending that the AI wave has created. It appears that politicians in Colorado took a look around and thought to themselves “Why is all that data center building going to Texas and Arizona? What’s wrong with the Rocky Mountain State?” Taking a page from the proven playbook that has gotten data centers built all over the country, Colorado is trying to jump on the financial incentives for data center development bandwagon. SB 24-085: A Statewide Strategy to Attract Data Center Investment Looking to significantly boost its appeal as a data center hub, Colorado is now considering Senate Bill 24-085, currently making its way through the state legislature. Sponsored by Senators Priola and Buckner and Representatives Parenti and Weinberg, this legislation promises substantial economic incentives in the form of state sales and use tax rebates for new data centers established within the state from fiscal year 2026 through 2033. Colorado hopes to position itself strategically to compete with neighboring states in attracting lucrative tech investments and high-skilled jobs. According to DataCenterMap.com, there are currently 53 data centers in the state, almost all located in the Denver area, but they are predominantly smaller facilities. In today’s era of massive AI-driven hyperscale expansion, Colorado is rarely mentioned in the same breath as major AI data center markets. Some local communities have passed their own incentive packages, but SB 24-085 aims to offer a unified, statewide framework that can also help mitigate growing NIMBY (Not In My Backyard) sentiment around new developments. The Details: How SB 24-085 Works The bill, titled “Concerning a rebate of the state sales and use tax paid on new digital infrastructure

Wonder Valley and the Great AI Pivot: Kevin O’Leary’s Bold Data Center Play

Data Center World 2025 drew record-breaking attendance, underscoring the AI-fueled urgency transforming infrastructure investment. But no session captivated the crowd quite like Kevin O’Leary’s electrifying keynote on Wonder Valley—his audacious plan to build the world’s largest AI compute data center campus. In a sweeping narrative that ranged from pandemic pivots to stranded gas and Branson-brand inspiration, O’Leary laid out a real estate and infrastructure strategy built for the AI era. A Pandemic-Era Pivot Becomes a Case Study in Digital Resilience O’Leary opened with a Shark Tank success story that doubled as a business parable. In 2019, a woman-led startup called Blueland raised $50 million to eliminate plastic cleaning bottles by shipping concentrated cleaning tablets in reusable kits. When COVID-19 shut down retail in 2020, her inventory was stuck in limbo—until she made an urgent call to O’Leary. What followed was a high-stakes, last-minute pivot: a union-approved commercial shoot in Brooklyn the night SAG-AFTRA shut down television production. The direct response ad campaign that resulted would not only liquidate the stranded inventory at full margin, but deliver something more valuable—data. By targeting locked-down consumers through local remnant TV ad slots and optimizing by conversion, Blueland saw unheard-of response rates as high as 17%. The campaign turned into a data goldmine: buyer locations, tablet usage patterns, household sizes, and contact details. Follow-up SMS campaigns would drive 30% reorders. “It built such a franchise in those 36 months,” O’Leary said, “with no retail. Now every retailer wants in.” The lesson? Build your infrastructure to control your data, and you build a business that scales even in chaos. This anecdote set the tone for the keynote: in a volatile world, infrastructure resilience and data control are the new core competencies. The Data Center Power Crisis: “There Is Not a Gig on the Grid” O’Leary

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

Stay Ahead, Stay ONMINE