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Cisco unveils integrated edge platform for AI

Announced at Cisco’s Partner Summit, Unified Edge will likely be part of many third-party packages that can be configured in a variety of ways, Cisco stated. “The platform is customer definable. For example, if a customer has a workload and they’ve decided they want to use Nutanix, they can go ahead and work with their […]

Announced at Cisco’s Partner Summit, Unified Edge will likely be part of many third-party packages that can be configured in a variety of ways, Cisco stated.

“The platform is customer definable. For example, if a customer has a workload and they’ve decided they want to use Nutanix, they can go ahead and work with their channel partner to configure the server with the amount of memory and storage that they would want. Then we are going to ship that customized, well-unified edge system,” Foster said. “It’s critical for edge locations and the customers that we’re working with, that they have flexibility and can easily work with someone in the independent software vendor ecosystem around edge and that customers can grow as their needs increase over the next 10 years with the options available in this chassis.”

Flexibility is key as enterprises grow not only AI applications but also other edge applications, experts say.

“A highly distributed IT ecosystem introduces new challenges in building, deploying, and maintaining remote infrastructure. The scale and reach of edge deployments creates a significant burden on IT organizations,” IDC wrote in a white paper on edge computing. “Without rigorous management, data security is at risk. And edge environments often come with unavoidable physical security risks. For these reasons, infrastructure that is designed to streamline and simplify deployment is preferred. Modernized edge platforms automate management, ensuring that configurations remain intact and that systems can remain updated even when no IT staff is physically present.”

“There are a variety of factors driving edge transformation. Most notable are AI workloads, and particularly those that are latency sensitive, such as real-time data processing for fraud detection, machine sensors and video analytics in manufacturing for quality control and predictive maintenance, and in-store retail analytics to create new customer experiences,” IDC wrote. “New AI workloads at the edge require high performance and better resilience, with critical operations and business processes relying on edge infrastructure. Greater efficiency and cost optimization are key benefits and will drive continued deployment of new edge use cases.”

Cisco Unified Edge can be ordered now and will ship in December, Foster said.

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Cisco unveils integrated edge platform for AI

Announced at Cisco’s Partner Summit, Unified Edge will likely be part of many third-party packages that can be configured in a variety of ways, Cisco stated. “The platform is customer definable. For example, if a customer has a workload and they’ve decided they want to use Nutanix, they can go

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Infoblox bolsters Universal DDI Platform with multi-cloud integrations

Universal DDI for Microsoft Management integration enables enterprises to gain control of their DNS and DHCP by centrally managing DNS and DHCP hosted on Microsoft server platforms. Integration with Google Cloud Internal Range applies consistent IPAM policies across Google Cloud, on-premises, and other cloud environments, which helps enterprise IT to

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Agentic AI: What now, what next?

Agentic AI burst onto the scene with its promises of streamliningoperations and accelerating productivity. But what’s real and what’s hype when it comes to deploying agentic AI? This Special Report examines the state of agentic AI, the challenges organizations are facing in deploying it, and the lessons learned from success

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Adnoc CEO Says AI Raises Energy Investment Needs to $4T

The global energy industry needs annual investment of $4 trillion as the boom in data centers and artificial intelligence increases demand, according to Sultan Al Jaber, head of the biggest crude producer in the United Arab Emirates. Long-term demand growth will outlast immediate concerns over an oil supply glut, Al Jaber, chief executive officer of Abu Dhabi National Oil Co., said at a conference in Abu Dhabi on Monday. Investors will need to develop the resources to drive the coming data boom, including revamping power grids, he said. Oil producers like the UAE are boosting output capacity, even as most analysts warn of a coming glut in crude supply that will weigh further on prices next year. Brent crude is down nearly 13% so far this year. Geopolitical concerns that have delayed shipments and threatened supply disruptions have prevented prices from dropping further. “Near-term uncertainty is real, while long-term demand remains strong,” Al Jaber said. “Our response to meet that demand should focus on data, not the drama.”  In a nod to the short-term weakness in markets, the OPEC+ producers group said on Sunday that it will pause production increases during the first quarter of next year after a modest increase this month and in December. Oil demand is set to remain above 100 million barrels a day beyond 2040, requiring added investment, the CEO said. The UAE aims to play a role in this energy investment push, with Al Jaber declaring that the country is “open for business” and that Adnoc’s international arm XRG is seeking more deals.

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Oil Holds Steady on OPEC+ Pause

Oil was little changed Monday as traders weighed the OPEC+ alliance’s plan to pause its output revival next quarter on anticipation demand will slow, while the market is seen headed for oversupply. West Texas Intermediate rose about 0.1% to settle above $61 a barrel after fluctuating between small gains and losses through the day, extending a string of marginal increases. The Organization of the Petroleum Exporting Countries and its partners said the decision on Sunday to halt production hikes from January reflects an expectation for a seasonal slowdown. The move comes against a backdrop of widespread forecasts for excess supplies next year that could weigh down prices. The US benchmark has slumped about 9% over the past three months as OPEC+ ramped up output in an apparent effort to regain market share, while producers outside the group also increased production. Prices recently bounced from a five-month low after tighter US sanctions on two major Russian oil producers over the war in Ukraine raised some questions about supply from Moscow. “The decision to halt quota hikes during 1Q does not materially change our production forecasts but still sends an important signal,” Morgan Stanley analysts including Martijn Rats and Charlotte Firkins wrote. “The group is still adjusting supply in response to market conditions.” The eight key members of OPEC+ are left with roughly 1.2 million barrels a day of their current supply tranche still to restore. Actual output increases have fallen short of advertised volumes, as some members offset earlier overproduction and others struggle to pump more. Following the OPEC+ move, Morgan Stanley raised its near-term price forecast for Brent while also maintaining a warning for a “substantial surplus.” The United Arab Emirates, meanwhile, on Monday added to the chorus of producers who have come out to downplay glut concerns. Traders will

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Gas continues to dominate Entergy plans as data center pipeline grows

7-12 GW Data center pipeline, up from 5-10 GW last quarter. 4.5 GW New power generating secured for “large growth opportunities.” $41 billion Estimated capital spending through 2029. Pending and signed hyperscaler deals Entergy is a vertically-integrated electric utility with five operating companies in four states: Arkansas, Louisiana, Mississippi and Texas. Its weather-adjusted retail sales rose 4.4% compared to last year. Profit increased from $645 million in the third quarter of 2024 to $694 million in the third quarter of 2025. In 2024, commercial and industrial customers made up 69% of Entergy’s sales, which were concentrated in Louisiana.  The company has agreements for several notable large load projects with Google and Meta. In general, it expects substantial load growth from commercial and industrial customers through 2029, though not the breakneck pace utilities like Dominion Energy expect in data center hotspots such as northern Virginia. In its third-quarter investor update, Entergy said its data center customer pipeline increased 2 GW from the previous quarter to land in the 7 GW to 12 GW range. Also in the quarter, Energy secured 4.5 GW of power generation equipment to serve new load expected to come online this decade. In August, the Louisiana Public Service Commission approved the generation and transmission resources needed to support Meta’s planned 2-GW campus in northeastern Louisiana. Those include three combined-cycle gas plants with combined nameplate capacity of about 2.2 GW. As part of the same proceeding, the commission also authorized Entergy to procure up to 1.5 GW of solar resources for the project. Entergy executives said Wednesday that the Meta agreement and additional expected load growth are reflected in the utility’s five-year capital plan, which lays out $41 billion in estimated spending through 2029. Entergy has also submitted an application to the Arkansas Public Service Commission for the Cypress

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Ukraine Claims Strike at Rosneft’s Saratov Refinery

Ukraine claimed another strike at a key Rosneft PJSC refinery in southwestern Russia as pressure mounts to curb Moscow’s revenues from the oil industry.  The overnight attack caused fires in the area of refining units in Saratov, Ukrainian General Staff said in a statement on Telegram. The strike was delivered by the Ukrainian Unmanned Systems Forces, according to a separate statement. Bloomberg News was not able to independently verify the strike or the extent of the damage. Rosneft didn’t immediately respond to a Bloomberg request for comment. The Saratov refinery has been a target of multiple drone attacks this year as Kyiv stepped up its efforts to cripple income that has helped fund the Russian invasion, while President Volodymyr Zelenskiy urged Western nations to sanction Russian oil companies and its dark fleet of oil tankers.  Kyiv has claimed around 160 successful strikes at Russian refineries and oil infrastructure this year, according to Vasyl Malyuk, chairman of the Ukrainian Security Service. Twenty facilities including refineries and terminals were struck in September and October, he said on Friday.  The refinery in Saratov has the capacity to process about 140,000 barrels of crude a day and is a key supplier of gasoline and diesel fuel to Russia’s European regions. It was sanctioned by the US last month as part of a package of measures targeting Rosneft and Lukoil PJSC. This was the seventh attack on the refinery so far this year. 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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BP Dubs Initial Results at Bumerangue ‘Extremely Encouraging’

In a release sent to Rigzone recently, Gordon Birrell, BP’s executive vice president for production and operations, said “initial results and analysis” at the Bumerangue find offshore Brazil “are extremely encouraging”. “2025 has seen significant strategic progress across BP’s upstream with record plant reliability, six major project start-ups, five more sanctioned and a string of exploration discoveries including Bumerangue,” Birrell said in the release. “We are still in the exploration phase for Bumerangue, however, initial results and analysis are extremely encouraging as they indicate a very large hydrocarbon column and a significant volume of liquids in the reservoir,” he added. “We are pleased about what we have seen to date and our confidence in the potential of this field has increased,” Birrell continued. “We have a team in place and are accelerating work on proposed appraisal activities and potential development concepts, which will include the potential for an early production system,” Birrell went on to state. In the release, BP noted that, following the announcement of the Bumerangue find back in August, initial laboratory and pressure gradient analysis “has confirmed the presence of a ~1,000 meter gross hydrocarbon column, including a ~100 meter gross oil column and a ~900 meter gross liquids rich gas-condensate column”.  “Given the presence of liquids across the entire hydrocarbon column, the high-quality rock properties observed, and BP’s extensive technology and deepwater developments experience, BP believes that the carbon dioxide in the reservoir can be managed,” the company said in the release. BP went on to state that it is continuing laboratory testing and other analysis to determine fluid characteristics, gas-to-oil and condensate-to-gas ratios, and an estimate of in-place volumes. The company said in the release that it will provide an update “in due course”. “Planning of appraisal activities is ongoing with well activities expected to

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The era of ‘free’ excess renewable energy is over

Thomas Sisto is co-founder and CEO of XL Batteries. Explosive growth in electricity demand is poised to consume any surplus that once was wasted.  We all know what is coming: Forecasts expect data centers alone to increase their power consumption by 165% in 2030. At that point, 50 GW of the 100 GW of predicted new U.S. peak demand will come from data centers. Combined with broader “electrification of everything” policies and increasingly complex grid dynamics, this growth is triggering a seismic economic shift. Wasting power will soon become an unaffordable luxury of the past. This shift demands a hard look at long-duration energy storage, or LDES, which will be critical for grid reliability and affordability as we integrate more renewables. The U.S. Department of Energy found that up to 460 GW of LDES capacity may be necessary by 2050. Not all LDES technologies are created equal, however. Round-trip efficiency, or RTE, will be a key determinant of which technologies can deliver at the scale and cost we need and which ones will perpetuate the pattern of waste.  A dangerous misconception persists that renewable energy is sometimes wasted or is so cheap that RTE doesn’t matter. This assumption ignores the true economics, which the data reveal. The industry must prioritize high-efficiency LDES technologies now to achieve both our climate goals and economic viability. Scale redefines the efficiency equation Here’s what the efficiency skeptics miss: Scale changes everything. Losing 50% of the energy stored in a home battery system is inconvenient but manageable; a 50% loss of stored energy at the grid scale — amounting to gigawatt-hours of stored energy — is catastrophic. Consider the difference between a leaking glass of water and a leaking Hoover Dam: The sheer volume of the dam’s water amplifies the loss.  This becomes even more critical given that the

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OpenAI spends even more money it doesn’t have

The aim, said Gogia, “is continuity, not cost efficiency. These deals are forward leaning, relying on revenue forecasts that remain speculative. In that context, OpenAI must continue to draw heavily on outside capital, whether through venture rounds, debt, or a future public offering.” He pointed out, “the company’s recent legal and corporate restructuring was designed to open the doors to that capital. Removing Microsoft’s exclusivity makes room for more vendors but also signals that no one provider can meet OpenAI’s demands. In several cases, suppliers are stepping in with financing arrangements that link product sales to future performance. While these strategies help close funding gaps, they introduce fragility. What looks like revenue is often pre-paid consumption, not realized margin.” Execution risks, he said, add to the concern. “Building and energizing enough data centers to meet OpenAI’s projected needs is not a function of ambition alone. It requires grid access, cooling capacity, and regional stability. Microsoft has acknowledged that it lacks the power infrastructure to fully deploy the GPUs it owns. Without physical readiness, all of these agreements sit on shaky ground.” Lots of equity swapping going on Scott Bickley, advisory fellow at Info-Tech Research Group, said he has not only been astounded by the funding announcements over the last few months, but is also appalled, primarily, he said, “because of the disconnect to what this does to the underlying technology stocks and their market prices versus where the technology is at from a development and ROI perspective … and from a boots on the ground perspective.” He added that while the financial pledges involve “huge, staggering numbers, most of them are tied up in ways that are not necessarily going to require all the cash to come from OpenAI. In a lot of cases, there is equity swapping. You have

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Verizon to build high-capacity fiber network to link AWS AI data centers

“AI will be essential to the future of business and society, driving innovation that demands a network to match,” Scott Lawrence, senior vice president and chief product officer at Verizon Business said in a statement. “This deal with Amazon demonstrates our continued commitment to meet the growing demands of AI workloads for the businesses and developers building our future.” This is not the first time that two companies have partnered. Verizon has previously adopted AWS as a preferred public cloud provider for its digital transformation efforts. The collaboration also extends to joint development of private mobile edge computing solutions, delivering secure, dedicated connectivity for enterprise customers. These efforts have been targeted at industries such as manufacturing, healthcare, retail, and entertainment.

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Supermicro Unveils Data Center Building Blocks to Accelerate AI Factory Deployment

Supermicro has introduced a new business line, Data Center Building Block Solutions (DCBBS), expanding its modular approach to data center development. The offering packages servers, storage, liquid-cooling infrastructure, networking, power shelves and battery backup units (BBUs), DCIM and automation software, and on-site services into pre-validated, factory-tested bundles designed to accelerate time-to-online (TTO) and improve long-term serviceability. This move represents a significant step beyond traditional rack integration; a shift toward a one-stop, data-center-scale platform aimed squarely at the hyperscale and AI factory market. By providing a single point of accountability across IT, power, and thermal domains, Supermicro’s model enables faster deployments and reduces integration risk—the modern equivalent of a “single throat to choke” for data center operators racing to bring GB200/NVL72-class racks online. What’s New in DCBBS DCBBS extends Supermicro’s modular design philosophy to an integrated catalog of facility-adjacent building blocks, not just IT nodes. By including critical supporting infrastructure—cooling, power, networking, and lifecycle software—the platform helps operators bring new capacity online more quickly and predictably. According to Supermicro, DCBBS encompasses: Multi-vendor AI system support: Compatibility with NVIDIA, AMD, and Intel architectures, featuring Supermicro-designed cold plates that dissipate up to 98% of component-level heat. In-rack liquid-cooling designs: Coolant distribution manifolds (CDMs) and CDUs rated up to 250 kW, supporting 45 °C liquids, alongside rear-door heat exchangers, 800 GbE switches (51.2 Tb/s), 33 kW power shelves, and 48 V battery backup units. Liquid-to-Air (L2A) sidecars: Each row can reject up to 200 kW of heat without modifying existing building hydronics—an especially practical design for air-to-liquid retrofits. Automation and management software: SuperCloud Composer for rack-scale and liquid-cooling lifecycle management SuperCloud Automation Center for firmware, OS, Kubernetes, and AI pipeline enablement Developer Experience Console for self-service workflows and orchestration End-to-end services: Design, validation, and on-site deployment options—including four-hour response service levels—for both greenfield builds

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Investments Anchor Vertiv’s Growth Strategy as AI-Driven Data Center Orders Surge 60% YoY

New Acquisitions and Partner Awards Vertiv’s third-quarter financial performance was underscored by a series of strategic acquisitions and ecosystem recognitions that expand the company’s technological capabilities and market reach amid AI-driven demand. Acquisition of Waylay NV: AI and Hyperautomation for Infrastructure Intelligence On August 26, Vertiv announced its acquisition of Waylay NV, a Belgium-based developer of generative AI and hyperautomation software. The move bolsters Vertiv’s portfolio with AI-driven monitoring, predictive services, and performance optimization for digital infrastructure. Waylay’s automation platform integrates real-time analytics, orchestration, and workflow automation across diverse connected assets and cloud services—enabling predictive maintenance, uptime optimization, and energy management across power and cooling systems. “With the addition of Waylay’s technology and software-focused team, Vertiv will accelerate its vision of intelligent infrastructure—data-driven, proactive, and optimized for the world’s most demanding environments,” said CEO Giordano Albertazzi. Completion of Great Lakes Acquisition: Expanding White Space Integration Just days earlier, as alluded to above, Vertiv finalized its $200 million acquisition of Great Lakes Data Racks & Cabinets, a U.S.-based manufacturer of enclosures and integrated rack systems. The addition expands Vertiv’s capabilities in high-density, factory-integrated white space solutions; bridging power, cooling, and IT enclosures for hyperscale and edge data centers alike. Great Lakes’ U.S. and European manufacturing footprint complements Vertiv’s global reach, supporting faster deployment cycles and expanded configuration flexibility.  Albertazzi noted that the acquisition “enhances our ability to deliver comprehensive infrastructure solutions, furthering Vertiv’s capabilities to customize at scale and configure at speed for AI and high-density computing environments.” 2024 Partner Awards: Recognizing the Ecosystem Behind Growth Vertiv also spotlighted its partner ecosystem in August with its 2024 North America Partner Awards. The company recognized 11 partners for 2024 performance, growth, and AI execution across segments: Partner of the Year – SHI for launching a customer-facing high-density AI & Cyber Labs featuring

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QuEra’s Quantum Leap: From Neutral-Atom Breakthroughs to Hybrid HPC Integration

The race to make quantum computing practical – and commercially consequential – took a major step forward this fall, as Boston-based QuEra Computing announced new research milestones, expanded strategic funding, and an accelerating roadmap for hybrid quantum-classical supercomputing. QuEra’s Chief Commercial Officer Yuval Boger joined the Data Center Frontier Show to discuss how neutral-atom quantum systems are moving from research labs into high-performance computing centers and cloud environments worldwide. NVIDIA Joins Google in Backing QuEra’s $230 Million Round In early September, QuEra disclosed that NVentures, NVIDIA’s venture arm, has joined Google and others in expanding its $230 million Series B round. The investment deepens what has already been one of the most active collaborations between quantum and accelerated-computing companies. “We already work with NVIDIA, pairing our scalable neutral-atom architecture with its accelerated-computing stack to speed the arrival of useful, fault-tolerant quantum machines,” said QuEra CEO Andy Ory. “The decision to invest in us underscores our shared belief that hybrid quantum-classical systems will unlock meaningful value for customers sooner than many expect.” The partnership spans hardware, software, and go-to-market initiatives. QuEra’s neutral-atom machines are being integrated into NVIDIA’s CUDA-Q software platform for hybrid workloads, while the two companies collaborate at the NVIDIA Accelerated Quantum Center (NVAQC) in Boston, linking QuEra hardware with NVIDIA’s GB200 NVL72 GPU clusters for simulation and quantum-error-decoder research. Meanwhile, at Japan’s AIST ABCI-Q supercomputing center, QuEra’s Gemini-class quantum computer now operates beside more than 2,000 H100 GPUs, serving as a national testbed for hybrid workflows. A jointly developed transformer-based decoder running on NVIDIA’s GPUs has already outperformed classical maximum-likelihood error-correction models, marking a concrete step toward practical fault-tolerant quantum computing. For NVIDIA, the move signals conviction that quantum processing units (QPUs) will one day complement GPUs inside large-scale data centers. For QuEra, it widens access to the

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How CoreWeave and Poolside Are Teaming Up in West Texas to Build the Next Generation of AI Data Centers

In the evolving landscape of artificial-intelligence infrastructure, a singular truth is emerging: access to cutting-edge silicon and massive GPU clusters is no longer enough by itself. For companies chasing the frontier of multi-trillion-parameter model training and agentic AI deployment, the bottleneck increasingly lies not just in compute, but in the seamless integration of compute + power + data center scale. The latest chapter in this story is the collaboration between CoreWeave and Poolside, culminating in the launch of Project Horizon, a 2-gigawatt AI-campus build in West Texas. Setting the Stage: Who’s Involved, and Why It Matters CoreWeave (NASDAQ: CRWV) has positioned itself as “The Essential Cloud for AI™” — a company founded in 2017, publicly listed in March 2025, and aggressively building out its footprint of ultra-high-performance infrastructure.  One of its strategic moves: in July 2025 CoreWeave struck a definitive agreement to acquire Core Scientific (NASDAQ: CORZ) in an all-stock transaction. Through that deal, CoreWeave gains grip over approximately 1.3 GW of gross power across Core Scientific’s nationwide data center footprint, plus more than 1 GW of expansion potential.  That acquisition underlines a broader trend: AI-specialist clouds are no longer renting space and power; they’re working to own or tightly control it. Poolside, founded in 2023, is a foundation-model company with an ambitious mission: building artificial general intelligence (AGI) and deploying enterprise-scale agents.  According to Poolside’s blog: “When people ask what it takes to build frontier AI … the focus is usually on the model … but that’s only half the story. The other half is infrastructure. If you don’t control your infrastructure, you don’t control your destiny—and you don’t have a shot at the frontier.”  Simply put: if you’re chasing multi-trillion-parameter models, you need both the compute horsepower and the power infrastructure; and ideally, tight vertical integration. Together, the

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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.

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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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