Ameresco secures $140M energy savings project at the Denver Federal Center

Stay Ahead, Stay ONMINE

Ameresco secures $140M energy savings project at the Denver Federal Center

Dive Brief: Clean technology and renewable energy company Ameresco secured a $140 million energy savings performance contract award from the U.S. General Services Administration to cut purchased energy and water use at the Denver Federal Center, according to a Jan. 13 news release. The contract covers the addition of a centralized geothermal heat pump system […]

Dive Brief:

Clean technology and renewable energy company Ameresco secured a $140 million energy savings performance contract award from the U.S. General Services Administration to cut purchased energy and water use at the Denver Federal Center, according to a Jan. 13 news release.
The contract covers the addition of a centralized geothermal heat pump system and a solar photovoltaic system to supply year-round heating, cooling and electrical power to the 623-acre complex, which has 44 buildings used by 28 federal agencies.
The future of the contract could be in question, however, due to an executive order President Donald J. Trump issued on his first day in office pausing the disbursement of funds from the Inflation Reduction Act, the source of the contract’s funding, and the Infrastructure Investment and Jobs Act.

Dive Insight:

In addition to the planned geothermal and solar systems, the project will electrify about half of the Denver Federal Center, install new windows and implement other energy conservation measures. The ESPC is expected to cut grid purchased energy at the complex by approximately 51% and water usage by approximately 10%. GSA said in the press release this would result in more than $2 million in cost savings in the first year.

“Fifty percent of their energy bill is serious money, so you can easily do a cost benefit [analysis] on that,” said Jennifer Perkins, the government industry specialist at Siemens subsidiary Brightly, a maker of software for asset lifecycle management. A project of that size also can create a lot of jobs, she said, noting she is not involved in the project.

In an energy savings performance contract, the contracted company conducts an energy audit of the facilities and designs and constructs a project based on its findings. As of Jan. 16, the GSA had obligated $416 million in total for ESPCs, according to an agency spokesperson.

Funding for the Denver Federal Center is part of $3.4 billion the IRA allocated to the GSA to “build, modernize and maintain more sustainable and cost-efficient high-performance facilities” that utilize low-embodied-carbon materials and help achieve net-zero emissions across the federal building portfolio by 2045, according to the release.

“These investments are a prime example of how Inflation Reduction Act investments get us a triple-win: creating good jobs, saving taxpayer dollars through energy efficiency, and ensuring a healthier, brighter future for our communities and our kids,” then-GSA Administrator Robin Carnahan stated in the news release.

In a 2023 blog post, the GSA had announced plans to invest almost $975 million from the IRA in emerging and sustainable technologies in federal buildings. In a Jan. 15 blog post, the agency stated that by leveraging private-sector funds through ESPCs, it could more than double that planned investment to $1.9 billion. The two blog posts have since been removed from the agency’s website.

But after campaigning against the IRA, the Biden administration’s signature climate legislation, Trump’s “Unleashing American Energy” executive order Jan. 20 paused the disbursement of Inflation Reduction Act funds. A separate Jan. 27 memo from the Office of Management and Budget ordered a pause on all federal grants and loans, starting at 5 p.m. Jan. 28, “including, but not limited to … the green new deal,” according to the memo.

Two federal judges temporarily blocked the effort with temporary restraining orders Jan. 28, leading OMB to rescind the memo on Jan. 29. However, White House Press Secretary Karoline Leavitt posted on X shortly after the memo was rescinded that “This is NOT a rescission of the federal funding freeze. It is simply a rescission of the OMB memo. … The President’s EO’s on federal funding remain in full force and effect, and will be rigorously implemented.”

Judge Jack McConnell of the U.S. District Court of Rhode Island issued another temporary restraining order Jan. 30 in response to Leavitt’s message, stating, in part, that “If Defendants engage in the ‘[identification] and review’ of federal financial assistance programs, as identified in the OMB Directive, such exercise shall not affect a pause, freeze, impediment, block, cancellation, or termination of Defendants’ compliance with such awards and obligations, except on the basis of the applicable authorizing statutes, regulations, and terms.”

On Feb. 7, the plaintiffs in that case filed another motion for a preliminary injunction, stating that “Despite the clear terms of the [temporary restraining order], the Government took the position in communication on February 5 that IIJA and IRA funds were excluded from the relief. This position and the ongoing freeze of numerous important funding streams … leave Plaintiff States uncertain as to the security of billions of dollars of critical resources for their residents.”

On Monday, the judge granted the motion, stating in part that “The Defendants must immediately restore withheld funds, including those federal funds appropriated in the Inflation Reduction Act and the 5 Infrastructure Improvement and Jobs Act.”

The General Services Administration and Ameresco did not respond to requests for comment.

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.

AWS launches ‘Capabilities by Region’ to simplify planning for cloud deployments

While Microsoft Azure’s Product Availability by Region portal lists services by geography, it lacks forward-looking timelines and the unified API comparability that AWS’s Capabilities by Region delivers, Jain noted. Region Picker, which is a similar offering from Google, too, falls short on granular, future-facing service or API roadmaps and focuses

Google Cloud aims for more cost-effective Arm computing with Axion N4A

It’s not alone: AWS introduced its own Arm-based chip, Graviton, in 2018 to reduce the cost of running internal cloud workloads such as Amazon retail IT, and now 50% of new AWS instances run on it. Microsoft, too, recently developed an Arm chip, Cobalt, to run Microsoft 365 and to

Perplexity’s open-source tool to run trillion-parameter models without costly upgrades

The obvious answer would be Nvidia’s new GB200 systems, essentially one giant 72-GPU server. But those cost millions, face extreme supply shortages, and aren’t available everywhere, the researchers noted. Meanwhile, H100 and H200 systems are plentiful and relatively cheap. The catch: running large models across multiple older systems has traditionally

Arista shares Q3 financials, touts ‘golden era in networking’

“I think a lot of these designs will materialize as the standards for Ethernet are getting stronger and stronger. We now have a UEC [Ultra Ethernet Consortium] spec. You heard me talk about the Scale-Up Ethernet spec for ESUN where we can bring different work streams onto the same Ethernet

Oil Rises but Logs Second Weekly Loss

Oil rose on Friday but still notched a second weekly loss as the market continued to weigh the threat to output from sanctions on Russia against a looming oversupply. West Texas Intermediate futures rose around 0.5% to settle below $60 a barrel, but were still down for the week. Adding to fears of a glut, oil prices have also been buffeted by swings in equity markets this week. Meanwhile, the White House’s move to clamp down on the buying of Russian crude led oil trading giant Gunvor Group to withdraw an offer for the international assets of Lukoil PJSC. The fate of the assets, which include stakes in oil fields, refineries and gas stations, remains unclear. One possible exception to that crackdown could emerge soon: President Donald Trump signaled an openness to exempting Hungary from sanctions on Russian energy purchases as he hosted Prime Minister Viktor Orban, briefly pushing futures to intraday lows. The development appeared to allay shortage fears, given that Budapest imports over 90% of its crude from Moscow. Senior industry figures have warned the latest US curbs on Russia’s two largest oil companies are beginning to have an impact on the market, particularly in diesel, where prices have been surging in recent days, with time spreads for the fuel signaling supply pressure. At the same time, the US measures have come against a backdrop of oversupply that has weighed on key crude oil metrics. The spread between the nearest West Texas Intermediate futures closed at the weakest level since February on Thursday. “If the market flips to contango, we may see more bearish funds enter the crude space,” said Dennis Kissler, senior vice president for trading at BOK Financial said of the potential that longer-dated contracts trade at a premium to nearer-term ones. “Most traders remain surprised

Gunvor Scraps Lukoil Deal

Commodity trader Gunvor Group has withdrawn its offer for the international assets of sanctioned Russian oil producer Lukoil PJSC after the US Treasury Department called it “the Kremlin’s puppet” and said the oil and gas trader would never get a license. Gunvor pushed back on the Treasury comment on social media, calling it “fundamentally misinformed and false.” The Geneva-based company said it would seek to correct a “clear misunderstanding” but that it would withdraw its bid for now. President Trump has been clear that the war must end immediately. As long as Putin continues the senseless killings, the Kremlin’s puppet, Gunvor, will never get a license to operate and profit. — Treasury Department (@USTreasury) November 6, 2025 The comment is a remarkable volte-face after a week in which Gunvor has been in talks with the US Office of Foreign Assets Control, part of the Treasury Department, and other bodies in charge of sanctions to help press its case for a deal that would have transformed it into an integrated oil producing and processing colossus. Gunvor swooped on the assets at the end of last month following the US blacklisting of Lukoil and fellow Russian oil giant Rosneft PJSC, and its exit may leave the door open to other suitors. Gunvor on Thursday also announced it had raised $2.81 billion in a credit facility financed by US arms of global banks. Like other major commodity traders, the firm funds the bulk of its trades of oil, gas and metals around the world with bank financing. For the trader, the comments are likely to revive questions about its connections in Moscow at a time when many oil industry participants are wary of any links to Russia. The trader’s co-founder, Gennady Timchenko, is a friend of Russian President Vladimir Putin, and when the US imposed sanctions

Ship With Russia Oil Makes Rare Move Offshore India

A tanker carrying crude from recently-sanctioned Rosneft PJSC has made a rare cargo transfer off Mumbai, as the Trump administration ramps up its scrutiny of India’s oil trade with Russia. But the unusual move has puzzled traders. The cargo was transferred from one blacklisted tanker to another sanctioned ship, meaning there’s been no attempt to hide its origin — typical of such a move — and the crude is still heading for an Indian port: Kochi in the south, rather than Mumbai on the west coast. India’s purchases of Russian oil have drawn the ire of President Donald Trump, and the US penalties on Rosneft along with Lukoil PJSC are expected to severely impact the trade. The market is keenly watching for disruptions to established flows before a grace period related to the sanctions ends later this month. “What we’re seeing now is this uncertainty in the market about what the sanctions risks are,” said Rachel Ziemba, an analyst at the Center for a New American Security in Washington. “The net result is more ship-to-ship transfers, more subterfuge, longer routes, more complicated transactions.” The Fortis took around 720,000 barrels of Russian Urals from Ailana on Tuesday near Mumbai, according to ship-tracking data compiled by Bloomberg, Kpler and Vortexa. The cargo was collected from the Baltic port of Ust-Luga before the US sanctioned Rosneft, and Ailana had idled in the area for nearly two weeks with no clear reason. Ailana is on its way back to Russia, while Fortis is expected to arrive at Kochi early next week with the cargo, ship-tracking data shows. Both vessels have been sanctioned by the European Union and the UK. Fortis’ owner and manager — Vietnam-based Pacific Logistic & Maritime and North Star Ship Management — didn’t respond to emailed requests for comment. There are no contact details on maritime database

Southwest Power Pool to develop 765-kV regional transmission ‘backbone’

Listen to the article 4 min This audio is auto-generated. Please let us know if you have feedback. Dive Brief: The Southwest Power Pool board of directors on Wednesday approved an $8.6 billion slate of 50 transmission projects across its 14-state footprint. The projects are intended to help the grid operator meet peak demand, which it expects will double, to reach 109 GW, in the next 10 years. Key to the 2025 Integrated Transmission Plan is development of a 765-kV regional transmission “backbone” that can carry four times the power SPP’s existing 345-kV lines do, and do so more efficiently. The grid operator’s transmission system “is at capacity and forecasted load growth will only exacerbate the existing strain,” it said. “Simply adding new generation will not resolve the challenges.” 765-kV transmission lines are the highest operating voltages in the U.S. but are new in both SPP and in the neighboring Electric Reliability Council of Texas market. Texas regulators approved the higher voltage lines for the first time in April. Dive Insight: Transmission developers in SPP and ERCOT are turning to 765-kV projects to mitigate line losses and move greater volumes of power into demand centers at a time when electricity demand is expected to rise significantly. “With the new load being integrated into the system, SPP could see an increase in the footprint’s annual energy consumption by as much as 136%,” the grid operator said in its ITP. “Investments in transmission are the key to keep costs low, maintain reliability, and power economic growth.” Even under conservative assumptions, SPP forecasts a 35% increase in demand, “making timely transmission investment essential,” the grid operator said. SPP selected Xcel Energy in February to construct the first 765-kV lines in its footprint. Those lines were identified in its 2024 plan. AEP Texas will build

The week in 5 numbers: Gas valuations soar but solar leads new capacity

The price gas power merger and acquisitions have reached in some markets, according to energy analytics firm Enverus. The artificial intelligence boom, along with expectations of increased manufacturing and electrification, is driving a surge in natural gas investment, but thermal generation remains risky, some analysts say, drawing parallels to the dot com bubble at the turn of the century.

Our laws must catch up to data centers’ rising power

Alexandra Klass is the James G. Degnan Professor of Law at Michigan Law, and Dave Owen is the Albert Abramson ’54 Distinguished Professor of Law at UC Law San Francisco. The United States faces massive growth in electricity demand. If utilities’ projections are right, data centers will drive much of that growth. And if utilities try to meet that demand in traditional ways, the results could be bad for consumers, the environment and the tech industry. Those traditional ways assume that utilities must meet the needs of electricity customers at all times. This requires utilities to build new power plants and transmission and distribution lines and (in most states) pass those costs, plus a profit margin, on to consumers. Utilities also will not allow major new users to connect to the grid until those users’ needs can be met. These principles are a poor fit for the present moment. Building new power plants and transmission lines has become increasingly difficult. If data centers must wait until that infrastructure is fully built, they may wait for years. Worse, utilities and government officials are citing the potential data-center boom as a reason to extend the life of old, expensive, and heavily polluting coal plants or to build new gas plants. If they do so, and if they pass those costs on to consumers, retail electricity prices and pollution will rise. And if current demand projections turn out to be overestimates — which has happened during past tech booms — consumers will pay for new power plants that never needed to be built. But this unfortunate scenario is not inevitable. We are scholars of energy, natural resources, and environmental law, and in a paper we explore a better way of meeting this moment. Our inspiration comes from legal systems for allocating water, particularly in

Designing the AI Century: 7×24 Exchange Fall ’25 Charts the New Data Center Industrial Stack

SMRs and the AI Power Gap: Steve Fairfax Separates Promise from Physics If NVIDIA’s Sean Young made the case for AI factories, Steve Fairfax offered a sobering counterweight: even the smartest factories can’t run without power—and not just any power, but constant, high-availability, clean generation at a scale utilities are increasingly struggling to deliver. In his keynote “Small Modular Reactors for Data Centers,” Fairfax, president of Oresme and one of the data center industry’s most seasoned voices on reliability, walked through the long arc from nuclear fusion research to today’s resurgent interest in fission at modular scale. His presentation blended nuclear engineering history with pragmatic counsel for AI-era infrastructure leaders: SMRs are promising, but their road to reality is paved with physics, fuel, and policy—not PowerPoint. From Fusion Research to Data Center Reliability Fairfax began with his own story—a career that bridges nuclear reliability and data center engineering. As a young physicist and electrical engineer at MIT, he helped build the Alcator C-MOD fusion reactor, a 400-megawatt research facility that heated plasma to 100 million degrees with 3 million amps of current. The magnet system alone drew 265,000 amps at 1,400 volts, producing forces measured in millions of pounds. It was an extreme experiment in controlled power, and one that shaped his later philosophy: design for failure, test for truth, and assume nothing lasts forever. When the U.S. cooled on fusion power in the 1990s, Fairfax applied nuclear reliability methods to data center systems—quantifying uptime and redundancy with the same math used for reactor safety. By 1994, he was consulting for hyperscale pioneers still calling 10 MW “monstrous.” Today’s 400 MW campuses, he noted, are beginning to look a lot more like reactors in their energy intensity—and increasingly, in their regulatory scrutiny. Defining the Small Modular Reactor Fairfax defined SMRs

Top network and data center events 2025 & 2026

Denise Dubie is a senior editor at Network World with nearly 30 years of experience writing about the tech industry. Her coverage areas include AIOps, cybersecurity, networking careers, network management, observability, SASE, SD-WAN, and how AI transforms enterprise IT. A seasoned journalist and content creator, Denise writes breaking news and in-depth features, and she delivers practical advice for IT professionals while making complex technology accessible to all. Before returning to journalism, she held senior content marketing roles at CA Technologies, Berkshire Grey, and Cisco. Denise is a trusted voice in the world of enterprise IT and networking.

Google’s cheaper, faster TPUs are here, while users of other AI processors face a supply crunch

Opportunities for the AI industry LLM vendors such as OpenAI and Anthropic, which still have relatively young code bases and are continuously evolving them, also have much to gain from the arrival of Ironwood for training their models, said Forrester vice president and principal analyst Charlie Dai. In fact, Anthropic has already agreed to procure 1 million TPUs for training and its models and using them for inferencing. Other, smaller vendors using Google’s TPUs for training models include Lightricks and Essential AI. Google has seen a steady increase in demand for its TPUs (which it also uses to run interna services), and is expected to buy $9.8 billion worth of TPUs from Broadcom this year, compared to $6.2 billion and $2.04 billion in 2024 and 2023 respectively, according to Harrowell. “This makes them the second-biggest AI chip program for cloud and enterprise data centers, just tailing Nvidia, with approximately 5% of the market. Nvidia owns about 78% of the market,” Harrowell said. The legacy problem While some analysts were optimistic about the prospects for TPUs in the enterprise, IDC research director Brandon Hoff said enterprises will most likely to stay away from Ironwood or TPUs in general because of their existing code base written for other platforms. “For enterprise customers who are writing their own inferencing, they will be tied into Nvidia’s software platform,” Hoff said, referring to CUDA, the software platform that runs on Nvidia GPUs. CUDA was released to the public in 2007, while the first version of TensorFlow has only been around since 2015.

Cisco launches AI infrastructure, AI practitioner certifications

“This new certification focuses on artificial intelligence and machine learning workloads, helping technical professionals become AI-ready and successfully embed AI into their workflows,” said Pat Merat, vice president at Learn with Cisco, in a blog detailing the new AI Infrastructure Specialist certification. “The certification validates a candidate’s comprehensive knowledge in designing, implementing, operating, and troubleshooting AI solutions across Cisco infrastructure.” Separately, the AITECH certification is part of the Cisco AI Infrastructure track, which complements its existing networking, data center, and security certifications. Cisco says the AITECH cert training is intended for network engineers, system administrators, solution architects, and other IT professionals who want to learn how AI impacts enterprise infrastructure. The training curriculum covers topics such as: Utilizing AI for code generation, refactoring, and using modern AI-assisted coding workflows. Using generative AI for exploratory data analysis, data cleaning, transformation, and generating actionable insights. Designing and implementing multi-step AI-assisted workflows and understanding complex agentic systems for automation. Learning AI-powered requirements, evaluating customization approaches, considering deployment strategies, and designing robust AI workflows. Evaluating, fine-tuning, and deploying pre-trained AI models, and implementing Retrieval Augmented Generation (RAG) systems. Monitoring, maintaining, and optimizing AI-powered workflows, ensuring data integrity and security. AITECH certification candidates will learn how to use AI to enhance productivity, automate routine tasks, and support the development of new applications. The training program includes hands-on labs and simulations to demonstrate practical use cases for AI within Cisco and multi-vendor environments.

Chip-to-Grid Gets Bought: Eaton, Vertiv, and Daikin Deals Imply a New Thermal Capital Cycle

This week delivered three telling acquisitions that mark a turning point for the global data center supply chain; and more specifically, for the high-density liquid cooling mega-play now unfolding across the power-thermal continuum. Eaton is acquiring Boyd Thermal for $9.5 billion from Goldman Sachs Asset Management. Vertiv is buying PurgeRite for about $1 billion from Milton Street Capital. And Daikin Applied has moved to acquire Chilldyne, one of the most proven negative-pressure direct-to-chip pioneers. On paper, they’re three distinct transactions. In reality, they’re chapters in the same story: the acceleration of strategic vertical integration around thermal infrastructure for AI-class compute. The Equity Layer: Private Capital Builds, Strategics Buy From an equity standpoint, these are classic handoff moments between private-equity construction and corporate consolidation. Goldman Sachs built Boyd Thermal into a global platform spanning cold plates, CDUs, and high-density liquid loop design, now sold to Eaton at an enterprise multiple north of 5× 2026E revenue. Milton Street Capital took PurgeRite from a specialist contractor in fluid flushing and commissioning into a nationwide services platform. And Daikin, long synonymous with chillers and air-side thermal, is crossing the liquid Rubicon by buying its way into the D2C ecosystem. Each deal crystallizes a simple fact: liquid cooling is no longer an adjunct; it’s core infrastructure. Private equity did its job scaling the parts. Strategic players are now paying up for the system. Eaton’s Bid: The Chip-to-Grid Thesis For Eaton, Boyd Thermal is the final missing piece in its “chip-to-grid” thesis. The company already owns the electrical side of the data center: UPS, busway, switchgear, and monitoring. Boyd plugs the thermal gap, allowing Eaton to market full rack-to-substation solutions for AI loads in the 50–100 kW+ range. It’s a statement acquisition that places Eaton squarely against Schneider Electric, Vertiv and ABB in the race to

Space: The final frontier for data processing

There are, however, a couple of reasons why data centers in space are being considered. There are plenty of reports about how the increased amount of AI processing is affecting power consumption within data centers; the World Economic Forum has estimated that the power required to handle AI is increasing at a rate of between 26% and 36% annually. Therefore, it is not surprising that organizations are looking at other options. But an even more pressing reason for orbiting data centers is to handle the amount of data that is being produced by existing satellites, Judge said. “Essentially, satellites are gathering a lot more data than can be sent to earth, because downlinks are a bottleneck,” he noted. “With AI capacity in orbit, they could potentially analyze more of this data, extract more useful information, and send insights back to earth. My overall feeling is that any more data processing in space is going to be driven by space processing needs.” And China may already be ahead of the game. Last year, Guoxing Aerospace launched 12 satellites, forming a space-based computing network dubbed the Three-Body Computing Constellation. When completed, it will contain 2,800 satellites, all handling the orchestration and processing of data, taking edge computing to a new dimension.

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