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AI shifts IT roles from operator to orchestrator

The report indicates that IT roles are becoming more strategic and automation-driven, with 52% of respondents citing increases in both areas. Roles are also becoming more cross-functional (47%) and complex (41%), reflecting the integration of AI into broader business processes. AI is also affecting how IT teams allocate time. Respondents report spending more time on […]

The report indicates that IT roles are becoming more strategic and automation-driven, with 52% of respondents citing increases in both areas. Roles are also becoming more cross-functional (47%) and complex (41%), reflecting the integration of AI into broader business processes. AI is also affecting how IT teams allocate time. Respondents report spending more time on proactive activities such as strategizing and analyzing system performance, while some reactive tasks, including troubleshooting incidents, are decreasing.

Governance, training, and data challenges

The report highlights several areas organizations must address to support AI adoption. More than half of respondents (56%) say clearer AI policies and guardrails would help them adapt, while 50% point to the need for formal training.

Data quality is also a key factor. Eighty-three percent of respondents say AI effectiveness depends on the breadth and quality of the data available to it. Respondents also cite issues such as tool fragmentation and lack of integration as barriers to effective AI use.

Respondents said they expect AI and automation to play a larger role in IT operations. More than three-quarters (77%) say their organizations will become more proactive over the next two to three years, supported by increased automation and data-driven insights. At the same time, organizations expect to encounter challenges, including skills gaps, governance requirements, and ensuring the accuracy and reliability of AI-driven systems.

“AI is not making IT simpler—it’s making it more consequential,” said Krishna Sai, chief technology officer at SolarWinds, in a statement. “The teams thriving in this environment are not usually the ones with the most AI tools. Instead, those who are building the governance and structure to actually trust them are seeing the greatest results.”

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AI shifts IT roles from operator to orchestrator

The report indicates that IT roles are becoming more strategic and automation-driven, with 52% of respondents citing increases in both areas. Roles are also becoming more cross-functional (47%) and complex (41%), reflecting the integration of AI into broader business processes. AI is also affecting how IT teams allocate time. Respondents

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Apply Now: 2026 Waste to Energy and Materials Technical Assistance for State, Local, and Tribal Governments

The U.S. Department of Energy’s Alternative Fuels and Feedstocks Office (AFFO), formerly known as the Bioenergy Technologies Office, and the National Laboratory of the Rockies (NLR) are launching the 2026 Waste to Energy and Materials Technical Assistance Program for state, local, and Tribal governments. The scope of this year’s program has been expanded to include additional municipal solid waste materials such as electronics, industrial wastewater, and other byproducts.  U.S. waste streams present significant logistical and economic challenges for states, counties, municipalities, and Tribal governments. However, waste is also a resource that can be used as an unconventional additional source of energy, advanced materials, and critical minerals. This program provides no-cost technical assistance to states, counties, municipalities, and Tribal governments with the most relevant data to guide decision-making—providing local solutions to the various aspects of waste management, taking into consideration current handling practices, costs, and infrastructure. It is designed to help officials evaluate the most sensible end uses for their waste, whether repurposing it for on-site heat and power, upgrading it into transportation fuels, or using it for material and mineral recovery. Program technical assistance includes: Waste resource information Infrastructure considerations Techno-economic comparison of energy, material, and mineral recovery options Evaluation and sharing of case studies (to the extent possible) from similar communities/projects The 2026 Waste to Energy and Materials Technical Assistance application portal is now open and applications will be accepted through May 30, 2026. For information on applicant eligibility and how to apply, please visit NLR’s technical assistance webpage. Timeline for Technical Assistance Opportunity Date Action April 15, 2026 Application Portal Opens May 30, 2026 Application Portal Closes  July – August 2026 Selections Made and Recipients Informed  Learn more about AFFO-supported waste to energy and materials technical assistance. If you have further questions, please see frequently asked questions or contact the Waste to

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Energy Deputy Secretary Danly Commends FERC Action on Large Load Interconnection Reform

WASHINGTON—U.S. Deputy Secretary of Energy James P. Danly issued the following statement after the Federal Energy Regulatory Commission (FERC or Commission) announced it will take action by June 2026 on the large load interconnection proceeding initiated at the direction of U.S. Secretary of Energy Chris Wright: “FERC’s announcement today demonstrates Chairman Swett’s commitment to implement Secretary Wright’s directive that the Commission ensure the timely and orderly integration of large electric loads that deliver on President Trump’s goal of American energy dominance. “I expect that the Commission will act quickly and decisively to improve interconnection processes, support the co-location of load and generation, and accelerate the addition of new generation to ensure that supply is built alongside demand—delivering affordable, reliable, and secure energy for all Americans. “Having served at FERC as commissioner and chairman, I understand FERC’s role in ensuring the reliability of the nation’s bulk power system, and I commend Chairman Swett for focusing on affordability and reliability.”                                                                                               ###  

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Petrobras discovers hydrocarbons in Campos basin presalt offshore Brazil

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #c19a06 !important; border-color: #c19a06 !important; } Petrobras has discovered presence in the Campos basin presalt offshore Brazil during exploration in sector SC-AP4, block CM-477. Samples taken from the well, 1-BRSA-1404DC-RJS, will be sent for laboratory analysis with the aim of characterizing the conditions of the reservoirs and fluids found to enable continued evaluation of the area’s potential, the company said in a release Apr. 13. The discovery well was drilled 201 km off the coast of the state of Rio de Janeiro in water depth of 2,984 m. The hydrocarbon-bearing interval was confirmed through electrical profiles, gas evidence, and fluid sampling. Petrobras is the operator of block CM-477 with 70% interest. bp plc holds the remaining 30%.

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bp to operate blocks offshore Namibia through acquisition

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #c19a06 !important; border-color: #c19a06 !important; } Map from bp plc <!–> –> bp plc aims to become operator of three exploration blocks offshore Namibia through acquisition of a 60% interest from Eco Atlantic Oil & Gas. Subject to Namibian government and joint venture partner approvals, bp will operate blocks PEL97, PEL99, and PEL100 in Walvis basin.   In a release Apr. 13, bp said entering the blocks builds on its recent exploration successes in Namibia through Azule Energy, a 50-50 joint venture between bp and Eni. Eco Atlantic will remain a partner, along with Namibia’s national oil company NAMCOR, following the deal’s closing, which is subject to closing conditions.

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ConocoPhillips sends team to Venezuela to evaluate oil, gas opportunities

ConocoPhillips sent a team to Venezuela to evaluate oil and gas opportunities, the company confirmed to Oil & Gas Journal Apr. 13. In an email to OGJ, a company spokesperson said “ConocoPhillips can confirm that we sent a small evaluation team to Venezuela during the week of Apr. 6 to better understand the potential for in-country oil and gas opportunities.” Asked what clarity the company seeks, the spokesperson said the team “will evaluate Venezuela against other international opportunities as part of our disciplined investment framework.” The operator left Venezuela in 2007 after then-President Hugo Chavez’s government reverted privately run oil fields to state control. ConocoPhillips, along with ExxonMobil, refused the government’s terms and took claims to the World Bank’s International Centre for the Settlement of Investment Disputes (ICSID). ConocoPhillips is owed about $12 billion following two judgements, an amount still sought by the company, which, prior to the expropriation of its interests, held a 50.1% interest in Petrozuata, a 40% interest in Hamaca, and a 32.5% interest in Corocoro heavy oil projects in Venezuela. In January, following the removal of Venezuela’s leader Nicolas Maduro, US President Donald Trump urged oil and gas companies to spend billions to rebuild Venezuela’s energy sector. ExxonMobil, which also exited the country in 2007, ​sent a technical team to Venezuela in March to ⁠evaluate the infrastructure and investment opportunities. In a discussion at CERAWeek by S&P Global in Houston in March, ConocoPhillips’ chief executive officer, Ryan Lance, said Venezuela needs to “completely rewire” ​its fiscal system to attract new ‌investment. The South American country holds a large cache of proven oil reserves, but has faced decades of production challenges due to mismanagement, underinvestment, and sanctions.

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TotalEnergies, TPAO sign MoU to assess exploration opportunities

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #c19a06 !important; border-color: #c19a06 !important; } TotalEnergies EP New Ventures SA has signed a memorandum of understanding (MoU) with Türkiye Petrolleri Anonim Ortaklığı (TPAO) for potential collaboration. The MoU provides a framework for technical collaboration, including a joint assessment of hydrocarbon exploration opportunities in the Black Sea region of Türkiye as well as internationally. In February of this year, TPAO signed an MoU with Chevron Business Development EMEA Ltd., a subsidiary of Chevron, providing an opportunity to “identify and evaluate cooperation opportunities that may arise in international projects and in oil exploration and production license areas in onshore and offshore fields in Türkiye.”

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OpenAI pulls out of a second Stargate data center deal

“OpenAI is embattled on several fronts. Anthropic has been doing very well in the enterprise, and OpenAI’s cash burn might be a problem if it wants to go public at an astronomical $800 billion+ valuation. This is especially true with higher energy prices due to geopolitics, and the public and regulators increasingly skeptical of AI companies, especially outside of the United States,” Roberts said. “I see these moves as OpenAI tightening its belt a bit and being more deliberate about spending as it moves past the interesting tech demo stage of its existence and is expected to provide a real return for investors.” He added, “I expect it’s a symptom of a broader problem, which is that OpenAI has thrown some good money after bad in bets that didn’t work out, like the Sora platform it just shut down, and it’s under increasing pressure to translate its first-mover advantage into real upside for its investors. Spending operational money instead of capital money might give it some flexibility in the short term, and perhaps that’s what this is about.” All in all, he noted, “on a scale of business-ending event to nothingburger, I would put it somewhere in the middle, maybe a little closer to nothingburger.” Acceligence CIO Yuri Goryunov agreed with Roberts, and said, “OpenAI has a problem with commercialization and runaway operating costs, for sure. They are trying to rightsize their commitments and make sure that they deliver on their core products before they run out of money.” Goryunov described OpenAI’s arrangement with Microsoft in Norway as “prudent financial engineering” that allows it to access the data center resources without having to tie up too much capital. “It’s financial discipline. OpenAI [executives] are starting to behave like grownups.” Forrester senior analyst Alvin Nguyen echoed those thoughts. 

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DCF Tours: SDC Manhattan, 375 Pearl St.

Power: Redundant utility design in a power-constrained market The tour made equally clear that in Manhattan, power is still the central gating factor. The brochure describes SDC Manhattan as offering 18MW of aggregate power delivered to the building, backed by redundant electrical and mechanical systems, backup generators, and Tier III-type concurrent maintainability. The December 2025 press release updated that picture in a more market-facing way, noting that Sabey is one of the only colocation providers in Manhattan with available power, including nearly a megawatt of turnkey power and 7MW of utility power across two powered shell spaces. Bajrushi’s explanation of the electrical topology helped show how Sabey has made that possible. Standing on the third floor, he described a ring bus tying together four Con Edison feeds. Bajrushi said the feeds all originate from the same substation but take different paths into the building, creating redundancy outside the building as well as within it. He added that if one feed fails, the ring bus remains unaffected, and that only one feed is needed to power everything currently in operation. He also noted that Sabey has the ability to add two more feeds in the future if expansion calls for it. That matters in a city where available utility capacity is hard to come by and where many data center conversations end not with square footage but with a megawatt number. Bajrushi also noted that physical space is not the core constraint at 375 Pearl. He said the building still has plenty of room for future buildouts, including open areas that could become additional white space, chiller capacity, or other infrastructure. The bigger question, he suggested, is how and when power and supporting systems get installed. That observation aligns neatly with Sabey’s press release. The company is effectively arguing that SDC

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Maine to put brakes on big data centers as AI expansion collides with power limits

Mills has pushed for an exemption protecting a proposed $550 million project at the former Androscoggin paper mill in Jay, arguing it would reuse existing infrastructure without straining the grid. Lawmakers rejected that exemption. Mills’ office did not immediately respond to a request for comment. A national wave, an unanswered federal question Maine is one of at least 12 states now weighing moratorium or restraint legislation, alongside more than 300 data center bills filed across 30-plus states in the current session, according to legislative tracking firm MultiState. The shared concern is energy cost. Data centers could consume up to 12% of total US electricity by 2028, according to the US Department of Energy. On March 25, Senator Bernie Sanders and Alexandria Ocasio-Cortez introduced the AI Data Center Moratorium Act in Congress, which would impose a nationwide freeze on all new data center construction until Congress passes AI safety legislation. The Trump administration has pursued a different path from the legislative approach being taken in states. On March 4, Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI signed the White House’s Ratepayer Protection Pledge, a voluntary commitment by hyperscalers to fund their own power generation rather than pass grid costs to ratepayers. The pledge, published in the Federal Register on March 9, carries no penalties for noncompliance or auditing requirements.

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Cisco just made two moves to own the AI infrastructure stack

In a world of autonomous agents, identity and access become the de facto safety rails. Astrix is designed to inventory these non-human identities, map their permissions, detect toxic combinations, and remediate overprivileged access before it becomes an exploit or a data leak. That capability integrates directly with Cisco’s broader zero-trust and identity-centric security strategy, in which the network enforces policy based on who or what the entity is, not on which subnet it resides in. How this strengthens Cisco’s secure networking story Cisco has positioned itself as the vendor that can deliver “AI-ready, secure networks” spanning campus, data center, cloud, and edge. Galileo and Astrix extend that narrative from infrastructure into AI behavior and identity governance: The network becomes the high‑performance, policy‑enforcing substrate for AI traffic and data. Splunk plus Galileo becomes the observability plane for AI agents, linking AI incidents to network and application signals. Security plus Astrix becomes the identity and permission-control layer that constrains what AI agents can actually do within the environment. This is the core of Cisco’s emerging “Secure AI” posture: not just using AI to improve security but securing AI itself as it is embedded across every workflow, API, and device. For customers, that means AI initiatives can be brought under the same operational and compliance disciplines already used for networks and apps, rather than existing as unmanaged risk islands. Why this matters to Cisco customers Most large Cisco accounts are exactly the enterprises now experimenting with AI agents in contact centers, IT operations, and business workflows. They face three practical problems: They cannot see what agents are doing end‑to‑end, or measure quality beyond offline benchmarks. They lack a coherent model for managing the identities, secrets, and permissions those agents depend on. Their security and networking teams are often disconnected from AI projects happening in lines of business.

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From Buildings to Token Factories: Compu Dynamics CEO Steve Altizer On Why AI Is Rewriting the Data Center Design Playbook

Not Falling Short—Just Not Optimized Altizer drew a clear distinction. Traditional data centers can run AI workloads, but they weren’t built for them. “We’re not falling short much, we’re just not optimizing.” The gap shows up most clearly in density. Legacy facilities were designed for roughly 300 to 400 watts per square foot. AI pushes that to 2,000 to 4,000 watts per square foot—changing not just rack design, but the logic of the entire facility. For Altizer, AI-ready infrastructure starts with fundamentals: access to water for heat rejection, significantly higher power density, and in some cases specific redundancy topologies favored by chip makers. It also requires liquid cooling loops extended to the rack and, critically, flexibility in the white space. That last point is the hardest to reconcile with traditional design. “The GPUs change… your power requirements change… your liquid cooling requirements change. The data center needs to change with it.” Buildings are static. AI is not. Rethinking Modular: From Containers to Systems “Modular” has been part of the data center vocabulary for years, but Altizer argues most of the industry is still thinking about it the wrong way. The old model centered on ISO containers. The emerging model focuses on modularizing the white space itself. “We’re not building buildings—we’re building assemblies of equipment.” Compu Dynamics is pushing toward factory-built IT modules that can be delivered and assembled on-site. A standard 5 MW block consists of 10 modules, stacked into a two-story configuration and designed for transport by trailer across the U.S. From there, scale becomes repeatable. Blocks can be placed adjacent or connected to create larger deployments, moving from 5 MW to 10 MW and beyond. The point is not just scalability; it’s repeatability and speed. Altizer ties this directly to a broader shift in how data centers are

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Data centers are moving inland, away from some traditional locations

The future is even less clear the further you go out. The vast majority of data centers planned for launch between 2028 and 2032 have yet to break ground and only a sliver are under construction. Those delays, it seems, appear to be twofold: first, the well-documented component shortage. Not just memory and storage, but batteries, electrical transformers, and circuit breakers. They all make up less than 10% of the cost to construct one data center, but as Andrew Likens, energy and infrastructure lead at AI data center provider Crusoe’s told Bloomberg, it’s impossible to build new data centers without them. “If one piece of your supply chain is delayed, then your whole project can’t deliver,” Likens said. “It is a pretty wild puzzle at the moment.” Second problem is the growing rebellion against data centers, both by citizens and governments alike. The latest pushback comes from the Seminole nation of Native Americans, who have banned data centers on their tribal lands. Of the data centers that are coming online in the next few months, the top states reflect what Synergy has been saying about data center migration to the interior of the country. Texas is leading the way, with 22.5 GW coming online, followed by New Mexico at 8.3 GW and Pennsylvania, which is making a major push for data centers to come to the state, at 7.1 GW.

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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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