OpenAI, ChatGPT maker, and AMD have signed a multi-year deal for AMD to supply chips that will power OpenAI’s future AI systems. As part of the deal, OpenAI will get warrants that allow it to buy up to 10% of AMD’s shares — about 160 million shares — at a very low price. These shares will only be available if OpenAI meets certain goals in performance and deployment.
OpenAI plans to start using 1 gigawatt of computing power with AMD’s new Instinct MI450 chips by the second half of 2026. Over time, this could grow to as much as 6 gigawatts of AI computing power.
The move shows OpenAI’s plan to reduce its heavy dependence on Nvidia. Nvidia remains an important partner, as it has already agreed to provide up to 10 gigawatts of computing power under its own deal with OpenAI. The AMD agreement is not exclusive, which means OpenAI can still work with other chip makers in the future.
AMD CEO, Lisa Su, noted in an interview that:
“You need partnerships like this that really bring the ecosystem together to ensure that, you know, we can really get the best technologies, you know, out there…So we’re super excited about the opportunities here.”
Numbers That Matter: The $100B Power Play Behind OpenAI’s AI Engine
Experts believe the AMD–OpenAI deal could bring AMD tens of billions of dollars in new yearly revenue. It could also generate over 100 billion dollars in new income for OpenAI and its clients over four years.
After the announcement, AMD’s stock rose sharply by over 30% trading. On the other hand, Nvidia’s shares dropped slightly, as investors worried about new competition in the AI chip market.
AMD currently has about 1.62 billion shares in total. The warrants given to OpenAI will only be valid if AMD meets specific stock price and performance goals — including reaching $600 per share for the final stage. These financial terms show how large this partnership could become and how much confidence investors now have in AMD’s growing role in AI hardware.
Chip Chess: AMD, Nvidia, and OpenAI’s Strategic Power Moves
Nvidia’s earlier deal with ChatGPT’s owner included up to 10 gigawatts of computing systems. The new AMD partnership doesn’t replace Nvidia — it expands OpenAI’s supply options. The rollout is expected over several years, with the first systems planned for 2026.
- READ MORE: NVIDIA Stock Surges on $100B OpenAI and $5B Intel Deals: Driving Sustainable AI Computing
However, there are risks. AMD must prove that its chips can perform as well as Nvidia’s in speed, power efficiency, and reliability. There are also challenges in scaling up production, securing parts, and meeting OpenAI’s demanding timelines.
The warrants are split into parts (“tranches”) tied to both AMD’s stock performance and the rollout of AI systems. That means OpenAI’s potential ownership depends on how well AMD performs.
This deal impacts each of the companies involved:
- OpenAI gains a second major chip supplier, reducing its risk of relying on one company. It also strengthens ties with AMD through possible ownership, helping it expand its AI computing capacity over time.
- AMD earns a major boost in reputation and a long-term client in OpenAI. The deal supports AMD’s AI growth strategy and could help it compete with Nvidia. But it also adds pressure to meet production goals, manage costs, and hit strict performance targets.
- Nvidia faces stronger competition in the AI chip space. This could affect its prices and profit margins over time. To stay ahead, Nvidia will likely focus on improving chip efficiency, system integration, and value-added services while monitoring demand shifts between itself and AMD.
RELATED: TSMC Dominates AI Chip Market with Record Sales—But Can It Tackle Its Rising Emissions?
The Carbon Cost of Intelligence: AI’s Growing Energy Appetite
While this deal is a big step in business and technology, it also raises environmental, social, and governance (ESG) concerns — especially around power use and emissions.
Wired for Power: How 6 Gigawatts Could Change AI’s Footprint
AI data centers use huge amounts of electricity. The International Energy Agency (IEA) says power demand from global data centers could more than double by 2030, reaching around 945 terawatt-hours — about the same as Japan’s total power use today. In developed countries, data centers could drive over 20% of all electricity demand growth.
Deloitte estimates that in 2025, data centers will use around 536 terawatt-hours of power — about 2% of the world’s total. By 2030, this could exceed 1,000 terawatt-hours.
Some studies suggest AI systems alone might take up nearly 50% of all data center energy use by late 2025, using about 23 gigawatts of power — roughly equal to the total electricity demand of small countries.
If global AI hardware demand hits between 5.3 and 9.4 gigawatts in 2025, total energy use could reach 46 to 82 terawatt-hours — similar to what Switzerland or Finland uses each year. That means OpenAI’s 6-gigawatt deployment with AMD could consume a major share of global power, depending on how efficiently it runs.
A single high-end training node with eight GPUs can draw up to 8.4 kilowatts of power when training AI models like ChatGPT. Scaled across thousands of nodes, total power use becomes massive.
- INTERESTING READ: ChatGPT, Gemini, and DeepSeek Are on an AI Race – But at What Climate Cost? A Comparison
Silicon and Sustainability: The Hidden Cost of Making AI Chips
AI chips also affect the environment during manufacturing. Producing GPUs requires mining rare minerals, refining metals, and making semiconductors — all of which use a lot of energy and create waste.
Studies show that while power use has the largest climate impact, making the chips themselves also causes issues like mineral depletion, water pollution, and toxic waste. Some estimates say training advanced AI models can use up to 4,600 times more energy than older machine-learning systems.
If AI adoption continues to grow quickly, its total electricity use could increase 24 times by 2030. Because of this, researchers and companies are exploring ways to make AI more energy-efficient.
Smaller and optimized models can cut energy use by nearly 28% without much loss in accuracy. Streamlining data and removing extra model layers can lower energy needs by more than 90% in some cases.
The researchers noted that in the U.S., using more efficient AI models could save about 16.25 terawatt-hours of power in 2025 — the same amount as two nuclear plants produce in a year. By 2028, the savings could reach 41.8 terawatt-hours, equal to seven nuclear plants. These cuts show how choosing better models can greatly reduce the energy use of data centers and make AI more sustainable.
Greening the Grid: Can AMD, Nvidia, and OpenAI Align AI with ESG?
From an ESG standpoint, the AMD–OpenAI deal puts pressure on all three companies — OpenAI, AMD, and Nvidia — to act responsibly as AI expands. They are expected to:
- Disclose how much energy and emissions come from their AI systems.
- Use renewable energy or carbon offsets to power their data centers.
- Build strong governance rules to ensure fairness, privacy, and transparency in AI use.
- Be accountable to investors, regulators, and the public about their environmental and social impacts.
Some experts recommend that companies fully integrate ESG principles into AI projects — assessing environmental and social risks early, applying strong oversight, and aligning goals with long-term sustainability.
The AMD–OpenAI deal marks a new chapter in the AI hardware race. It could reshape how computing power is built, supplied, and shared between tech leaders. But as AI infrastructure grows, so will its energy demands. Balancing performance with sustainability will be one of the biggest challenges for the big tech in the years ahead.
The post AMD Stock Skyrockets with OpenAI Deal, Sparking a New Challenge to Nvidia’s AI Dominance appeared first on Carbon Credits.
For most businesses, the emissions that matter most sit outside their own walls. Scope 3 emissions, everything generated across your value chain, from the suppliers who make your inputs to the customers who use your products, typically make up the majority of a company’s total carbon footprint. Under the Corporate Sustainability Reporting Directive (CSRD), those value-chain emissions now have to be measured and disclosed with a rigour that spend-based estimates alone struggle to satisfy. This guide sets out how to improve Scope 3 data accuracy for CSRD: the calculation methods open to you, how to move from estimates to verified supplier data, and how to govern that data so it holds up to audit.
A carbon credit is a commitment that extends well into the future. The tonne of CO₂ compensated for today from a nature-based carbon project must remain out of the atmosphere for good, which means the forest behind the credit has to remain standing long after the transaction is complete. For any buyer, this raises a defining question: What ensures that the forest endures?
What replaced the cheap REDD credit on the boardroom slide deck, and why procurement is leading the rewrite.
Three years ago, a corporate slide showing a portfolio of cheap REDD+ credits could carry a board meeting. The number was big, the price was low, and the press release wrote itself. Today, that same slide gets sent back with questions. The questions are uncomfortable, the answers are unclear, and your general counsel is suddenly in the room.
Conventional carbon offsets are not dead. The voluntary carbon market retired 202 million tonnes in 2025, and the Morgan Stanley Institute for Sustainable Investing survey published in January 2026 confirmed that interest from corporate buyers remains substantial. What changed is the credibility threshold. The integrity floor has risen, the disclosure scrutiny has tightened, and the buyer profile has shifted. This article tracks what changed, what sophisticated buyers now ask before signing, and what serious corporates are putting on the board slide instead.
What boards used to buy, and why it stopped working
The 2020 to 2022 model was simple: buy a large tranche of avoidance credits at low single-digit prices, retire them against the company footprint, announce the carbon-neutral claim, and move on. Most of those credits came from REDD+ projects, renewable energy installations in countries where the renewable energy was already economic, or methane projects with thin documentation.
Several things broke that model. Academic research published in 2023, including a widely cited Science paper, found that the majority of REDD+ credits issued under the most common methodologies did not represent additional reductions when tested against rigorous counterfactuals. The Voluntary Carbon Markets Integrity Initiative published its Claims Code of Practice, which sets requirements for what companies can credibly claim from credit use. The European Union finalised its Green Claims Directive, restricting how companies can describe products as climate-neutral. France’s Décret 2022-539 already restricts carbon neutrality advertising. California’s AB 1305 imposes disclosure requirements on any company making net-zero or carbon-neutral claims while doing business in the state.
The collective effect: the cheap credit no longer buys the announcement, and the announcement now carries litigation risk.
The integrity reset: ICVCM, VCMI, and what changed
The Integrity Council for the Voluntary Carbon Market published the Core Carbon Principles in 2023 and began assessing methodologies against them in 2024. The first methodologies received the CCP label later that year. The point of the label is to give corporate buyers a defensible quality screen they can cite in disclosure.
The Voluntary Carbon Markets Integrity Initiative complements this on the demand side. Its Claims Code of Practice defines what a buyer can say (Silver, Gold, or Platinum claims, with associated requirements) based on the quality of credits used and the underlying decarbonisation strategy. Together, CCP and VCMI build a quality stack: CCP on the supply, VCMI on the claim, with the science-based target sitting underneath both.
The reset is not a ban on offsets. It is a ratchet. Credits that meet the new bar continue to clear; credits that do not, do not. The Morgan Stanley survey found that 61% of current buyers like the CCP label concept but that supply of labelled credits remains limited. That supply constraint is now visible in pricing.
What sophisticated buyers ask before they sign
The questions on the procurement scorecard have changed. A 2022 buyer might have asked about price, vintage, and project type. A 2026 buyer asks five different questions before any of those.
- What does the counterfactual look like, and who validated it.
- What is the permanence regime, and what is the buffer pool exposure.
- What is the leakage risk, and how is it mitigated.
- What rating has the project received from the independent ratings agencies (Sylvera, BeZero, Calyx Global), and what was the rationale.
- What is the documentation discipline that survives an audit four years from now when the procurement team that signed the contract has moved on.
If the vendor cannot answer those five questions on a first call, the conversation ends. Conversely, if the vendor can answer them with documented specificity, the conversation often expands beyond a single transaction toward a multi-year engagement.
Where this leaves your near-term commitments
You probably have near-term commitments that pre-date the integrity reset. Public targets to be carbon neutral by 2025 or 2030. Product-level claims that ran in last year’s marketing. Disclosed reduction trajectories that assumed continued access to cheap credits.
You have three workable paths. The first is to re-baseline your strategy, replacing the most exposed credits with higher-quality alternatives and adjusting the public language to match what you can defend. The second is to shift the underlying spend from offsetting outside your value chain to investing inside your value chain, where reductions count against Scope 3 directly and the audit trail is cleaner. The third is to keep the strategy and absorb the risk, which is increasingly the most expensive option once you price in litigation, restatement, and reputational exposure.
Most serious buyers are choosing the second path. It moves the carbon spend from a compliance cost to a procurement and resilience investment, and it removes the central failure point of the legacy model: the disconnect between where the emissions occurred and where the reductions sat. Nature-based supply chain investments, structured under the GHG Protocol Land Sector and Removals Standard and aligned to the SBTi FLAG Guidance, are the asset class that fits this brief. They generate inventory-grade reductions, they produce audit-grade documentation, and they survive the new claim restrictions because the carbon math sits inside the value chain that the disclosure already covers.
If you are reassessing a carbon strategy under the new integrity bar, or rebuilding a board narrative that has to survive a more skeptical audience, the carbon and sustainability experts at Carbon Credit Capital can help. The Dual-Value Model gives you a defensible alternative to legacy offset purchases, with the documentation and operational integration that survives the procurement scorecard and the audit. Schedule a consultation.
-
Climate Change11 months ago
Guest post: Why China is still building new coal – and when it might stop
-
Greenhouse Gases11 months ago
Guest post: Why China is still building new coal – and when it might stop
-
Greenhouse Gases2 years ago嘉宾来稿：满足中国增长的用电需求 光伏加储能“比新建煤电更实惠”
-
Climate Change2 years ago嘉宾来稿：满足中国增长的用电需求 光伏加储能“比新建煤电更实惠”
-
Climate Change2 years ago
Bill Discounting Climate Change in Florida’s Energy Policy Awaits DeSantis’ Approval
-
Renewable Energy9 months agoSending Progressive Philanthropist George Soros to Prison?
-
Carbon Footprint2 years agoUS SEC’s Climate Disclosure Rules Spur Renewed Interest in Carbon Credits
-
Greenhouse Gases1 year ago
嘉宾来稿：探究火山喷发如何影响气候预测