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.
Carbon Footprint
Climate-Linked Supply Chain Risk Is Already in Your P&L
The earnings calls that quietly reframed climate from sustainability question to operating risk.
Three earnings calls in the last 18 months tell the story without any help from a press release.
Hershey, May 2024: cocoa price exposure compresses margin, and the company attributes part of the cost shock to West African weather. Olam, July 2024: coffee climate exposure quantified in the annual report. JBS, January 2025: supply chain climate disclosures expanded materially in response to investor pressure and regulatory expectation. None of these companies issued the announcement as climate news. They issued it as financial news. The climate-linked supply chain risk did not arrive with a sustainability framing; it arrived as a P&L line.
You are probably reading this article because you suspect the same thing is happening to your business. This piece walks through what is showing up on which earnings calls, how procurement and finance leaders are quantifying the exposure, and what serious corporates are doing about it before the regulator asks.
Where climate risk has already appeared in earnings
The pattern is consistent across resource-intensive sectors. A weather event compresses supply, the price spikes, the cost flows through the income statement, and the analyst on the call asks whether the event is anomalous or structural. Increasingly, the honest answer is the second one.
Cocoa is the cleanest example. The 2023 to 2024 West African harvest fell sharply on the back of erratic rainfall and disease. Cocoa futures more than tripled. Companies with concentrated West African sourcing absorbed the cost; companies with diversified sourcing absorbed less. The exposure was not climate as ESG topic. It was climate as cost of goods.
Coffee follows the same pattern. Brazilian and Vietnamese harvests have moved on weather more sharply across the last several seasons. Roasters with long-tenor supplier relationships and origin diversification have managed the volatility; roasters with spot-market exposure have not. Wheat, sugar, palm oil, beef: the same dynamic in different commodities, a pattern the IPCC AR6 Working Group II report projects will intensify across agricultural systems through mid-century.
What this means: climate risk is no longer a footnote in the 10-K. It is a line item the CFO has to explain on the call.
The three commodity exposures that hit margin first
For most companies with material Scope 3 exposure, three exposures dominate the near-term P&L risk.
- Concentrated single-origin sourcing in a climate-vulnerable region. If your tier-one supply for any material commodity sits in one geography, you have a concentration risk that climate amplifies. Diversification across origins is the obvious hedge, but it takes years to build and requires relationships you cannot acquire by tender.
- Supplier financial fragility under climate stress. Smallholder farmers, who supply a large share of the global cocoa, coffee, and palm oil market, do not carry the balance sheets to absorb yield shocks. When yields collapse, they exit. When they exit, your supply base shrinks, and the surviving suppliers raise prices. The risk is structural, not cyclical.
- Logistics and storage exposure to extreme weather. Hurricane disruptions to Gulf shipping, drought-driven Panama Canal restrictions, flooding in European inland waterways: each of these has moved input costs in the last three years, a pattern documented in Munich Re’s natural catastrophe data. The exposure shows up as a one-quarter event in the financial press but accumulates over time on the cost line.
TCFD and ISSB disclosure changes
The disclosure architecture has now caught up with the risk. The Task Force on Climate-related Financial Disclosures, whose recommendations are now embedded in the ISSB’s IFRS S2 climate standard, requires companies to disclose climate-related risks across physical and transition categories, with quantification where possible.
For physical risk specifically (the climate-linked supply chain risk you are reading about), the disclosure must address both acute exposures (extreme weather events) and chronic exposures (gradual changes in temperature, precipitation, and growing seasons). The disclosure must address the time horizon over which the risk is material, the parts of the value chain exposed, and the financial impact under different scenarios.
The CSRD imposes similar requirements under European law, with double materiality (both financial and impact materiality) embedded in the assessment. The practical effect: your auditors and your investor relations team now need a defensible answer to the climate-linked supply chain risk question, and the answer needs to be quantified.
What procurement and finance can do now
Three actions matter near-term.
Map your exposure. Most companies do not have a clear view of which tier-one and tier-two suppliers sit in which climate-vulnerable geographies. Without the map, you cannot quantify the risk, and without the quantification, you cannot disclose it credibly. The map is the foundation, and World Resources Institute climate risk research provides useful public tooling to start.
Diversify and deepen, in that order. Diversification across origins reduces concentration risk, but the deeper move is to invest in the resilience of the suppliers you already have. Regenerative practices, agroforestry, soil health interventions: these reduce yield volatility under climate stress and protect your input cost trajectory.
Embed the climate spend inside procurement, not outside it. Treating climate risk as a sustainability cost line subordinates it to the ESG budget. Treating it as a procurement and resilience investment puts it in the budget that matters, which is the cost-of-goods budget that the CFO defends quarterly.
Nature-based supply chain investments are the asset class designed for exactly this purpose. They sit inside the value chain, they reduce climate-linked supply risk, they generate verifiable Scope 3 reductions, and they produce the documentation an auditor and a regulator can both test.
If you are quantifying climate-linked supply chain risk in advance of the next earnings cycle or the next disclosure period, the carbon and sustainability experts at Carbon Credit Capital can help you map your exposure and structure a Dual-Value Model response that addresses reduction, resilience, and disclosure-readiness in a single program. Schedule a consultation.
Carbon Footprint
Where should an SME start with a carbon action plan?
More and more small and medium-sized businesses are hearing the same question from their larger customers: What is your carbon footprint? That question now travels down entire supply chains, and it arrives next to tender requirements, certification criteria, and rising customer expectations.
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Carbon Footprint
Insetting vs Offsetting: Which Actually Counts Toward Your Scope 3 Targets
The accounting differences that decide whether your nature investment shows up in inventory, in BVCM, or nowhere at all.
The question reaches a procurement team about three weeks before the next sustainability committee meeting. Someone has read about insetting. Someone else has just signed off on an offset purchase. The CSO wants to know if the two are interchangeable. The answer is no, and the GHG Protocol Land Sector and Removals Standard is the reason why.
This article walks through what each term means at audit-grade specificity, what the standards actually say about how each gets counted, and how to decide which tool fits which target. The insetting vs offsetting question is one of the most-searched in corporate climate strategy, and one of the most poorly answered. By the end of this piece, you should be able to brief a committee on the difference without notes.
The two definitions, in plain English
Offsetting means buying carbon credits generated outside your value chain and retiring them against your residual emissions. The reduction happens somewhere else, financed by you, and the credit is the receipt.
Insetting means investing in emission reductions or removals inside your own value chain, typically with suppliers, where the reduction is directly linked to the products and services you buy. The reduction happens inside the boundary of your Scope 3 inventory, and the accounting treatment is fundamentally different.
The shorthand from the University of Oxford’s Nature-based Insetting Initiative is useful: insetting is what you do with the supply chain you have; offsetting is what you do with the supply chain you do not have.
What the GHG Protocol Land Sector Standard actually says
The GHG Protocol Land Sector and Removals Standard, finalised in 2024 after a multi-year pilot, sets the rules for how land-based emission reductions and removals enter corporate inventories. The Standard distinguishes between inventory accounting (Scope 1, 2, and 3) and project or intervention accounting (a separate methodology for crediting).
For insetting, the practical implication is that supplier-level interventions, when properly measured and attributed, can reduce your Scope 3 category 1 (purchased goods and services) emissions in your inventory. The reduction is not a credit retired against the inventory; it is a lower inventory number, period.
For offsetting, the credit is retired separately. It can be reported as a contribution toward a net-zero claim under the SBTi Beyond Value Chain Mitigation framework or as part of a VCMI Carbon Integrity claim, but it does not lower the inventory number.
A practical consequence: if your Science Based Target requires a 50% absolute reduction in Scope 3 emissions by 2030, insetting moves you toward the target. Offsetting does not. This single point of difference reshapes the procurement decision.
When insetting counts toward Scope 3 (and when it does not)
Insetting counts toward Scope 3 only when several conditions are met:
- The intervention must occur with an entity in your value chain.
- The emissions reduction or removal must be measured against a defensible baseline.
- The reduction must be attributed to your share of that supplier’s output, not double-counted with other buyers.
- It must follow the inventory accounting rules in the GHG Protocol Land Sector Standard, not the project accounting rules used to generate credits.
The most common failure mode is double counting. If your supplier sells the same reduction as a credit on the voluntary market and also reports it to you as a Scope 3 reduction, the math breaks. The Standard requires you to address this risk, typically by purchasing and retiring the supplier-issued credit as part of your inventory or by contractual provisions that prevent the supplier from selling the reduction twice.
When insetting does not count toward Scope 3: when the intervention sits with a supplier you do not buy from, when the baseline is not defensible, when the attribution is unclear, or when the documentation does not survive audit. Those cases default to Beyond Value Chain Mitigation, which is still useful but operates on a different ledger.
The procurement and supplier engagement question
Insetting is harder than offsetting. That is the unfashionable truth most buyers eventually confront. Offsetting is a transaction; insetting is a relationship.
To run an insetting program, you need supplier mapping precise enough to know which farms or facilities sit at which Scope 3 boundary. You need an engagement model that gets suppliers to participate, which usually requires multi-year commitments and shared economics. You need an MRV architecture that measures the right things and produces audit-ready documentation. And you need a contractual structure that prevents double counting and protects both sides.
The trade-off you receive in return is significant. Reductions count against your inventory rather than your residual. Supplier relationships deepen, which protects sourcing continuity. Yield and quality improvements often follow regenerative interventions, which reduces your input cost over time. And the regulatory file, under CSRD, CSDDD, EUDR, and the SBTi FLAG Guidance, is materially stronger.
Choosing the right tool for the right target
A practical decision rule. If your target is a science-based Scope 3 reduction and you operate in a FLAG sector or source FLAG commodities, insetting is the structurally correct tool. If your target is a net-zero claim that includes neutralising hard-to-abate residual emissions outside your value chain, BVCM via high-integrity offsets is the structurally correct tool. Most companies with material Scope 3 exposure need both, in different proportions, sequenced over time.
The sequencing matters. Insetting takes longer to stand up but produces a permanent reduction in the inventory. Offsetting can be transacted faster but does not change the inventory and now sits under tighter claim restrictions. Treat them as complementary tools with different jobs, not as substitutes. The Accountability Framework Initiative and the IUCN Global Standard for Nature-based Solutions both provide useful guardrails for the insetting side, with biodiversity, human rights, and benefit-sharing requirements that go beyond carbon math.
If you are mapping a Scope 3 reduction roadmap and need to scope which interventions count toward your inventory versus which sit in Beyond Value Chain Mitigation, the carbon and sustainability experts at Carbon Credit Capital can help you structure a nature-based supply chain investment program that fits your FLAG exposure, your target architecture, and your audit horizon. Schedule a consultation.
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