Connect with us

Published

on

AI Energy

AI is a powerful force driving innovation across industries in today’s rapidly evolving technological landscape. However, as AI capabilities expand, so does its appetite for energy. This phenomenon has brought the intersection of AI and energy into sharp focus, particularly in the context of global decarbonization efforts.

The Interplay of AI and Renewable Energy

The rise of AI has spurred an unprecedented demand for computing power, much of which is supplied by data centers. 

These data giants consume vast amounts of electricity, prompting concerns about their environmental impact and contribution to carbon emissions. Some argue that these companies have the resources and the motivation to invest in cleaner energy technologies. They can also advocate for policy changes to support decarbonization efforts. However, others raise concerns about the environmental impact and the need for greater transparency and accountability in their sustainability initiatives.

Amidst the urgency to transition to renewable energy sources, the energy consumed by AI presents a significant challenge to decarbonization efforts.

On one side, the influx of demand from tech giants could provide a financial boost to investments in renewables, potentially accelerating the transition to cleaner energy sources. However, there remains a tangible risk that the energy demands of AI will be met using conventional, fossil fuel-based methods, such as natural gas or coal. This scenario would undermine progress toward decarbonization goals and perpetuate reliance on non-renewable resources.

Thus, navigating this decarbonization dilemma requires balancing the transformative potential of AI and mitigating its environmental impact. 

  • It calls for strategic investments in renewable energy infrastructure with AI technology innovation to optimize energy efficiency. 
  • Collaborative efforts between tech companies, energy providers, policymakers, and environmental advocates are essential to charting a sustainable path forward.

A Bloomberg analysis reported, that traditional energy corporations like PPL Corp., Alliant Energy Corp., WEC Energy Group Inc., Entergy Corp., Duke Energy Corp., NextEra Energy Inc., DTE Energy Co., CenterPoint Energy Inc., and Vistra Corp., are also deeply involved in navigating the challenges and opportunities presented by AI and data centers.

These companies face pressure to optimize their operations for efficiency, reliability, and sustainability. AI technologies offer opportunities to enhance grid management, predict demand more accurately, optimize energy distribution, and improve maintenance scheduling. Moreover, these corporations will likely explore AI-driven solutions to meet regulatory requirements and customer demands for cleaner energy sources.

As AI becomes increasingly integral to various industries, including energy, investors will evaluate companies based on their AI capabilities and ability to adapt to technological advancements.

The automation era in the energy sector

This futuristic vision is swiftly materializing – the AI in energy and power market is forecasted to surge at a CAGR of 24.68%, from a value of US$3.103 billion in 2021 to US$14.527 billion by 2028.

AI energy

AI-Growth Drivers Transforming the Energy Companies

From predictive maintenance to demand forecast, AI-powered solutions are revolutionizing traditional practices and reshaping the industry.

1. Predictive Maintenance: Preventing Downtime, Maximizing Efficiency

By analyzing vast amounts of data from sensors and equipment, AI algorithms can detect anomalies and predict potential failures before they occur. This approach not only minimizes downtime but also maximizes the lifespan of critical assets. It further leads to substantial cost savings for energy companies.

2. Optimized Asset Management: Maximizing Returns on Investments

AI-driven asset management solutions enable energy companies to optimize the performance of their infrastructure. Through real-time monitoring and analysis, AI algorithms can identify opportunities for efficiency improvements and asset optimization. AI empowers companies to make data-driven decisions that enhance profitability and sustainability.

3. Dynamic Demand Forecasting: Balancing Supply and Demand

Accurate demand forecasting is essential for energy companies to manage supply and avoid costly overproduction or shortages. AI-powered demand forecasting models leverage historical data, weather patterns, market trends, and other variables to predict future demand with precision. By optimizing resource allocation and scheduling, energy companies can minimize waste and maximize revenue, ultimately improving cost efficiency.

4. Enhanced Customer Engagement: Personalized Services and Solutions

AI technologies also enable energy companies to enhance customer engagement by offering personalized services and solutions. Data analytics and machine learning empower companies to customize offerings based on individual customer preferences and behavior.

AI energy

source: Data Dynamics

Moving on, we can see the top energy giants using AI in their operations  

Top Energy Giants using AI in their Operations  

These energy companies exemplify the strategic adoption of AI to enhance their operational capabilities, driving efficiency gains and ultimately contributing to their bottom line.

Exxon Mobil

Exxon Mobil integrates AI to enhance operational efficiency and reliability across its operations. It collaborates with IBM to use quantum computing in advancing AI-driven simulations. Additionally, they use AI for critical calculations to optimize CCS methods. 

  • Enhances its operational efficiency, minimizes downtime, and reduces maintenance costs with AI-driven predictive maintenance and process optimization. 
  • The AI-powered analytics enable the company to optimize supply chain management.
  • Subsequently, it ensures timely delivery of products to customers while minimizing transportation costs and environmental impact.

ABB

The Swiss technology leader in electrification and automation is a pioneer in AI usage. The company

  • Utilizes AI to identify faults like pipeline and machinery cracks through image analysis. 
  • Manages distributed energy resources for reliable green power.
  • Employs AI to analyze seismic data for optimizing oil extraction.

Schneider Electric

It uses Microsoft’s machine learning to remotely monitor and configure pumps in oil and gas fields. AI can detect pump failures, prevent weeks of downtime, and repair costs of up to $1 million.

BP

The London-based gas and oil giant leverages AI to enhance decision-making processes, optimize resource allocation, and improve safety standards. AI boosts the oil extraction and recovery process with high-end sensors. It further lowers the cost/ barrel, reduces risk, and ensures compliance. 

Notably, BP is one of Amazon’s most trusted cloud computing clients.  It has used its technology to enhance the performance of its lubricants ERP system with 40% faster response times.

Royal Dutch Shell

Shell implements AI technologies to streamline operations, drive innovation, and enhance overall performance. It utilizes Microsoft’s cloud-centric platform, Azure. By leveraging AI technologies, Shell aims to boost revenue, cut costs, and enhance operational safety, such as monitoring data from drill sensors deep underground.

Gretchen Watkins, President of Shell Oil Company, revealed at the CERAWeek energy conference that,

Shell employs AI algorithms for drilling in wells in the Permian Basin. These algorithms, driven by machine learning, facilitate safe, reliable, and cost-effective operations.

The Top 10 AI-powered solutions in the Energy and Power Sector and their Stocks to Watch Out

AI

The U.S. Department of Energy established the Artificial Intelligence and Technology Office (AITO) to elevate it into a global leader in AI

AITO is responsible for reliable AI governance and capabilities in energy infrastructure, advising on trustworthy AI/ML strategies. It fosters partnerships, policies, and innovations in AI and energy across public, private, and international sectors. AITO further supports Department of Energy program offices to implement AI/ML strategies. 

Overall, the relationship between AI, energy, and decarbonization efforts is complex and multifaceted, and addressing the challenges it presents will require collaboration across industries and disciplines.

The post Wired for Change: AI, Energy, and the Decarbonization Dilemma appeared first on Carbon Credits.

Continue Reading

Carbon Footprint

Conflict in the Middle East Threatens Carbon Capture Buildout: What It Means for the Global CCUS Market?

Published

on

Conflict in the Middle East Threatens Carbon Capture Buildout: What It Means for the Global CCUS Market?

The conflict in the Middle East is raising doubts about major carbon capture projects in the Gulf region. Carbon capture, utilization, and storage, known as CCUS, is a technology that prevents carbon dioxide (CO₂) from entering the atmosphere. It captures CO₂ from industrial sources and stores it underground or uses it in industrial processes. CCUS is seen as crucial for cutting hard‑to‑abate emissions from oil, gas, cement, and steel.

Gulf Ambitions Hit the Pause Button

Before the conflict, Gulf plans aimed for about 20 million tonnes per year (Mtpa) of CCUS capacity by 2030. This would have positioned the region as a key global hub. But Rystad Energy says this is now unlikely. The pipeline may shrink closer to the lower case of around 12 Mtpa by 2035 due to delays and repriced risk. 

impact of middle east conflict to CCUS in gulf
Source: Rystad Energy

The Gulf’s CCUS buildout has strong logical drivers. The region has abundant oil and gas operations, and projects often connect to those facilities. However, when the upstream energy system is disrupted, CCUS plans can be delayed, pushed back, or re‑evaluated. This change affects investors’ view of CCUS as a near‑term investment in the region.

Rising Costs and Risk Reprice Carbon Capture

One major risk from prolonged conflict is rising energy costs. If energy prices jump — which often happens during regional conflict — the cost to capture and transport CO₂ also rises.

Rystad’s analysis shows that a 50 % rise in energy prices could increase capture and transport costs by about 30 %. That could push the cost of capturing a tonne of CO₂ well above the price range expected by 2030 in the European Union’s emissions trading system. 

  • The analysis suggests an increase from $95 per tonne to $124 per tonne using a ‘middle impact’ case, where energy prices rise about 50%.
ccus cost impact of energy price increase
Source: Rystad Energy

Higher costs come from more expensive power, higher equipment prices, and slower supply chains. All these pressures hit CCUS projects hard because they are already more costly than conventional infrastructure.

Energy‑intensive capture systems need cheap, reliable supplies of power and materials. Rising inflation and disrupted supply chains could reduce availability and slow project build‑outs. 

Longer project timelines may also raise the cost of capital. Investors typically demand higher returns when projects take longer or face greater uncertainty. In some cases, projects may only move forward if they are supported by governments or strategic partners, especially when the cost per tonne of CO₂ captured rises above key benchmarks. 

Global CCUS Market Still Expanding

While the Gulf faces near‑term risks, the global CCUS market has continued to grow. A large number of projects are being developed worldwide.

As of 2025, ~628 CCUS projects are tracked globally across all stages, with potential capture capacity exceeding 416 Mtpa if completed. Operational capacity reached 64 Mtpa from 77 facilities. The breakdown by number of facilities and total capture capacity is as follows:

commercial CCS facilities capacity and projects 2025 H1
Source: Global CCS Institute

The market is growing because many governments and companies have adopted emission‑reduction mandates. About 63 % of industries say these mandates accelerate CCUS deployment.

  • Nearly 55 % of new CCUS projects are integrated with other low‑carbon technologies like hydrogen or renewable energy.
CO₂ capture capacity of commercial CCS facility
Source: Global CCS Institute

North America leads global capacity, accounting for about 46 % of total CCUS project capacity. Europe holds around 26 %, Asia‑Pacific about 21 %, and the Middle East & Africa roughly 7 % of the total project pipeline.

The oil and gas sector remains the largest user of CCUS, making up about 53 % of the global captured CO₂. Industrial decarbonization in sectors like cement and steel now represents around 25 % of the planned capacity worldwide. 

operational CCS capacity per region
Source: IEA estimations

Market research also shows that the CCS market size was estimated at about USD 3.9 billion in 2025, growing at a compound annual growth rate (CAGR) of 7 % to reach USD 6.7 billion by 2033. This growth reflects rising investments in decarbonization technologies across industrial and power sectors.

Long-Term Outlook: The Gigaton Challenge

CCUS projects are growing, but still fall far short of what climate models recommend. A recent Rystad Energy forecast suggests that global CCUS capacity could expand to more than 550 million tonnes per year by 2030. That’s more than a tenfold increase over today’s roughly 45 million tonnes per year of captured CO₂.

However, this projected expansion is still far below what many climate scenarios require. Limiting global warming to under 2 °C often needs CCUS to capture nearly 8 gigatonnes of CO₂ each year by 2050 in many energy transition models. That means growth must accelerate sharply after 2030 to meet climate goals.

The IDTechEx forecast shows a strong long‑term outlook for CCUS. It estimates global capture capacity will hit around 0.7 gigatonnes per year by 2036. This indicates rapid growth, with a CAGR over 20% from 2026 to 2036. This would place CCUS as a major technology in global decarbonization, if investment and deployment scale up quickly.

What This Means for the Gulf and the World

For the Gulf region, rising geopolitical risk is changing how CCUS projects are evaluated. Many planned build‑outs linked to oil and gas value chains may be slowed or repriced as risk premiums rise.

Some analysts now expect that Gulf CCUS capacity may align with a more cautious trajectory through the mid‑2030s rather than a rapid 2030 build‑out. Moreover, the 8 Mtpa shortfall equals 1.5% of the projected 550 Mtpa global capacity, placing intense pressure on North America and Europe to accelerate.

Rising costs from energy price shocks further complicate the equation. With Middle East & Africa capacity shrinking from 7% to ~4% of the total pipeline, US 45Q projects and EU ETS industrial clusters must find enough replacement capacity.

Still, global drivers for CCUS remain strong. Governments and companies worldwide continue to plan and build projects. New technologies and integrations with hydrogen, renewable energy, and industrial clusters could help spread costs and scale the technology.

As many countries expand their net‑zero plans, CCUS will play a key role in managing emissions that are difficult to eliminate through electrification or fuel switching alone.

In this evolving landscape, the CCUS market is poised for significant long‑term growth, but near‑term geopolitical disruptions and cost pressures will require careful planning, strong policy support, and sustained investment. Strategic partnerships and global cooperation will be key to ensuring that CCUS can meet both economic and climate goals.

The post Conflict in the Middle East Threatens Carbon Capture Buildout: What It Means for the Global CCUS Market? appeared first on Carbon Credits.

Continue Reading

Carbon Footprint

Indigenous and local knowledge in carbon projects: why it defines credit quality

Published

on

Carbon buyers are asking better questions: permanence risk, additionality, co-benefits, and third-party verification, has all become vital considerations. The due diligence applied to nature-based carbon credits has grown sharper and more rigorous over the past few years. Yet one factor consistently sits at the edges of buyer evaluation: Whether the communities living on and around the project land are genuinely embedded in its design, management, and long-term success.

Continue Reading

Carbon Footprint

AI vs. Climate Reality: Why Big Tech Is Buying Millions of Carbon Credits

Published

on

The artificial intelligence (AI) boom has entered a new phase. It is no longer just about innovation or market dominance. Instead, it is now deeply tied to energy demand, emissions, and capital discipline. As a result, the rapid expansion of AI infrastructure is pushing Big Tech into an uncomfortable position—balancing climate commitments with rising environmental costs.

Data compiled for CNBC by carbon management platform Ceezer shows a sharp rise in carbon credit purchases across the sector. Companies are scaling AI aggressively, yet at the same time, they are leaning more heavily on carbon markets to offset the emissions they cannot yet avoid.

This shift is not happening in isolation. It reflects a broader structural tension between growth, sustainability, and financial performance.

AI Expansion Is Driving Both Emissions and Offsets

Tech giants such as Alphabet, Microsoft, Meta, and Amazon are collectively expected to spend close to $700 billion this year to scale their AI capabilities. This includes building hyperscale data centers, deploying advanced chips, and expanding global cloud infrastructure.

However, these investments come with a high environmental cost. AI systems require vast computing power, which in turn demands continuous electricity and cooling. Water use is also rising, particularly in large data center clusters. Consequently, emissions are increasing even as companies reaffirm their net-zero ambitions.

This is where carbon credits play a growing role. Each credit represents one metric ton of carbon dioxide either reduced or removed from the atmosphere. By purchasing these credits, companies aim to offset emissions that remain difficult to eliminate in the short term.

Yet this approach raises a fundamental question. Are carbon credits acting as a bridge to decarbonization—or becoming a substitute for it?

AI growth carbon credits

A Market Surge Signals Structural Dependence

The scale of growth in carbon credit purchases suggests a structural shift rather than a temporary adjustment.

In 2022, permanent carbon removal purchases across these companies stood at just over 14,000 credits. Within a year, that figure jumped dramatically to 11.92 million. The momentum did not slow. Purchases increased to 24.4 million in 2024 and then surged to 68.4 million in 2025.

This exponential rise highlights how quickly AI-driven emissions are feeding into carbon markets. More importantly, it shows that demand for high-quality removal credits is accelerating faster than supply.

At the same time, companies are not relying on a single solution. Their portfolios include nature-based projects such as forestry and soil carbon, alongside engineered approaches like direct air capture. Long-term offtake agreements are also becoming more common, helping secure future credit supply while supporting project development.

However, the rapid increase in demand raises concerns about market depth. High-integrity carbon removal credits remain scarce, and scaling them is both capital-intensive and time-consuming.

Microsoft Sets the Pace—but Questions Remain

Among its peers, Microsoft has taken a clear lead in carbon removal efforts. The company reported a 247% increase in credit purchases between fiscal 2022 and 2023, followed by a further 337% jump in 2024. Growth continued into the next fiscal year, roughly doubling again.

More notably, Microsoft expanded its carbon removal agreements to 45 million metric tons of CO₂ in 2025, up from 22 million tons the previous year. These agreements span multiple geographies and technologies, reflecting a diversified approach to carbon removal.

carbon removal credits microsoft

The company is now a top climate leader, intending to become carbon-negative by 2030. Its strategy emphasizes reducing emissions first and then removing what cannot be avoided.

However, a key gap remains. It has not explicitly tied its carbon credit strategy to its AI expansion. While the correlation is clear, the lack of direct disclosure leaves room for interpretation.

This ambiguity is not unique to Microsoft. It reflects a broader issue across the sector, where sustainability narratives are evolving faster than reporting frameworks.

Free Cash Flow Pressures Are Becoming Harder to Ignore

While environmental concerns are rising, financial pressures are also building.

The CNBC report further highlighted that the scale of AI investment is unprecedented. As companies ramp up spending, free cash flow is beginning to decline. The four largest U.S. tech firms generated a combined $237 billion in free cash flow in 2024. That figure dropped to $200 billion in 2025, and further declines are expected.

This trend signals a shift in capital allocation. Companies are prioritizing long-term growth over short-term financial efficiency. However, this comes at a cost. Lower cash generation reduces flexibility and may increase reliance on external financing.

For instance, Alphabet raised $25 billion through a bond sale in late 2025, while its long-term debt rose sharply to $46.5 billion. This move underscores how even cash-rich companies are turning to debt markets to sustain their AI ambitions.

carbon credits investment

For investors, the implications are significant. The AI story remains compelling, but it now comes with margin pressure, delayed returns, and increased financial risk.

Renewables Help Stabilize Emissions—but Not Fully

Despite the rise in emissions, the increase has not been as steep as some feared. This is largely due to the rapid adoption of renewable energy.

Hyperscalers have expanded their clean energy portfolios, securing power purchase agreements and investing in renewable projects. As a result, they have been able to offset part of the additional demand created by AI workloads.

Ceezer’s data suggest that while emissions rose alongside AI growth, the increase was relatively moderate. This indicates that companies are responding quickly by integrating renewable energy into their operations.

However, this strategy has limits. Renewable energy can reduce operational emissions, but it cannot fully eliminate the impact of rapid infrastructure expansion. As AI demand continues to grow, the gap between emissions and reductions may widen.

Stricter Rules Are Reshaping Carbon Credit Use

At the same time, the regulatory landscape for carbon credits is becoming more stringent. New frameworks are redefining how companies can use offsets within their climate strategies.

Initiatives such as the VCMI Scope 3 Action Code now allow limited use of high-quality credits, but only under strict disclosure conditions. Meanwhile, the Science Based Targets initiative (SBTi) continues to refine its guidance, particularly as Scope 3 emissions remain difficult to reduce.

The challenge is substantial. The global Scope 3 emissions gap is estimated at 1.4 billion tonnes and could increase significantly by 2030. This creates pressure on companies to find credible solutions without over-relying on offsets.

In parallel, disclosure frameworks such as CSRD are pushing companies to provide detailed explanations of their carbon credit strategies. This includes justifying project selection, verifying credit quality, and demonstrating measurable impact.

The direction is clear. Carbon credits are no longer a simple compliance tool. They are becoming part of a broader accountability framework.

Carbon Removal Market Expands—but Supply Constraints Persist

The carbon removal market is growing rapidly, yet it remains constrained.

MSCI Projections suggest the global carbon credit market could exceed $30 billion by 2030. Corporate demand for carbon removal credits may surpass 150 million metric tons annually within the same timeframe.

msci carbon market

However, supply is struggling to keep pace. High costs remain a major barrier, particularly for advanced technologies such as direct air capture, where prices often exceed $100 per ton.

In 2025, offtake agreements reached $13.7 billion, reflecting a strong corporate commitment. Yet these agreements will deliver only 78 million credits over the next decade. Actual durable carbon removal credits retired in the same year remained below 200,000.

This mismatch highlights a key issue. While demand is accelerating, real-world deployment is lagging. As a result, the market faces both growth potential and structural limitations.

carbon offtake big tech
Source: Sylvera

The Bottom Line: A Delicate Balancing Act

Big Tech’s AI expansion is reshaping both the digital economy and the carbon market. On one side, companies are investing heavily in future growth. On the other hand, they are navigating rising emissions, tighter regulations, and increasing financial pressure.

Carbon credits are playing a critical role in bridging this gap. However, they are not a long-term solution on their own.

The path forward will require a more balanced approach—one that combines technological innovation with real emissions reductions and transparent reporting. Companies must prove that their climate commitments are more than offset strategies.

At the same time, investors will need to adjust expectations. The AI boom promises strong returns, but it also introduces new risks. Lower cash flow, higher capital intensity, and evolving climate obligations are all part of the equation.

Ultimately, the success of this transition will depend on execution. The companies leading the AI race must now show they can scale responsibly—without compromising either financial stability or climate credibility.

The post AI vs. Climate Reality: Why Big Tech Is Buying Millions of Carbon Credits appeared first on Carbon Credits.

Continue Reading

Trending

Copyright © 2022 BreakingClimateChange.com