How Amazon achieved its 100% renewable energy goal

Investing in 500+ solar and wind projects, bringing carbon-free energy to dirty grids, and buying Renewable Energy Certificates all played a role.

Amazon recently announced that we met our 100% renewable energy goal, seven years early. Making progress like that—especially with operations as complex as ours—isn’t easy, so we wanted to share more about how we were able to get it done. We used a variety of mechanisms, which included investing in new solar and wind projects, supporting projects in countries that still rely heavily on fossil fuels to power their grids (where renewable energy projects are needed the most), and purchasing Renewable Energy Certificates (RECs).

Here's a bit more about seven key steps we took to achieve our goal:

  1. Investing in 240+ utility-scale projects, which deliver new sources of energy to the grid

    We signed agreements with developers and energy companies where we agreed to buy the renewable energy produced by hundreds of utility-scale solar and wind projects, which help make those projects possible and brings large amounts of new renewable energy online. The agreements – known as Power Purchase Agreements (PPAs) – give the developer confidence to buy materials, purchase land, and move forward with the construction. Once built, these projects provide new sources of renewable energy to the grid, helping decarbonize the grid mix – benefitting everyone who uses those grids (including us). In many cases, these projects would not have moved forward if it weren’t for our investment.

  2. Enabling 270 onsite solar projects on Amazon buildings, which bring renewable energy directly to our buildings or the local grid

    We invested in 270 solar arrays on the rooftops and grounds of Amazon fulfillment centers, Whole Foods Market stores, and other facilities. Many of these projects power the Amazon facilities directly, helping defray the amount of energy the buildings need from the grid. Other projects, like the rooftop solar array at the Amazon Air Hub at the Cincinnati/Northern Kentucky International Airport (CVG), sends power to the local grid, helping power nearby homes and businesses.

  3. Bringing new renewable energy to regions where our operations are located

    The majority of the utility-scale projects we invest in connect to grids where we have operations, including our data center regions. For example, in the IAD Region in Northern Virginia, Amazon has invested in 19 solar projects capable of producing a total of 1.3 gigawatts (GW) of renewable energy for the local grid. In our PDX Region in Oregon, Amazon recently invested in Leaning Juniper, a wind farm that is being repowered with enhanced turbine technology to help it produce more energy. In our DUB Region in Ireland, Amazon is collaborating with Bord na Mona Energy park in County Offaly to co-locate data centers with wind projects, and to invest in up to 800 megawatts (MW) of renewable projects across the country.

  4. Bringing new solar and wind projects to dirty grids

    While a lot of our projects bring carbon-free energy to the grids where we have operations, we’re also focused on making the grid cleaner and more reliable for everyone. An emissions-first approach – which prioritizes supporting renewable energy projects in locations and countries that still rely heavily on fossil fuels – is the fastest way to decarbonize global grids. We’ve done this by investing in projects in countries including Poland, Greece, South Africa, and India, where we enabled 50 solar and wind projects – enough to power 1.1 million homes in New Delhi each year. To demonstrate why location matters, by investing in seven utility-scale renewable energy projects in India, instead of a country like Sweden where the grid is already renewable-heavy, we’ve reduced carbon emissions by 18 times. And to encourage other corporate renewable energy buyers to do the same, we created the Emissions First Partnership alongside many other large buyers of renewable energy, including General Motors, Intel, Meta, and Rivian.

  5. Using grids that already have a large amount of renewable energy

    We’re often able to locate projects on grids that already have a large amount of renewable energy, and as part of our renewable energy methodology, we count the renewable energy mix in the grid toward our goal. This means in a country like the U.S., where the grid already runs on 31% renewable energy, we’re able to reach 100% by investing in additional solar and wind projects to cover the remaining 69% of our energy consumption.

  6. Purchasing Renewable Energy Certificates (RECs)

    No company with complex and growing operations is able today to only consume renewable energy – there simply aren’t enough sources in enough locations, and it takes a while for new projects to come online. Like most companies with ambitious climate goals like ours, we also purchase RECs. RECs are used to legally substantiate claims of renewable energy use, and are used by many companies and government agencies, and other entities, like local utilities. They also help make renewable energy investment more inclusive by allowing medium and small businesses to invest in renewable energy projects without having to purchase an entire wind or solar farm, allowing them to also play a role in addressing climate change.

    When Amazon or any other buyer purchases renewable energy, there’s no way to guarantee that the same electron generated by an Amazon-backed project will be the same electron consumed by our data centers, fulfillment centers, or other operations. RECs allow us to account for these electrons, which are still flowing through the grid, and helping power other needs, like energy to run homes and businesses.

  7. Using different kinds of RECs

    Amazon purchases “bundled” and “unbundled” RECs, which we use as a temporary measure. Bundled RECs are purchased alongside our investment in a wind or solar project, and act as a bridge until the project comes online. This is important, because due to grid constraints, many projects are delayed around the world. Across the United States, there are currently more than 260,000 megawatts (MW) of renewable energy and storage projects waiting to connect to the grid—enough carbon-free energy to power 63.3 million US homes.

    Unbundled RECs are purchased independent of a project. The revenue typically supports an existing project, helping with repairs, upgrades and other needs. Both forms of RECs are a fundamental component of the global renewable energy market – and are key to our society’s transition to a carbon-free energy future. Many current renewable energy technologies would not have been financed nor have become operable without the support of REC purchases, according to the American Council on Renewable Energy.

  8. Amazon’s commitment to sustainability

    We are focused on reaching our Climate Pledge to be net-zero carbon by 2040. We know our path won’t be linear, and we’re continuing to innovate in order to add new sources of carbon-free energy to grids around the world.

    We believe in transparency for our customers, employees and partners, and release a voluntary annual Sustainability Report that highlights the work and progress we’re making to become a more sustainable company, across every business in which we operate. This report, including our achievement of our 100% renewable energy goal, is verified by independent external third-party assurors.

    From investing in new carbon-free energy projects to advocating for grid modernization and collaborating with key stakeholders around the world, Amazon is working toward a cleaner energy future.

Research areas

Related content

US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Member of Technical Staff with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Member of Technical Staff with the AGI team, you will lead the development of algorithms and modeling techniques, to advance the state of the art with LLMs. You will lead the foundational model development in an applied research role, including model training, dataset design, and pre- and post-training optimization. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
GB, London
We are looking for an Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Our products are used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. We are looking for an experienced Economist with a deep passion for building econometric solutions and the ability to communicate data insights and scientific vision to execute on strategic projects. Key job responsibilities - Leverage econometrics and ML models to optimize advertising strategies on behalf of our customers. - Influence key business and product decisions based on insights from models you develop. - Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience. - Work closely with software engineers on detailed requirements to productionize the models you build. - Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Work with other scientists, software developers, and product partners to implement your solutions.
US, NY, New York
About Sponsored Products and Brands: The Sponsored Products and Brands (SPB) organization at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About Our Team: The Brand Beacon team is responsible for inventing impressions offerings for brands to increase share of voice via premium experiences, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Senior Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders. * Stay up-to-date with advancements and the latest modeling techniques in the field. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI
US, WA, Seattle
Amazon Industrial Robotics is seeking exceptional applied science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. We're building revolutionary software infrastructure that combines cutting-edge AI, large-scale optimization, and advanced manufacturing processes to create adaptive production control systems. As a Senior Applied Scientist, you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques, evaluate them against representative manufacturing scenarios, and adapt them to meet the robustness, reliability, and performance needs of production environments. You will invent new algorithms where gaps exist. You'll collaborate closely with software engineering, manufacturing engineering, robotics simulation, and operations teams, and your outputs will directly power the systems that determine what to build next, where to allocate resources, and how to maximize throughput. The ideal candidate brings deep expertise in optimization and machine learning, with a proven track record of delivering scientifically complex solutions into production. You are hands-on, writing significant portions of critical-path scientific code while driving your team's scientific agenda. If you're passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today, this role offers the chance to make a lasting impact on the future of automation. Key job responsibilities - Identify and devise new scientific approaches for constraint identification, dispatch optimization, WIP release control, and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented - Lead the design, implementation, and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production - Design and build ML models and optimization algorithms including constraint prediction, starvation risk forecasting, and dispatch optimization - Write a significant portion of critical-path scientific code with solutions that are inventive, maintainable, scalable, and extensible - Execute rapid, rigorous experimentation with reproducible results, closing the gap between simulation and real manufacturing environments - Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone - Influence your team's science and business strategy through insightful contributions to roadmaps, goals, and priorities - Partner with manufacturing engineering, robotics simulation, and applied intelligence teams to ensure scientific approaches are grounded in operational reality - Drive your team's scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations - Actively participate in hiring and mentor other scientists, improving their skills and ability to deliver - Write clear narratives and documentation describing scientific solutions and design choices
US, NY, New York
The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high-effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior Research Scientist on the team, you will be at the forefront of innovation, developing measurement solutions end-to-end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics. Key job responsibilities * Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models that measure the impact of ad spend across multiple platforms and timescales. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Team video https://advertising.amazon.com/help/G4LNN5YWHP6SM9TJ About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
US, WA, Seattle
Amazon's Stores-Ads Science team operates at the intersection of Amazon's Stores and advertising businesses. We develop causal measurement systems, optimization algorithms, and machine learning models that inform how advertising affects shopper engagement, driving selling partner growth and marketplace economics. Our science shapes decisions both at the strategic level and in production systems. We are a team of interdisciplinary scientists who combine causal inference, economic modeling, and machine learning to drive measurable business impact. We are looking for an Applied Science Manager to lead our Ads Impact initiative. This team owns the science of understanding and optimizing how advertising creates value for shoppers and selling partners. What makes this role distinctive is its position at the frontier of AI and Economics: as Amazon's shopping experience evolves from traditional search toward LLM-powered, agentic commerce, the fundamental mechanisms through which advertising creates value are changing. This role will partner with leading scientists and academic researchers to measure these effects through large-scale causal experimentation, and develop novel methods to encode causal and economic reasoning into AI systems that optimize the shopping experience. Key job responsibilities In this role, you will lead a team of scientists, setting the technical vision and science roadmap for ads impact measurement and optimization. You will design experiments that identify the causal mechanisms through which advertising drives shopper engagement, advertiser value, and marketplace outcomes. You will develop optimization algorithms that integrate these causal signals into production and business decision-making, in close partnership with engineering and product teams across the organization. You will lead the research and communicate findings and recommendations to senior leadership through written narratives that connect technical science to business strategy. This role requires deep expertise in causal inference and experimental design, combined with strong applied ML skills and the engineering judgment to translate research into production systems. You will hire and develop future science leaders, think strategically, set ambitious roadmaps in highly ambiguous problem spaces, and foster a culture that values both intellectual depth and production impact. You will work cross-functionally, influencing across organizational boundaries to drive alignment on complex, multi-sided tradeoffs.
US, WA, Seattle
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Recruiting Agents and Candidate Voice team is revolutionizing how Amazon finds and connects with talent worldwide! We're looking for an experienced Applied Scientist to design and implement agentic solutions that help millions of candidates find their dream jobs at Amazon. Key job responsibilities • Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability. • Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey. • Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions. • Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals. • Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.
GB, London
Sr. Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. Develop strategic plans to identify fundamentally new solutions for business problems. Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.
US, WA, Seattle
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Recruiting Agents and Candidate Voice team is revolutionizing how Amazon finds and connects with talent worldwide! We're looking for an experienced Applied Scientist to design and implement agentic solutions that help millions of candidates find their dream jobs at Amazon. Key job responsibilities • Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability. • Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey. • Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions. • Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals. • Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.