Artificial intelligence moved from a buzzword to a part of everyday life faster than many expected.
As AI continues to transform how we work, learn, and solve problems, it has brought tremendous potential to improve lives, along with real concerns, strong opinions, and important questions about how the technology should be used. Realizing AI's promise while avoiding the risks associated with rapid adoption requires thoughtful choices and responsible action.
As AES helps accelerate the future of energy, we are putting responsible innovation into practice.
A framework built on our core values
Our approach to AI is guided by a simple principle: innovation delivers its greatest value when it is paired with transparency, trust, and accountability.
That’s why we developed nine principles that guide how we design, implement, deploy, and use AI technologies across our business and in collaboration with our customers and partners. These principles include accountability, integrity, fairness, privacy and confidentiality, regulatory compliance, safety and security, traceability and explainability, transparency, and data minimization.
AI creates value when it shapes how work gets done. At AES, these 9 principles are part of building AI, from the quality and ownership of the data through the design, validation, deployment, monitoring, and continued improvement of each solution. Subject Matter Experts define the decisions, outcomes, and ways of working that matter most, while our Digital, Data and AI teams provide the trusted data, engineering capabilities, and governance needed to scale responsibly.
These principles help us strike the right balance between technological progress and responsible stewardship by embedding AI where it creates the most value: augmenting human expertise, improving decisions, and transforming how work gets done without removing people from the lead. They also reflect our commitment to ensuring that AI applications align with AES' values of Safety First, Highest Standards, and All Together, while helping us create meaningful value for customers, communities, and stakeholders.
Responsible AI in action
How do we put these principles into practice across our business? The following examples show how they shape the AI solutions we build and deploy.
- Haven Safety AI (developed by Haven Safety Corporation, a company co-founded by AES and the AI Fund) is an AI-native platform designed to investigate incidents more quickly, identify systemic risks, and help prevent serious injuries before they occur. By applying AI to safety analytics, Haven demonstrates our commitment to the safety and accountability principles: using technology to protect people while keeping humans accountable for decisions.
- Farseer produces hourly, asset-level generation forecasts for wind and solar projects up to 10 days in advance, supporting our Commercial teams in estimating expected generation and adjusting decisions as conditions change. Farseer reflects principles of traceability, transparency, and accountability: it combines machine learning with trusted operational, weather, and market data, supported by strong data controls, business oversight, performance monitoring, and continuous improvement.
- GridSim applies advanced analytics and machine learning to complex interconnection data, providing predictive insight to help development teams evaluate the likelihood of a project advancing, where costs or risks may increase, where additional analysis is needed, and when exiting earlier could protect capital. GridSim does not make investment decisions; it gives development experts a more consistent and transparent way to make disciplined, informed choices. This approach reflects our principles of transparency and human accountability: AI augments expertise without replacing judgment.
- Maximo, an AI-enabled solar installation robot developed by AES, works alongside skilled construction crews, helping improve safety and increase productivity by performing the repetitive heavy lifting associated with solar module installation. Maximo reflects our safety and integrity principles: rather than replacing workers, it augments human capabilities to reduce physical strain and accelerate large-scale renewable energy projects.
AI that empowers our people
What these examples have in common is a people-centered approach. Each one uses AI to strengthen human judgment, improve safety, and help our teams work more effectively. As AI capabilities continue to advance, maintaining human oversight remains essential.
The path is consistent: start with a high-impact business decision, combine trusted data with deep functional expertise, apply AI where it improves foresight or execution, and maintain clear human accountability for outcomes. This is how AES is moving AI beyond experimentation and into the critical workflows and decision making that help us operate more safely, efficiently, and responsibly across the business.
Technology can process vast amounts of information and identify patterns at unprecedented speed, but people provide the judgment, context, and accountability needed to turn insights into meaningful action. That belief shapes how we develop and deploy new tools and how we think about the future of work. It is also reflected in external recognition, including AES being named one of Fortune’s World’s Most Admired Companies and one of Fast Company’s Best Workplaces for Innovators. By combining human expertise with advanced technology, we open the door to new possibilities while maintaining the confidence and mutual trust in our people and partners that long-term success requires.
Energy leadership for the AI era
AES leaders have written previously about the crucial role energy infrastructure plays in enabling AI leadership. Electricity demand continues to increase and reshape how our industry plans for growth.Meeting that demand will require more than new technology. It will require reliable power, smarter systems, and leadership from companies that understand both the opportunities and responsibilities of this moment.
AI can help the industry move faster, solve challenges more effectively, and build a more resilient energy future. But progress must be grounded in trust and focused on delivering real value for people and communities.
At AES, we are committed to pursuing AI in a way that reflects our values, supports our people, and benefits the communities we serve.
Responsible AI is not a destination. As technology evolves, so will our approach. We will continue learning, adapting, and strengthening our practices so AI remains a force for positive impact and helps power a bright energy future.
