AES Deploys AI Safety Platform in U.S. Operations

Rhea-AI Summary

AES (NYSE: AES) deployed Haven Safety AI across its U.S. utilities and renewables operations to accelerate incident investigations, improve root-cause identification, and identify systemic risks.

Field results show a 50%+ reduction in investigation time, higher-quality root-cause findings, and improved visibility into repeat risks, with the platform built and commercialized in under nine months.

Positive

• Investigation time reduced by over 50%
• Higher-quality and more consistent root-cause identification
• Large-scale production deployment across U.S. utilities and renewables
• Rapid development and commercialization in under nine months

Negative

• Deployment limited to U.S. operations
• Haven operated as an early-stage vendor with pre-seed funding

Key Figures

Investigation speed gain: 50% faster Investigation time reduction: Over 50% reduction Labor time reduction: 50% reduction +1 more

4 metrics

Investigation speed gain 50% faster Haven Safety AI incident investigations vs prior process

Investigation time reduction Over 50% reduction Time to complete safety incident investigations in field use cases

Labor time reduction 50% reduction Root cause analysis safety investigation labor time at AES

Build timeline Less than nine months From co-founding Haven to prototype, pipeline, funding, and deployments

Market Reality Check

Price: $14.23 Vol: Volume 9,895,057 is at 0....

low vol

$14.23 Last Close

Volume Volume 9,895,057 is at 0.56x the 20-day average, indicating subdued trading ahead of this AI announcement. low

Technical Shares at $14.23 are trading above the $13.54 200-day MA, reflecting an established upward bias pre-news.

Peers on Argus

AES gained 0.14% while peers were mixed: AQN +2.11%, BIP +2.69%, CIG -0.43%, ALE...

AES gained 0.14% while peers were mixed: AQN +2.11%, BIP +2.69%, CIG -0.43%, ALE -0.10%, AVA -0.28%, pointing to a stock-specific narrative rather than a sector-wide move.

Previous AI Reports

1 past event · Latest: Jul 30 (Positive)

Same Type Pattern 1 events

Date	Event	Sentiment	Move	Catalyst
Jul 30	AI deployment	Positive	-0.2%	Launch of AI-powered solar installation robot to cut time and costs.

Pattern Detected

Prior AI-related news saw a small negative move despite positive operational implications, suggesting muted or cautious trading responses to AI initiatives.

Recent Company History

Recent disclosures frame AES as an operator steadily embedding AI into its energy platform. A prior Jul 30, 2024 update highlighted an AI-enabled solar installation robot improving speed and cost efficiency, yet the stock slipped 0.23%. Today’s AI safety deployment similarly targets operational gains, extending AES’s pattern of applying AI across construction, renewables, and now safety workflows.

Historical Comparison

-0.2% avg move · Past AI news for AES led to an average -0.23% move. Today’s modest 0.14% uptick on another AI operat...

AI

-0.2%

Average Historical Move AI

Past AI news for AES led to an average -0.23% move. Today’s modest 0.14% uptick on another AI operations update is slightly firmer than that history but still subdued.

AES has progressed from AI-enabled solar installation robotics to AI-driven safety investigations, signaling broader integration of AI across its operations.

Market Pulse Summary

This announcement expands AES’s AI strategy into safety, with Haven Safety AI delivering reported 50...

Analysis

This announcement expands AES’s AI strategy into safety, with Haven Safety AI delivering reported 50%+ reductions in investigation time and labor while improving systemic risk detection. It builds on earlier AI deployments in solar installation, suggesting a broader digital operations theme. Investors may track how these efficiencies influence incident rates, operating costs, and project execution, especially alongside the company’s sizable renewables pipeline and ongoing merger process.

Key Terms

ai-native platform, root cause analysis

2 terms

ai-native platform technical

"one of the energy sector's first large-scale implementations of an AI-native platform"

An ai-native platform is a software system built from the ground up around artificial intelligence models and data workflows rather than adding AI as an afterthought; it is designed to collect and organize large datasets, train and update models, and deliver automated decisions or predictions at scale. For investors, ai-native platforms can signal a company with potentially faster product innovation, lower operating costs, and stronger differentiation—like a factory designed for electric cars instead of one retrofitted—though success depends on data quality, execution and regulatory factors.

root cause analysis technical

"50% reduction in root cause analysis safety investigation labor time"

Root cause analysis is a systematic way to find the underlying reason a problem happened, not just its visible symptoms, so that effective fixes can prevent it from recurring. For investors, it matters because clear identification and correction of root causes reduces the chance of repeated losses, regulatory penalties, or reputational damage—think of it as finding the cracked pipe behind a flood instead of only mopping up the water.

AI-generated analysis. Not financial advice.

Haven Safety AI delivers 50% faster investigations and identifies systemic risks to protect frontline workers

ARLINGTON, Va., March 12, 2026 /PRNewswire/ -- The AES Corporation (NYSE: AES) today announced one of the energy sector's first large-scale implementations of an AI-native platform that investigates incidents faster, uncovers systemic risk and prevents serious injuries before they occur. By deploying Haven Safety AI, AES is moving beyond traditional manual reporting to a proactive, AI-native approach designed to protect its workforce across its U.S. utilities and renewables facilities. Field utilization cases show over 50% reduction in time to complete safety incident investigations, higher-quality root cause identification and improved visibility into repeat and systemic risks across sites.

Solving the Complexity of Modern Energy Safety
While the power sector has made decades of progress in compliance, many organizations still struggle with manual, time-intensive investigations where systemic risks remain hidden. In the high-stakes environments of utility and renewable operations, the ability to identify a "hidden" risk, before it leads to an incident, is a critical safety imperative.

"Instead of spending time compiling reports behind a desk, our teams can now focus on understanding risk on site. We have seen a 50% reduction in root cause analysis safety investigation labor time with the adoption of Haven Safety AI," said Chantz Horman, Director of US Operations and Construction Health & Safety at AES. "With its intuitive interface, Haven has quickly become a force multiplier. It's helping us capture better information from the field, structure investigations more consistently, and learn faster."

Driving Innovation Across Industry
Haven Safety AI was launched with the strategic backing of AI Fund and AES, representing a commitment by AES to foster innovation that benefits all industries. By leveraging AES' operations and safety expertise and AI Fund's experience with AI rapid prototyping, Haven moved at an unprecedented pace. In less than nine months, the company was co-founded, developed a prototype, built a sales pipeline, received pre-seed funding, and had its first commercial deployments. By moving Haven into full-scale production, AES is demonstrating how AI can be embedded directly into daily workflows to identify patterns that previously required weeks of manual analysis.

Measurable Results in the Field
Since the rollout, AES has seen significant improvements in operational safety investigation and mitigation:

• Speed: Over 50% reduction in time to complete investigations.
• Precision: Higher-quality and consistency root cause identification and improved documentation efficiency.
• Proactive Prevention: Improved visibility into repeat and systemic risks across multiple sites.

"For years, safety leaders have known the insights are in the data, but the effort required to extract them has been overwhelming," said Joseph Hanna, Co-Founder and CEO of Haven. "AES is demonstrating what happens when AI is embedded directly into the investigation workflow. Teams move faster, uncover systemic risk earlier, and prevent repeat incidents. We are proud to partner with AES as they set a new standard for safety performance across the energy sector."

The AES deployment represents one of the first large-scale, production implementations of AI-driven incident intelligence across both utility and renewable energy operations. Haven is now working with enterprise customers across energy, construction, manufacturing, and logistics to bring the same capabilities to their safety teams.

About AES

The AES Corporation (NYSE: AES) is a Fortune 500 global energy company accelerating the future of energy. Together with our many stakeholders, we're improving lives by delivering the greener, smarter energy solutions the world needs. Our diverse workforce is committed to continuous innovation and operational excellence, while partnering with our customers on their strategic energy transitions and continuing to meet their energy needs today. For more information, visit www.aes.com.

About Haven Safety AI

Haven Safety AI, a product of Haven Safety Corporation, provides an AI-native platform for incident investigations, root cause analysis, and proactive risk reduction. By combining artificial intelligence with a structured industry knowledge graph, Haven helps organizations capture frontline insights, analyze systemic causes, and continuously improve safety performance. For more information, visit www.havensafety.com.

AES Safe Harbor Disclosure

This news release contains forward-looking statements within the meaning of the Securities Act of 1933 and of the Securities Exchange Act of 1934. Such forward-looking statements include, but are not limited to, those related to future earnings, growth and financial and operating performance. Forward-looking statements are not intended to be a guarantee of future results, but instead constitute AES' current expectations based on reasonable assumptions. Forecasted financial information is based on certain material assumptions. These assumptions include, but are not limited to, our expectations regarding accurate projections of future interest rates, commodity price and foreign currency pricing, continued normal levels of operating performance and electricity volume at our distribution companies and operational performance at our generation businesses consistent with historical levels, as well as the execution of PPAs, conversion of our backlog and growth investments at normalized investment levels, and rates of return consistent with prior experience.

Actual results could differ materially from those projected in our forward-looking statements due to risks, uncertainties and other factors. Important factors that could affect actual results are discussed in AES' filings with the Securities and Exchange Commission (the "SEC"), including, but not limited to, the risks discussed under Item 1A: "Risk Factors" and Item 7: "Management's Discussion & Analysis" in AES' 2025 Annual Report on Form 10-K and in subsequent reports filed with the SEC. Readers are encouraged to read AES' filings to learn more about the risk factors associated with AES' business. AES undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise, except where required by law.

Any Stockholder who desires a copy of the Company's 2025 Annual Report on Form 10-K filed March 2, 2026 with the SEC may obtain a copy (excluding the exhibits thereto) without charge by addressing a request to the Office of the Corporate Secretary, The AES Corporation, 4300 Wilson Boulevard, Arlington, Virginia 22203. Exhibits also may be requested, but a charge equal to the reproduction cost thereof will be made. A copy of the Annual Report on Form 10-K may be obtained by visiting the Company's website at www.aes.com.

AES Website Disclosure

AES uses its website, including its quarterly updates, as channels of distribution of Company information. The information AES posts through these channels may be deemed material. Accordingly, investors should monitor our website, in addition to following AES' press releases, quarterly SEC filings and public conference calls and webcasts. In addition, you may automatically receive e-mail alerts and other information about AES when you enroll your e-mail address by visiting the "Subscribe to Alerts" page of AES' Investors website. The contents of AES' website, including its quarterly updates, are not, however, incorporated by reference into this release.

Investor Relations: Susan Harcourt, 703-682-1204, susan.harcourt@aes.com
Media Contact: Katie Lau, 571-286-9362, katie.lau@aes.com

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SOURCE The AES Corporation

FAQ

How much faster are AES (AES) safety investigations with Haven Safety AI?

Investigations are completing over 50% faster versus manual methods, reducing time-to-investigate substantially. According to AES, field utilization cases reported a greater than 50% reduction in investigation time and faster root-cause analysis.

What operational benefits did AES (AES) report after deploying Haven Safety AI on March 12, 2026?

AES reported faster investigations, more consistent root-cause findings, and better systemic-risk visibility. According to AES, the deployment improved documentation efficiency and uncovered repeat risks across multiple sites.

Was the Haven Safety AI rollout at AES (AES) a full production deployment or a pilot?

AES implemented Haven Safety AI as a large-scale production deployment across U.S. utilities and renewables. According to AES, the implementation moved Haven into full-scale production after initial commercial deployments.

How quickly was Haven Safety AI developed before AES (AES) deployed it?

The platform moved from founding to commercial deployments in under nine months. According to AES, Haven was co-founded, prototyped, funded, and had first commercial deployments within nine months.

Does the AES (AES) announcement quantify financial savings or ROI from the Haven Safety AI deployment?

The announcement does not provide dollar-value savings or formal ROI figures for the deployment. According to AES, measurable results cited focus on time, precision, and visibility improvements rather than quantified financial metrics.

Which AES (AES) operations are covered by the Haven Safety AI deployment?

The deployment covers AES's U.S. utilities and renewables facilities specifically. According to AES, the platform is embedded into daily workflows across its U.S. operations to detect systemic risks and prevent repeat incidents.