Scaling Global Content with AI: How OpenSense Labs Built AES's Intelligent Content Layer

AES Corporation is a Fortune 500 global energy company and one of the world's leading clean-energy operators, recognized as the top seller of renewable energy to corporations globally. With operations spanning multiple continents and a network of country-specific digital properties from the Americas to Europe to Southeast Asia, AES's mission centers on improving lives by accelerating a safer, greener energy future.

The company has also built a reputation for operational innovation, including AI-enabled field technology such as its solar-installation robot, Maximo. That track record mattered: AES was already primed to bring AI into how it works, not just what it builds, which made an AI-driven content layer a natural next step for its digital operations.

Content Velocity at Global Scale

• Dozens of local and country-specific sites required constant publishing of news, projects, and sustainability updates
• Editorial teams were often small relative to the volume and geographic spread of content they managed
• Manual production of supporting content alt text, metadata, summaries couldn't keep pace with publishing demand

SEO and Accessibility Consistency

• Image alt text and page metadata varied in quality depending on which editor produced them
• Inconsistent metadata undermined search visibility across an already fragmented, multi-site structure
• Accessibility compliance depended on manual diligence rather than a systemic safeguard

Multilingual Brand Consistency

• Content needed to be translated into Spanish, Vietnamese, German, and other languages for regional audiences
• Literal or inconsistent translation risked diluting AES's brand tone and messaging across markets
• Manual translation cycles slowed down how quickly regional teams could publish timely, localized content

Rather than building isolated point solutions, OpenSense Labs designed a centralized AI intelligence layer and a set of specialized, enterprise-grade AI services that plug directly into AES's existing Drupal environment. Drupal remained the interface editors already knew; OpenSense Labs' AI services became the engine running quietly behind it.

This approach meant AES's teams could adopt sophisticated AI capabilities without retraining on a new system or disrupting an established publishing workflow. Every AI action was designed to feel like a natural extension of the tools editors already used every day, not a separate platform bolted on top.

Strategy

Intelligence Layer Design

OpenSense Labs built each AI service to be context-aware and brand-aligned, rather than generic. Alt text generation accounts for an image's context and each business unit's tone. Metadata suggestions are tuned for search performance without sacrificing brand voice. Translations are designed to preserve tone and cultural nuance rather than converting content word-for-word. This meant the underlying AI services had to be trained to understand AES's editorial standards, not simply process content in the abstract.

Workflow Integration

Every AI capability was embedded directly into AES's Drupal-based editorial workflow through simple, editor-triggered actions. An editor uploads an image and clicks a button to generate alt text. A new page is published, and metadata suggestions appear automatically. A piece of content is drafted in English, and a single click sends it through the translation pipeline. There are no new dashboards, logins, or parallel systems to learn; the AI layer works inside the tools editors already open every day.

OpenSense Labs' AI team built the intelligence layer as a set of backend services, each purpose-built for a specific editorial need and consumed through lightweight Drupal-side modules. The table below summarizes each capability delivered as part of this engagement.

Content editors upload an image and click a single button inside Drupal to fetch an AI-generated alt text suggestion. On the backend, OpenSense Labs' service produces meaningful, context-aware, and tailored descriptions for each business unit's tone, turning what was once an easily skipped manual step into a consistent, one-click part of the publishing process.

When a new page is published in Drupal, the client-side module calls OpenSense Labs' AI service to suggest optimized meta titles and descriptions. The output is designed to improve search rankings and discoverability while staying true to AES's brand voice, removing the guesswork editors previously faced when writing metadata by hand.

Authors draft content in English and trigger translation with a single click inside the existing Drupal workflow. OpenSense Labs' AI pipelines deliver translations into Spanish, Vietnamese, German, and other languages, built to preserve brand tone and cultural nuance so global content stays consistent no matter which market it reaches.

An AI-powered content quality layer reviews grammar and clarity, helping editors polish copy before it goes live while respecting the tone and voice conventions specific to each market and business unit.

For long-form content such as project updates, sustainability reports, and news articles, the AI service generates concise summaries suited to previews, listing pages, and quick-scan consumption, helping visitors find relevant content faster across AES's sprawling site network.

As new content enters the publishing workflow, the AI service automatically generates relevant tags and categories, including new categories where needed. This keeps taxonomy consistent across dozens of sites without requiring every editor to manually classify content the same way.

Because this AI intelligence layer was built to work inside AES's existing Drupal workflow, its impact shows up less as a single headline metric and more as a shift in how AES's global content operation runs day to day:

• Faster publishing cycles, with AI handling supporting content alt text, metadata, summaries, tags that previously required manual effort for every page
• More consistent SEO and accessibility coverage across AES's network of country-specific sites, regardless of which editor produced the content
• Reduced manual translation and tagging burden for regional teams, freeing editorial time for strategy and storytelling rather than production tasks
• Stronger brand-tone consistency across languages and markets, supported by AI services purpose-built to understand AES's voice rather than translate or generate generically

“The goal was to give them an AI layer that understands their brand well enough to handle the repetitive work, so their people can focus on the content only they can create.”