Grab launches AI tools developed with OpenAI, Anthropic

Grab has introduced two new AI-driven tools for its merchant and driver partners in Southeast Asia.

One of them is AI Merchant Assistant, which is integrated within the GrabMerchant app to provide small businesses with operational insights.

Grab’s AI Merchant Assistant was developed in collaboration with OpenAI and Anthropic. This tool can answer queries related to business and offer sales recommendations.

With 44 million monthly transacting users across 8 countries and over 800 cities in Southeast Asia, Grab offers OpenAI and Anthropic access to a large regional user base and real-life use cases to train, test, and refine AI models.

Another tool is the AI Driver Companion, developed in collaboration with OpenAI.

The ride guidance tool predicts high-demand areas using real-time and historical data.

The voice reporting tool enables drivers to report road conditions verbally. This feature improves the accuracy of GrabMaps.

🔗 Source: Grab

🧠 Food for thought

1️⃣ Grab’s super app evolution powers its AI strategy

Grab’s new AI assistants represent a strategic evolution within its broader “super app” journey that began years ago, not just a standalone technological upgrade.

Since 2019, Grab has been methodically expanding beyond ride-hailing to create a comprehensive ecosystem that now includes hotel bookings, video streaming, and financial services 1, positioning itself to better integrate AI across multiple service domains.

This expansion has already yielded significant economic impact, with Grab contributing approximately $5.8 billion to Southeast Asia’s economy and supporting over 9 million micro-entrepreneurs 2.

By building AI solutions specifically for merchants and drivers, Grab leverages its unique position at the intersection of multiple services, creating value by applying AI to real-world operational challenges rather than developing theoretical capabilities.

The company’s established relationships with millions of merchants and drivers create an immediate testing ground for AI implementation, allowing for rapid feedback and iteration.