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Why knowledge graphs are crucial for agentic AI

Xander Smart
Xander Smart • 5 min read
Why knowledge graphs are crucial for agentic AI
Smarter AI agents need smarter data. Knowledge graphs can help by providing a shared data foundation that enables agents to reason over connected, context-rich information. Photo: Unsplash
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Singapore’s ambition to become a global hub for artificial intelligence (AI) is rapidly taking shape, fueled by over $1 billion in government investments. But beyond the headlines lies a crucial shift unfolding in businesses across the city-state: the rise of autonomous AI agents, or agentic AI.

Unlike traditional AI systems, these self-directed agents can execute complex tasks without human intervention. Leveraging data captured in multiple formats and iterative learning, they independently make informed decisions. Industry analysts project that by 2028, 33% of enterprise software applications will incorporate agentic AI, up dramatically from under 1% in 2024.

In Singapore’s retail sector, a recent report highlighted that 69% of businesses now view AI agents as essential for maintaining a competitive advantage, and 85% of Singaporean retailers plan to boost AI investments in the next year alone, demonstrating a strong sense of urgency and growing confidence in the promise of AI.

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