Graph technology plays a crucial role in enhancing the capabilities of artificial intelligence (AI) by providing context to AI applications. Narrow AI, which focuses on performing one task well, is becoming broader in its applicability as more general AI solutions are developed. Context is essential for making decisions, and AI needs to mimic human intelligence by incorporating context into its decision-making processes. Graph technology connects data and defines relationships, offering an effective means to empower the development of sophisticated AI applications. There are four main areas where graphs provide context: knowledge graphs, graph accelerated machine learning, connected feature extraction, and AI explainability. These areas enhance AI with related information, enabling it to make decisions closer to human intelligence. By providing contextual power, graph technology can give AI solutions a significant boost in their capabilities, making them more powerful over time.