To achieve the vision of agentic AI, technologies must advance beyond current generative AI capabilities. Key requirements include explainability, robust context understanding, efficient learning mechanisms, and safety. The article suggests focusing on complementary technologies like synthetic data generation to overcome biases and enhance AI robustness. The author, an AI leader at YData, emphasizes the need for a nuanced approach to AI development, leveraging generative AI for creativity while exploring other technologies to address broader challenges in AI autonomy.
Key takeaways:
- Generative AI is transformative but not inherently designed for agentic AI's demands.
- Agentic AI requires true autonomy, robust decision-making, and scalability, which current generative AI lacks.
- Key requirements for agentic AI success include explainability, robust context understanding, efficient learning, and safety.
- Organizations should focus on complementary technologies like synthetic data generation to enhance AI systems.