The shift from individual AI projects to centralized platforms is necessary for organizations to scale effectively and manage AI responsibly.

The emergence of generative AI has led to more collaborative and expansive applications, requiring new approaches to testing and evaluation.

The rise of generative AI presents opportunities to create deep, complex applications that can provide long-term value, unlike simpler applications that may not be defensible in the long run.

This decade is characterized by the addition of generative AI tools, which build on the foundations of supervised learning.

The company leverages both traditional AI and generative AI to provide a seamless customer experience across various platforms.

The rise of AI tools is addressing the software development deficit, allowing for more efficient code generation and management.

Generative AI is just another step in the journey of using machine learning technologies in finance.

Centralized AI platforms help manage complexity and ensure responsible use of AI, addressing issues like shadow AI and security vulnerabilities.

Generative AI is an exciting new area that is currently smaller in scale but is expected to grow significantly in the next few years due to increased developer interest and venture capital investments.