According to Andrew Ng (@AndrewYNg), AI agents are rapidly improving their ability to analyze diverse business data sources, leading to substantial new value by connecting information that was previously siloed. Ng emphasizes that the increasing capabilities of AI, such as spotting correlations between email clicks and online purchases across platforms, make it more critical than ever for businesses to control their own data. He points out that many SaaS vendors intentionally create data silos by limiting data access or charging exorbitant fees for API access, which impedes the deployment of effective AI-driven workflows. Ng advises businesses to prioritize software solutions that ensure data ownership and accessibility, enabling flexible integration with both human and AI processes. He highlights the growing importance of organizing both structured and unstructured data, referencing tools like LandingAI’s Agentic Document Extraction for document processing and Obsidian for personal note management. This trend presents significant opportunities for AI-driven business optimization and underlines the competitive advantage of data interoperability (source: Andrew Ng, deeplearning.ai The Batch).

According to Jeff Dean, Google is rolling out a comprehensive set of new features that allow organizations to leverage contextual data and build agent-based systems on top of Gemini and Google Cloud (source: Jeff Dean on Twitter, Google Cloud Blog). Businesses can now use Gemini-powered agents to extract actionable insights from company-specific information, such as identifying pending action items from past meeting notes. This release enables practical applications of generative AI for workflow automation, data analysis, and decision support, providing a significant business opportunity for enterprises looking to streamline processes and enhance productivity with AI (source: Google Cloud Blog).