AI agents transform unstructured data into enterprise insights
AI agents enable enterprises to unlock the value of unstructured data, automate workflows, and deliver secure, intelligent business insights.
Unstructured data — including PDFs, videos, images, and audio files — now dominates organizational content. Despite its prevalence, extracting meaningful insights from this data has historically been a challenge. The rise of AI agents, however, is changing the game by turning static files into dynamic sources of decision-making power.
The Role of AI in Managing Unstructured Data
Ben Kus, Chief Technology Officer of Box Inc., emphasizes that AI agents are evolving from basic bots into sophisticated collaborators. These agents can read, classify, and reason over content in ways that mimic human capabilities. "Our job is to secure it, to collaborate with it, and now to provide AI on top of your unstructured data," Kus said during an interview at Okta’s Oktane event.
Key Developments:
- AI-Powered Classification: Automating the tagging of sensitive information and identifying high-value content across millions of documents.
- Retrieval-Augmented Generation (RAG): Enabling AI to retrieve precise answers rather than just pointing to documents, significantly reducing manual search time.
Enterprise Applications
Businesses are leveraging AI agents for:
- Sales Support: Quickly answering customer questions by analyzing vast repositories of data.
- Compliance & Security: Automating classification to meet regulatory requirements.
- HR & Customer Service: Streamlining access to historical data for faster decision-making.
Video Interview
For deeper insights, watch the full interview with Ben Kus here.
Governance and Security
Kus highlights the importance of building AI solutions with governance and security at the forefront. As enterprises adopt these technologies, ensuring data integrity and compliance remains critical.
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About the Author

Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.