Box CEO on AI agents: They will change the way we work

Summary

Aaron Levy, co-founder and CEO of Box, discusses the evolution of AI agents, explaining their role beyond simple chatbots like ChatGPT to more advanced tools capable of completing long-term tasks. Levy highlights Box’s AI agents for enterprise customers, focusing on deep research, data extraction, and task execution. He emphasizes that these AI agents can automate processes previously too costly or time-consuming, helping businesses improve productivity. Box differentiates itself with its secure, enterprise-focused platform that integrates with various AI models, offering solutions without the need to move sensitive data around.

Takeaways

• 😀 AI agents are different from traditional chatbots or assistants; they are designed to handle long-running tasks and provide complete solutions or reports.
• 😀 Gemini is an example of an AI system that can perform deep research, such as writing a research report after analyzing a set of data or documents.
• 😀 Enterprise customers can leverage AI agents to perform tasks like deep research, general data search, and data extraction across various business assets.
• 😀 AI agents can read and analyze large collections of documents, such as contracts and financial materials, to generate reports or conclusions on specific projects.
• 😀 AI agents enable businesses, like banks, to automate processes like due diligence by analyzing thousands of documents and creating reports.
• 😀 The use of AI agents in enterprises helps tackle tasks that were previously too expensive or time-consuming to complete manually.
• 😀 Aaron Levy argues that AI agents will not replace jobs but rather increase productivity by automating tasks that were never previously addressed.
• 😀 The enterprise platform Box differentiates itself by enabling AI to operate directly on business data without the need to move data to multiple platforms.
• 😀 Box integrates with multiple AI models, including those from Gemini, OpenAI, Meta, XAI, and others, offering flexibility and broad AI support for enterprises.
• 😀 Box's AI agents work with various IT systems, including IBM Watson, Salesforce, and Google Agent Space, to ensure seamless integration into enterprise workflows.

Q & A

What is an AI agent, and how does it differ from a chatbot?

An AI agent is a more advanced form of AI than a traditional chatbot. While a chatbot is used for simple, back-and-forth conversations, an AI agent is designed to handle long-running tasks, analyze data, and provide complete solutions or execute projects. AI agents are capable of performing complex tasks such as deep research and generating detailed reports, which are beyond the scope of basic chatbots.

What is Gemini, and how does it fit into AI research tasks?

Gemini is a tool that exemplifies the use of AI agents in deep research tasks. It allows users to request specific tasks, such as gathering the full history of a topic. The AI then performs the task, generating a comprehensive report or research output, which may take a few minutes. This is particularly useful for enterprise customers who require large-scale, in-depth research on various topics.

How can AI agents be applied to enterprise tasks?

AI agents can be used across various enterprise tasks such as searching through large datasets, extracting relevant information, and generating reports. For example, an AI agent can go through financial documents, contracts, or research materials and come back with conclusions or analyses tailored to specific needs, such as due diligence in acquisitions.

What are some examples of how AI agents can assist in specific industries?

In industries such as banking, AI agents can be used for due diligence tasks. For example, an AI agent could be tasked with reviewing thousands of documents related to a company being acquired and generate a detailed report on the findings. This enables organizations to execute tasks that would otherwise be time-consuming or too expensive to handle manually.

How do AI agents affect the job market, particularly in roles like investment banking?

While there is speculation that AI agents might replace jobs, especially in fields like investment banking, many experts argue that they will primarily be used for tasks that were previously not feasible due to cost or scale. AI agents will likely augment human work rather than replace it, enabling more efficient execution of tasks that were previously neglected.

How does Box differentiate its AI offerings from other companies in the space?

Box differentiates itself by focusing on being an enterprise platform that integrates AI directly into its customers' workflows. With over 120,000 customers, including 64% of the Fortune 500, Box provides a secure environment for data storage and management, allowing AI agents to access and analyze content without moving data across multiple platforms.

What is the role of AI agents in enterprise data management?

AI agents play a crucial role in enterprise data management by reducing the need to move data across multiple platforms. Instead of outsourcing AI tasks to external systems, Box's platform allows AI agents to be deployed directly on the data, maintaining security and efficiency while executing complex tasks like data analysis and report generation.

How does Box integrate with different AI models and ecosystems?

Box integrates with a wide range of AI models and ecosystems, including Gemini, OpenAI, Meta’s models, XAI, Grok 3, Claude, and Anthropic. Additionally, Box works with enterprise IT systems like IBM’s Watson X, Salesforce’s Agent Force, and Google’s Agent Space, ensuring seamless integration across various AI tools and customer infrastructures.

Why is it important for Box to integrate with the broader AI ecosystem?

Integrating with the broader AI ecosystem is important because it allows Box to offer flexibility and choice to its customers. Enterprises can use their preferred AI models while benefiting from Box’s secure data management platform. This integration ensures that businesses can leverage AI in a way that aligns with their existing technology stack.

How do AI agents improve productivity in organizations?

AI agents improve productivity by automating tasks that were previously time-consuming, expensive, or impractical. With AI performing tasks such as research, data extraction, and analysis, employees can focus on higher-level strategic work. This leads to more efficient operations and the ability to tackle previously ignored or overlooked tasks, ultimately boosting organizational productivity.