Box (BOX) Morgan Stanley Technology, Media & Telecom Conference 2026 summary

Business momentum and technology strategy

• Enterprises are increasingly seeking to leverage their internal data through intelligent workflow automation and AI, driving a strong cycle of upgrades to advanced content management solutions.

• The platform strategy focuses on connecting enterprise content to a growing number of AI agents, enabling secure collaboration and governance across both human and machine users.

• Files are positioned as the core unit of work for AI agents, requiring robust storage, security, and compliance capabilities.

• The company is building a 'file system for AI,' supporting both people and agents as primary users on the platform.

• Increasing developer and enterprise interest in integrating agents with enterprise content is fueling platform adoption.

Financial performance and growth drivers

• Q4 results exceeded expectations, with Enterprise Advanced now representing 10% of total revenue and delivering a 30%-40% per-user pricing uplift.

• Achieved three consecutive quarters of revenue acceleration, with guidance for a fourth and expectations of higher constant currency revenue growth next year.

• Enterprise Advanced customers are signing multi-year commitments, increasing contract visibility and stickiness.

• Monetization includes per-seat pricing uplift, seat expansion, and additional consumption-based charges for high-volume AI use cases.

• The business model is evolving toward a hybrid of seat-based and consumption-based pricing for agents, leveraging existing API monetization structures.

Product innovation and AI integration

• The platform enables both native and third-party AI agents to process, analyze, and manage large volumes of unstructured enterprise data.

• Early use cases include document processing, data extraction, and workflow automation, with agents able to interact with Box via CLI, API, and integrations.

• Security and governance features, such as Box Governance and Shield, are being extended to manage the risks associated with a proliferation of AI agents.

• The platform is designed to isolate agent access, enforce data policies, and provide auditability, addressing the unique risks of machine users.

• Ongoing product enhancements are making it easier for developers and customers to deploy and manage AI agents at scale.