AI agent orchestration is transforming how enterprises automate complex, document-centric workflows. Learn how to build secure, multi-step agentic workflows. In this AWS and Box webinar, industry experts discuss the shift from basic automation to advanced AI agent orchestration. As organizations deploy AI agents to read, write, and act on secure content, the focus is shifting toward building a secure data foundation. Discover how to redesign your business processes for an AI-first world. We break down the blueprint for document-centric workflows, such as employee onboarding, invoice processing, and contract reviews, and explain how to combine AI models with human-in-the-loop oversight for maximum productivity and reliability. You will also learn about "governance-native AI" and why security, identity management, and auditability are critical to building trust. The speakers explain why you should leverage open protocols like Model Context Protocol (MCP) to connect agents to your tools, and why using Box as your secure content layer allows your teams to focus on business logic rather than rebuilding complex RAG infrastructure and vector databases from scratch. 00:00 — Introduction and Speaker Welcomes 01:29 — Defining AI Agents in the Enterprise 03:07 — Orchestration vs. Automation in Business Workflows 05:07 — Real-World Examples: Onboarding and Expense Policies 08:45 — Security, Compliance, and Auditability in Agent Workflows 13:26 — The Role of Content and Context in AI Usefulness 18:31 — Build vs. Buy: Partnering for Agentic Capabilities 24:47 — What We Got Wrong About AI Agents a Year Ago 28:28 — Why Culture is the Number One Driver of AI Success FAQs: Q: What is the difference between simple automation and AI agent orchestration? A: Simple automation typically follows rigid, pre-defined rules. AI agent orchestration involves intelligent agents that have an objective, access to a knowledge base, and the ability to plan, act, and drive multi-step tasks across workflows without constant human intervention. Q: What is governance-native AI? A: Governance-native AI is the principle that an AI agent automatically inherits and respects the existing security, permissions, and compliance guardrails of the enterprise content layer. If a user does not have permission to access a document, the AI agent cannot access it either. Q: Why is a data foundation critical for AI agents? A: AI agents rely entirely on the quality and accessibility of your content. If your data foundation is unorganized or ungoverned, agents cannot extract accurate context. A strong data foundation ensures content is structured, secure, and connected across your workflows. Q: Should enterprises build their own AI infrastructure from scratch? A: No. Building custom RAG models, vector databases, and OCR layers is incredibly difficult and costly. Enterprises should use Box as their secure, governed content layer and focus their engineering resources on building business logic, prompts, and integrations on top. Q: What is the most important factor in a successful AI agent deployment? A: While technology is important, organizational culture is the primary driver of success. Organizations that understand employee needs, foster curiosity, and build centers of excellence deploy AI agents faster and more effectively.

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