The AI Agent Enterprise Revolution: Building the Missing Context Layer
When the CEO of Box tweets that "AI Agents are the big topic for enterprises right now," we should all take notice. The momentum is building, but so is the awareness of the critical challenges ahead.
What struck us most about Aaron Levie's insights wasn't just the excitement—it was the stark reality of what's missing: context.
@Levie on Enterprise AI Agents
The Enterprise Context Problem
Enterprises don't have their data in a single environment. Their CRM lives in Salesforce, documents in Box, HR data in Workday, and IT workflows in ServiceNow. This fragmentation creates an immediate challenge for AI Agents that need to work across systems.
As Levie points out: "Plenty of Agentic use-cases will span these systems. As an industry we will need to design more interaction patterns for how AI Agents talk to each other and exchange data in the future."
But here's what's not being talked about enough: AI Agents need structured context to function effectively across digital environments.
Why Context Matters More Than You Think
When an AI Agent tries to help an employee process a sales contract, it needs to:
Find the contract in Box
Check customer details in Salesforce
Confirm pricing rules in an internal system
Submit for approval in ServiceNow
Without proper context anchors in each system, the Agent is essentially blind—trying to navigate complex digital interfaces without a map.
The Missing Layer: AI-Ready Structure
A critical insight from Levie's thread addresses this directly: "Data needs to be in an AI-ready environment: decades of technology being adopted in an enterprise means decades of systems that have important data but are not in environments that AI Agents can easily talk to."
But what does "AI-ready" actually mean?
It means digital environments that provide:
Structural context for AI understanding
Reliable anchors for consistent interaction
Clear pathways between systems
Permission frameworks that translate to AI capabilities
The New Essential: Context Enhancement
For AI Agents to deliver on their promise in enterprise environments, we need more than just better models—we need better context.
This is precisely where we're focused: building the critical context layer that enables AI Agents to understand complex digital interfaces, maintain reliable interaction points, and navigate securely between systems.
Our technology transforms the structural chaos of enterprise environments into machine-readable maps that AI Agents can comprehend and navigate with confidence.
Moving Forward: What This Means For You
If you're exploring AI Agents for your enterprise, ask yourself:
How will your Agents understand your current digital environments?
What will provide consistent anchoring points as interfaces evolve?
How will you maintain context across your ecosystem of tools?
The answers to these questions will define your success with AI Agents far more than the underlying model you choose.
The future belongs to enterprises that build not just with AI, but with AI-ready context at the foundation.
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