The AI landscape shifted again this month with Anthropic's launch of Claude Cowork, a tool that brings the capabilities of their popular Claude Code agent to non-technical users. The announcement generated significant attention—and raised important questions about how organizations should approach these increasingly powerful AI tools.

What Are Claude Code and Cowork?

Claude Code, released in early 2025, is an AI coding agent that goes beyond traditional chatbot interactions. Rather than simply answering questions, it can take autonomous actions: editing files, running commands, navigating codebases, and executing multi-step tasks on behalf of users.

Claude Cowork, announced in January 2026, extends these capabilities beyond developers. Built into the Claude Desktop app, Cowork allows users to designate folders where Claude can read and modify files, effectively creating a file-managing AI assistant for general business use.

The key distinction from earlier AI tools: these are agents that take action, not just assistants that provide information.

Legitimate Use Cases

Organizations are finding genuine productivity benefits from AI coding agents:

Development Teams

Software teams report using Claude Code to accelerate routine tasks—writing tests, fixing lint issues, resolving merge conflicts, and navigating unfamiliar codebases. For new team members, it can help explain complex dependencies and data pipelines.

Non-Technical Applications

With Cowork, the applications extend beyond coding. Reports indicate use cases ranging from document organization to data analysis to content generation—tasks that previously required either technical skills or significant manual effort.

Automation of Repetitive Work

Both tools can handle multi-step workflows that would otherwise consume significant human time, from processing files to generating reports to managing routine administrative tasks.

Security Considerations Organizations Should Understand

The power that makes these tools useful also creates security considerations that organizations should be aware of:

Prompt Injection Vulnerabilities

Security researchers have documented vulnerabilities in AI agents where malicious instructions can be hidden in files or documents. When the AI processes these files, it may execute the hidden instructions—potentially accessing or transmitting sensitive data.

This type of attack—called indirect prompt injection—is particularly concerning because the user never intentionally provides malicious input. The attack comes through content the AI encounters during normal operation.

Data Exposure Risks

AI agents that can read files and execute commands operate with significant access. Considerations include:

  • Files containing credentials, API keys, or sensitive configuration
  • Documents with customer data, financial information, or proprietary content
  • Access to connected systems through integrations and plugins
  • Data transmitted to AI provider servers for processing

We discussed related data handling considerations in our article on what business apps reveal about your data.

Shadow AI Concerns

When powerful AI tools are easily accessible, employees may adopt them without organizational oversight. This "shadow AI" usage creates challenges:

  • Sensitive information may be processed through unapproved channels
  • Security teams lack visibility into what data is being shared
  • Compliance requirements may be unknowingly violated
  • Organizational policies may not cover these new use cases

Permissions and Access

AI agents typically operate with the same permissions as the user who runs them. This means the agent can access anything the user can access—which may be more than intended for any single automated task.

The Broader AI Usage Policy Question

Claude Code and Cowork are part of a larger trend. AI tools are proliferating across every business function, and organizations face a fundamental question: how do we govern AI use?

The Current State

Research suggests that a significant majority of organizations using AI tools lack formal policies governing their use. The gap between AI adoption and AI governance continues to widen as new tools emerge faster than policies can be developed.

This creates risk. When employees use AI tools without guidance, they make individual decisions about what data to share, what tasks to automate, and what outputs to trust—decisions that may have organizational implications.

What AI Usage Policies Address

Organizations developing AI governance frameworks typically consider:

  • Approved tools: Which AI systems are sanctioned for business use?
  • Data boundaries: What information can and cannot be processed through AI tools?
  • Human oversight: What decisions require human review of AI outputs?
  • Accountability: Who is responsible when AI-assisted work has errors or causes harm?
  • Transparency: When must AI involvement be disclosed?
  • Compliance: How do AI tools interact with regulatory requirements?

Regulatory Developments

The regulatory landscape around AI is evolving rapidly. Various jurisdictions have introduced requirements around AI transparency, bias auditing, and accountability—particularly for AI used in employment decisions, customer interactions, and automated decision-making.

Organizations operating across multiple jurisdictions face an increasingly complex compliance environment that formal policies can help navigate.

A Moment for Reflection

The emergence of AI agents like Claude Code and Cowork represents a genuine shift in how work can be done. These tools offer real benefits—and real considerations that organizations should think through.

The organizations that navigate this transition well will likely be those that:

  • Understand what these tools actually do and how they work
  • Consider the security implications before broad adoption
  • Develop policies that enable appropriate use while managing risk
  • Maintain human oversight of AI-assisted work
  • Stay informed as both tools and threats evolve

This isn't about avoiding AI—it's about approaching it thoughtfully.

Questions for Your Organization

Rather than prescribing solutions, here are questions that can help clarify your situation:

  • Do you know which AI tools employees are currently using for work?
  • What happens when sensitive data is processed through consumer AI services?
  • Who in your organization is responsible for AI governance decisions?
  • If an AI agent made a consequential error, how would you know—and who would be accountable?
  • Does your existing acceptable use policy address AI tools, or was it written before this category existed?

Every organization's situation is different. What matters is having the conversation and making intentional decisions rather than letting adoption happen by default.

This article is intended for informational purposes only and does not constitute professional security, legal, or compliance advice. Organizations should consult with qualified professionals to assess their specific situation and develop appropriate policies.