22. September 2025 By Annette Kauppinen and Ville Vuorio
From Assistant to Collaborator - How AI Is Changing the Craft of Coding Part 3
Blog 3 of 6 — Securing the AI Teammate: Privacy, Trust, and Compliance in the Age of Code Agents
As AI coding tools like Roo Code and Cline become everyday teammates for developers, a new question rises to the surface—one that goes far beyond productivity: Can you trust your AI agent?
For Ville Vuorio, Technical Architect for the Nordics at adesso Finland, the answer is clear—but conditional.
“AI can absolutely speed things up. But you need to know what it sees, what it sends, and what it stores. Trust without control is dangerous,” he says.
That sentiment is increasingly shared across engineering, security, and legal teams. As organizations embrace AI coding agents, they’re realizing these tools aren’t just helpful coders—they’re also potential gateways to sensitive data, IP, and customer information. Without proper safeguards, a well-intended automation can quickly become a liability.
Client-side architecture isn’t a luxury—it’s a requirement
One of the reasons Roo Code and Cline stand out in the crowded AI tooling landscape is their architectural design. Both emphasize client-side execution, ensuring that code, credentials, and proprietary data remain within the company’s infrastructure.
Cline also meets SOC 2 Type I and GDPR standards, while Roo Code supports local model execution and custom approval flows, giving teams fine-grained control over how AI operates.
“Local control is everything,” Ville says. “If a tool sends your code to an external cloud without you knowing, you’ve already lost the security battle.”
This is especially crucial for industries like finance, healthcare, or defense—where regulatory compliance isn’t optional and auditability is key.
Privacy policies aren’t enough—real governance is needed
Security isn’t just about technical features. It’s about people, policies, and process discipline. As Ville points out, “Organizations need to apply the same governance principles to AI tools as they do to any critical software component. That includes defining clear roles, usage boundaries, access controls, and review workflows.”
Organizations must establish well-defined AI usage policies:
- What kinds of data can be processed?
- Who reviews the outputs?
- Are results stored, logged, or retained—and by whom?
Cline includes audit logs, permission models, and zero-retention policies that help organizations apply structured governance to AI usage.
Avoiding shadow AI: the governance blind spot
When AI adoption spreads informally—through personal tools, browser plugins, or GitHub Copilots set up under personal accounts—it opens the door to shadow AI: unmonitored, unreviewed, and potentially non-compliant usage of powerful tools.
This is one of the biggest risks Ville sees in large organizations. “If you don’t provide approved tools and clear policies, people will find their own workarounds,” he warns. “That’s not innovation. That’s a security gap.”
The solution? AI governance frameworks—structured approaches that align AI tool usage with business goals, regulatory requirements, and team readiness. These frameworks should define ownership (who manages AI adoption), evaluation criteria (how tools are approved), and oversight practices (how usage is tracked and reviewed).
From compliance to confidence
Ultimately, securing the AI teammate isn’t about limiting what these tools can do—it’s about enabling them to operate safely, consistently, and responsibly. When done right, security doesn’t slow things down—it builds confidence.
Ville puts it simply:
“AI should make you faster. But it should also make you feel safer. If you have to wonder what it’s doing behind the scenes, something’s wrong.”
As companies lean into AI-enhanced development, those who take security and governance seriously will have a clear advantage—not just in protecting their assets, but in unlocking AI’s full potential as a trusted collaborator.
Next in the series:
In Blog 4, we’ll dive into the human side of adoption—how to prepare your team for AI integration, overcome resistance, and build a culture of confident, capable collaboration between humans and machines.
Read the previous parts:
Part 1: How AI Coding Tools Are Transforming the Daily Work of Developers
Part 2: From Workflow Support to Organizational Shift: How AI Is Redefining Software Teams
