Your AI agent is working.
But who’s watching?
AI agents work independently with data and processes. Learn how to maintain control over behavior, governance, security, and management.
More and more organizations have their first AI agents up and running. They answer questions, process orders, support employees, and perform tasks independently in ERP, CRM, and other business systems. AI is moving from experimentation into production. And that’s precisely when a question arises that remains unanswered in many boardrooms: Who oversees what these agents do once they’re live? That sounds like a technical issue. It’s a business issue.
An Agent Behaves Differently Than Software
Traditional software does what you program it to do. An AI agent is given a goal, access to data, and the freedom to make decisions on its own within set parameters. That’s what makes it valuable. It also creates new risks as data, integrations, and permissions change over time. New data is added. Integrations change. Permissions are updated. Or an agent gains access to information it was never intended to access. That’s precisely where risks arise.
Take an agent that processes orders. What happens if that same agent suddenly retrieves data from your HR system or accesses customer data for which it has no authorization? Technically, everything may be functioning as intended, but something is still not right. In AI projects, a lot of attention is focused on functionality and use cases. That makes sense, because that’s where the value lies. But after going live, there’s often a lack of visibility into what an agent is actually doing.
Security Faces a New Challenge
Firewalls, identity management, endpoint security, and a SOC remain important. They answer questions such as: Does someone have unauthorized access? Is an attack underway? Are we seeing suspicious activity? With AI agents, another question arises: Is this agent still doing what it’s supposed to do? That’s a different type of risk. It’s not just about who has access, but also about accountability for what the agent does and on whose behalf.
What actions did the agent perform?
What data was affected in the process?
Did the agent do anything unusual or wrong?
Managing AI Agents Is Just as Important as Building Them
In the coming years, large organizations will have dozens to hundreds of agents running side by side—for customer service, finance, sales, and operations. This creates a management challenge that is rarely planned for in advance: who monitors performance, costs, token consumption, data access, model updates, governance, and security?
An AI agent isn’t a project you deliver and then forget about. It becomes part of your daily operations. Just as you manage your cloud, applications, and infrastructure, you’ll also need to manage your AI landscape.
For executives, compliance, and security teams, it all comes down to four questions: Which agents are currently deployed, what data are they using, what decisions are they making, and who is responsible?
These questions are relevant everywhere, but carry greater weight when working with sensitive data or customer information, such as in the financial and business services sectors. An agent that deviates from its original purpose can lead to operational disruptions, compliance issues, and reputational damage. New laws and regulations, such as the AI Act and the Cybersecurity Act, also require organizations to demonstrate that they have control over their AI security.
Why Security Monitoring and Process Knowledge Must Go Hand in Hand
Security specialists excel at detecting technical anomalies such as suspicious activity, unusual access requests, and abnormal traffic. What they often lack is the business context: why the agent was built, what processes it supports, and what outcomes it is expected to deliver. HSO provides that business context. To assess whether an agent’s behavior is appropriate, you need to understand the business process.
Why was the agent developed?
What data is the agent supposed to use?
What outcome is expected?
What processes does the agent support?
A traditional SOC service provider observes: something unusual is happening here.
The combination of process and security knowledge reveals: this behavior does not align with the role for which this agent was developed. That discrepancy determines how quickly you can intervene.
That’s Why HSO and Nedscaper Are Pooling Their Expertise
With that in mind, HSO Managed Services and Nedscaper have entered into a partnership focused on Managed AI & Agents. HSO manages the AI solution itself—including models, performance, usage, costs, changes, and operational functioning—drawing on its knowledge of your business processes, data, and Dynamics environment. Nedscaper provides specialized security monitoring and incident response regarding agent behavior.
The real difference is how the two teams work together. With many security issues, reports are routed through the customer from one vendor to another. That takes time—precisely when time is of the essence.
In this model, both parties communicate directly with each other and with you. Communication channels are already established, access rights are in place, and investigations can begin immediately while keeping you informed throughout the process. For organizations using AI in business-critical processes, that speed can significantly reduce operational and compliance risks. Investigation and recovery start sooner, and you have a single point of contact.
In Addition to Your Existing SOC, Not Instead of It
Many large organizations already have a security partner. This approach does not replace that partner. It complements your existing setup where generic monitoring falls short: addressing whether an agent’s behavior still aligns with the business objective for which it was developed. Technically, it integrates with your existing security and IT infrastructure.
Governance Is a Prerequisite, Not the Final Piece of the Puzzle
Working securely with agents starts with clear agreements. What data is an agent allowed to use? What actions is it permitted to perform? Who is the owner? These are questions you need to answer in advance, not after something goes wrong.
That’s why HSO and Nedscaper focus not only on monitoring, but also on governance, architecture, and management processes. This is especially relevant for organizations that are now building their first agents. By incorporating management and security from the start, you avoid having to work around them later on.
The Next Step Toward Enterprise AI
AI agents are becoming an integral part of your business operations. As a result, AI management is shifting from a technical issue to a governance issue. Success depends not only on the quality of the agent, but also on oversight, governance, monitoring, and security throughout its entire lifecycle.
Organizations that establish these capabilities now will be better positioned as AI adoption scales. Not because they use more AI, but because they use AI responsibly. An agent only delivers lasting value if you can trust it to do what it’s supposed to do—and nothing more than that.
Ready to Govern and Secure Your AI Agents?
Do you know which AI agents are operating across your organization, what data they use, and who is responsible when unusual behavior occurs? Schedule a consultation on Managed AI & Agents today.