AI agents are rapidly moving from experimentation into everyday operations. Sales teams use assistants to update CRMs, finance deploys bots for reconciliation, and IT explores agents for ticket triage. What these initiatives have in common is that they typically emerge locally: per team, per tool, per use case.

That feels innovative. Until it breaks down.

Without coordination, a new and often underestimated risk emerges: AI sprawl. Unlike SaaS or API sprawl, this is not just about complexity or cost. AI agents make autonomous decisions and execute actions within business-critical systems. Without central orchestration, speed quickly turns into chaos, with direct consequences for security, compliance and control.

What AI sprawl looks like in practice

AI sprawl occurs when teams independently develop and deploy agents, often outside the visibility of IT. In practice, this results in multiple patterns appearing at the same time: agents with their own integrations, different authorisation levels and overlapping functionality, each implemented slightly differently.

A familiar scenario is one where a marketing agent enriches customer data, a finance agent validates transactions, and an IT agent handles tickets. All three interact with partially the same systems, but with different credentials, context and decision logic. No one has a complete overview anymore.

The result is not only inefficiency and duplication, but a loss of control. Which agent has access to which data? What actions is it allowed to perform? And what happens if an agent is misconfigured or deliberately manipulated?

Because agents operate within the organisational perimeter, they often bypass traditional security controls. As a result, they silently expand the organisation’s attack surface.

Why AI sprawl is a security problem

Unlike traditional integrations, AI agents initiate actions autonomously. A single misconfigured agent can read sensitive data, make unauthorised changes or propagate unintended actions across multiple workflows.

This is not a theoretical risk. Real incidents show that agents can be exploited through indirect inputs, misleading context or vulnerabilities in the underlying tooling. At the same time, many IT and security teams admit they lack visibility into where agents are running and what they are actually doing.

This is where the core issue lies. Traditional security models are designed around users and applications, not autonomous decision-making entities. AI sprawl is therefore not a tooling issue, but a governance and architecture challenge.

Why MCP alone is not enough

Frameworks such as Model Context Protocol help AI agents interact with tools and actions in a standardised way. This is an important step forward.

However, MCP alone does not solve the core problem. If each department sets up its own MCP server, whether local or open source, a new form of sprawl simply emerges. Context may be standardised, but governance, security and compliance remain fragmented.

What organisations need is not a standalone MCP implementation, but an Enterprise MCP approach: a single, central layer where context, access, policies and observability come together.

From AI sprawl to orchestrated intelligence

The difference between uncontrolled AI and scalable agentic AI lies in orchestration. Not agents as isolated entities, but agents as a centrally managed fleet.

In an orchestrated model, all agents are registered and traceable. Policies and authorisations are enforced centrally. Exceptions are explicit and auditable. Logic is reused to prevent duplication.

The result is that IT retains control, audits become simpler, and innovation can move faster without the need for constant remediation afterwards. The focus shifts from “what can this agent do?” to “how does this system operate safely and predictably as a whole?”.

The role of Workato in controlling AI sprawl

This is where Workato comes into play.

Workato acts as an enterprise orchestration and execution layer in which AI agents do not interact directly with business systems, but through controlled workflows. Existing APIs, integrations and automations are exposed within a managed context.

With an Enterprise MCP approach enabled by Workato, organisations gain central governance and identity and access management, consistent logging and audit trails, built-in security and compliance mechanisms, and scalable, reusable automation logic instead of isolated API calls.

AI agents decide what needs to happen. Workato ensures that how it happens remains safe, traceable and controllable.

Why this matters for enterprise AI

Replacing AI sprawl with orchestration creates a fundamentally different dynamic. Processes become faster, but also more predictable. Security risks decrease as access and behaviour are centrally governed. IT can enable innovation rather than fixing issues after the fact.

This is the tipping point at which agentic AI becomes suitable for production environments: not as a collection of smart tools, but as an integrated part of the enterprise architecture.

Ciphix as an architecture partner

As a Workato partner, Ciphix helps organisations make this transition. Not by adding more agents, but by introducing structure before complexity takes hold.

Ciphix supports organisations in designing an Enterprise MCP architecture, governing agentic AI landscapes, connecting AI decision-making with controlled orchestration, and preventing new forms of sprawl.

In doing so, we help organisations scale AI responsibly, combining speed with control.

Conclusion

AI agents are here to stay. But without central orchestration, their potential becomes a risk. AI sprawl is the next major security challenge, and only an enterprise-grade approach can address it.

By bringing context, governance and execution together through Enterprise MCP and Workato, organisations can move from experimentation to controlled intelligence.

If you would like to explore how your organisation can prevent AI sprawl and deploy agentic AI in a safe and scalable way using Workato, our architects are happy to discuss an approach that fits your enterprise landscape.