Integrating AI Agents with Enterprise Systems

An AI agent that cannot access your systems is like a new hire without a computer. The real value of agentic workflows comes from connecting them to the data, tools and processes that run your organisation.

But enterprise integration is notoriously complex. Here is how to approach it without creating a maintenance nightmare.

The integration challenge

Most organisations have a tangled landscape of systems: CRMs, ERPs, HR platforms, ticketing tools, databases, file stores and more. Many of these were never designed to work together, let alone with AI agents.

Agentic workflows need to:

• Read data from multiple sources.
• Write updates back to systems of record.
• Trigger actions in other tools.
• Respect security, permissions and audit requirements.

Getting this right requires careful planning and a pragmatic approach to what is possible.

Start with the workflow, not the technology

It is tempting to start by cataloguing all your APIs and data sources. Resist this urge. Instead, start with the workflow you want to automate.

Ask:

• What data does the agent need to do its job?
• What systems must it update?
• What actions must it trigger?
• What permissions and guardrails apply?

This workflow-first approach keeps you focused on what matters and avoids over-engineering.

Favour standard protocols

Where possible, use standard integration protocols: REST APIs, webhooks, OAuth for authentication. These are well-understood, widely supported and easier to maintain.

Avoid building custom, point-to-point integrations unless absolutely necessary. They work in the short term but become fragile as systems evolve.

If a system lacks a modern API, consider middleware or integration platforms that can abstract the complexity. The goal is to give your agents a clean, consistent interface to the systems they need.

Handle authentication carefully

Agents need credentials to access enterprise systems. This creates security risks that must be managed.

Best practices include:

• Use service accounts with the minimum permissions required.
• Store credentials securely, using secrets management tools.
• Rotate credentials regularly.
• Log all agent actions for audit purposes.

Avoid giving agents broad administrative access. Principle of least privilege applies just as much to AI as to humans.

Design for resilience

Enterprise systems go down. APIs change. Data gets corrupted. Your agentic workflows need to handle these realities gracefully.

Build in:

• Retry logic for transient failures.
• Graceful degradation when a system is unavailable.
• Alerting when integrations fail.
• Clear escalation paths for issues that cannot be resolved automatically.

Assume things will go wrong and design accordingly.

Respect the system of record

One of the biggest integration pitfalls is creating data inconsistencies. If an agent updates a record in one system but fails to sync it elsewhere, you end up with conflicting versions of the truth.

Identify your systems of record for each data type and ensure agents respect them. When in doubt, read from the source and write back to the source. Avoid caching data in the agent itself.

Legacy systems are not a blocker

Many organisations assume agentic workflows are incompatible with legacy systems. This is rarely true.

Legacy systems can often be integrated through:

• Screen scraping or robotic process automation (RPA) for systems without APIs.
• Database connectors for direct data access.
• File-based integrations for batch processes.
• Middleware that wraps legacy systems with modern interfaces.

The integration may be less elegant, but it is usually possible. Do not let legacy concerns become an excuse for inaction.

Plan for change

Enterprise systems are not static. Vendors release updates, APIs change, and new tools are adopted. Your integration layer needs to accommodate this.

Practical steps include:

• Abstract integration logic so changes in one system do not cascade everywhere.
• Monitor for API deprecations and breaking changes.
• Maintain documentation of all integrations and their dependencies.
• Test integrations regularly, not just when something breaks.

The payoff

Getting integration right is hard work, but the payoff is substantial. Agents that can access your systems become genuinely useful: they can answer questions, take action and drive outcomes without constant human intervention.

The alternative - agents that are isolated from your enterprise stack - delivers only a fraction of the potential value. Invest in integration, and your agentic workflows will repay you many times over.