Migrating Legacy Systems to Agentic AI
ServiceNow and Accenture launched tools to migrate legacy security systems to agentic AI, reducing enterprise risk.
On June 29, 2026, Accenture and ServiceNow introduced a joint offering to help enterprises modernize risk management and migrate legacy cybersecurity platforms to agentic AI. This new collaboration uses managed security services on the ServiceNow AI Platform alongside an Accenture automation tool to handle the migration process. It matters because it targets the heavy cost and friction of leaving outdated systems behind, offering a path to connect scattered business tools and AI agents under one roof.
The heavy toll of legacy system migration
Outdated cybersecurity tools are sticky. They hold critical business data, but they slow down modern operations and cost too much to maintain. Many CTOs want to move to modern AI-driven setups, but the fear of breaking existing workflows keeps them stuck. This fear is not misplaced. Migrating legacy setups usually means dealing with mismatched data schemas and broken APIs.
When you attempt to dismantle legacy infrastructure, you run into decades of custom configurations. Security rules written ten years ago by engineers who have long left the company still run in the background. Nobody knows exactly what they do, but everyone is afraid to turn them off. If you turn them off, you might blind your security operations center. So, the old systems remain, consuming budget and slowing down response times.
But staying on old software is no longer a viable strategy. Security threats move too fast for manual intervention. The announcement from Accenture and ServiceNow shows that the market is shifting its focus toward automated transition tools. They want to make it easier for enterprises to move their operations onto a single platform that can run AI agents alongside traditional software. This is a step forward, but the migration itself is only the first obstacle.
How the new joint offering works
The partnership combines two main pieces. First, it introduces managed security services built on the ServiceNow AI Platform. Second, it includes an Accenture solution designed to automate the migration process itself. This setup is built to unify legacy systems, departmental tools, cloud applications, and AI agents into one operational view.
By automating the transition, the two companies aim to cut the high costs and complexity that usually stall these projects. Instead of manual data mapping, the AI-driven system handles the heavy lifting of translating old security rules into modern, agentic workflows. This allows operations teams to focus on setting policies rather than fixing broken pipelines.
The automated migration tool analyzes legacy code, maps the data structures to the ServiceNow platform, and sets up initial automation rules. This reduces the manual labor that typically consumes months of engineering time. It provides a cleaner starting point for companies that want to adopt autonomous agents but are held back by their technical debt.
Why agentic systems need strong operational plumbing
A single view of your systems is a great start. But a dashboard cannot run your business on its own. When you deploy AI agents to handle risk management, they need to make decisions and execute actions across different tools. This is where many enterprise AI projects fail. They work well in a demo, but they fall apart when they hit the messy reality of production.
We see this frequently at Algo & Art. Building an agentic system requires more than just connecting an LLM to an API. It requires solid engineering to handle rate limits and sudden system failures. If an agent misinterprets a security alert and shuts down a critical server, the fallout is immediate. Enterprises need reliable pipelines and strict safety guardrails to keep these autonomous agents in line.
The challenge lies in the unpredictable nature of generative models. Unlike traditional software, AI agents can respond differently to the same input based on subtle changes in context. In a security environment, predictability is everything. You cannot let an autonomous agent decide on a whim how to isolate a compromised system. You need to wrap the agent in a structured framework that limits its actions to safe, pre-approved bounds.
How we build production pipelines that last
At Algo & Art, we help companies move past the demo phase. While platforms like ServiceNow provide the foundation, we build the custom orchestration and operational plumbing that makes these systems reliable at scale. Our team designs automation pipelines that connect legacy infrastructure to modern AI agents. And we make sure those pipelines do not compromise your existing security rules.
Our focus is on the practical mechanics of agentic workflows. We build evaluation frameworks to test how agents perform under stress. We implement guardrails to prevent unauthorized actions and ensure compliance. This hands-on engineering is what turns a promising AI tool into a reliable part of your daily operations.
We also build mock environments to simulate security incidents. This allows us to test how the AI agents interact with other enterprise software before they go live. We monitor latency, error rates, and decision-making accuracy. If an agent struggles with a specific type of alert, we catch it in testing, not in production. This level of operational rigor is what makes agentic AI safe for the enterprise.
Frequently asked questions
What did ServiceNow and Accenture announce on June 29, 2026?
They launched a joint offering to help enterprises migrate from legacy cybersecurity platforms to agentic AI. The solution includes managed security services on the ServiceNow AI Platform and an Accenture tool that automates the migration process.
Why is migrating from legacy cybersecurity systems so difficult?
These migrations are typically held back by extreme complexity, high costs, and the risk of breaking existing security workflows. Legacy systems often use outdated data formats that do not work well with modern AI agents.
How does Algo & Art support enterprise AI migrations?
We build the underlying production pipelines and custom agent orchestration needed to make these systems reliable. Our team ensures that your AI agents work safely with both legacy tools and modern cloud applications.