How Soon Will Agentic AI Usher in a New Era of Enterprise-Focused Automation?

NEW YORK, Aug. 6, 2025 — Agentic AI is the next big thing for generative AI and is set to essentially reshape Enterprise Resource Planning (ERP) systems by transforming from a traditionally passive infrastructure to one that actively manages end-to-end workflows.

Agentic AI is also helping to deliver dynamic decision support, and elevate the user experience through conversational interfaces.  

In a recent benchmarking survey, Bain found out from nearly 500 IT leaders about their expectations for ERP and agentic AI. Majority (78 percent) expect at least some ERP functionality to be replaced or augmented by agentic AI over the next three years.

Nearly half (44 percent) expect AI to affect more than 10 percent of ERP functionality during that time frame, and 16 percent expect AI to affect more than 25 percent of ERP functionality.

A divide between leaders and laggards was also reflected by the Bain survey. While 35 percent of respondents said that ERP was enabling AI adoption, another 27 percent see it as a roadblock. Depending on the tech maturity, the perception of ERP’s role in AI adoption varies. Leaders find ERP helpful, while laggards see it as a drag.

How Vital is Integration with Existing Systems

Agentic AI solutions should ideally have a free-flowing integration with the current technology stack, including Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems.

This integration is crucial for a unified view of the customer and for AI agents to access the data they need and execute actions effectively. The Model Context Protocol (MCP) can help standardize these integrations, reducing friction.

In the transformational process, ERP has been touched at the far end as it is responsible for the management of critical business functions such as finance, supply chain, inventory, HR and customer success.

There is a vast value potential in AI for ERP. The providers are optimistic that it will streamline operations, improve efficiency, and drive innovation within enterprises.

Integration of Agentic AI in ERP

Some of the recent industry breakthroughs in integration of Agentic AI in ERP includes launch of an agentic platform by startup Opkey.

As per the company it offers such a dynamic scope, that it performs tasks in automation that are beyond imagination.

Considering that ERPs are nuanced systems, there is no room for failure. They are slower to change than other SaaS apps, adopting and incorporating new technology over time. Opkey has a core philosophy that time is ripe now to bring the AI revolution to ERP, transforming this critical piece of business infrastructure. 

With agentic AI, Opkey has developed a technology intelligent enough to simplify workstreams, handle complex assignments, and automate critical systems, once and for all. 

Similarly, IFS has plans in the pipeline to roll TheLoops’ agentic AI capabilities into its ERP system by year-end. However, customers will have to wait to know how much these features cost.

Somya Kapoor, CEO of TheLoops said, “The acquisition brings TheLoops’ full Agent Development life cycle (ADLC) platform into IFS, enabling enterprises to design, test, deploy, monitor, and fine-tune AI agents with built-in support for versioning, compliance, and performance optimization.”

She said it also offers a multi-agent building capability that enterprises can use to perform complex tasks or workflows by collaborating with internal and external agents with support from interoperability frameworks such as MCP and A2A.

Opkey’s AI Agents to Assist Customers One Must Know

Configuration agent: The role of this agent is to undertake configuration mapping, migrating planning, and execution to accelerate complex deployment workstreams.

Testing agent: The testing agent performs test automation and patch updates leveraging AI-powered, self-configuring test scripts and pre-built test scripts.

Training agent: Change management and end-user enablement is the task cut out for this agent. It uses test case data and AI-generated user guides to assist users via job aids, training, and personalized in-app prompts.

Support agent: The support agent assists end users at scale by analyzing user journeys, identifying root causes, and prompting the user to resolution.

Agentic AI solutions must seamlessly integrate with current technology stack, including Customer Relationship Management and Enterprise Resource Planning systems.

Inputs from Saqib Malik

Editing by David Ryder