What is Agentic AI, and how is it Transforming ERP?

It should come as no surprise that AI is changing enterprise SaaS. From project management to coding to graphic design, we’re deploying AI in all sorts of new ways.

The last frontier of AI transformation is Enterprise Resource Planning, or ERP.  

ERP has come last because it is responsible for the management of critical business functions. (Critical means finance, supply chain, inventory, HR, customer success, and more.) “Move fast and break things” just doesn’t cut it when outages and slowdowns can bring global enterprises to their knees.

Still, there’s tremendous value potential in AI for ERP. Providers promise it will streamline operations, improve efficiency, and drive innovation within enterprises. In this blog, you will learn about agentic lifecycle management systems, and how they can help in addressing challenges with updating your ERP.

The Current State of ERP

Advances in ERP in the last few years have allowed organizations to break down silos and centralize operations. The ultimate goal of this centralization is better, data-driven decisions that improve everyday business functions. Businesses also see lower costs with automation through ERP.

Or so we hoped.  

In reality, enterprises often end up using different applications to manage different core business processes. For example, a company may prefer Workday for HR and talent management, and Oracle for finance and accounting. The split may make sense on a business level, but unfortunately it leaves organizations right back where they started–with siloed data on disparate apps. Not automated.  

To solve this problem, ERP providers built out some new tools, like Business Process Management and Workflows, to gain visibility and streamline systems. These tools work by running rules-based mechanisms across different ERPs.

Although these techniques can streamline processes to some extent, they’re still not truly automated. Often, they require extensive human intervention for tasks including:

• Transferring data from one system to another

• Handling exceptions or errors in workflows

Again, these manual tasks have turned out to be a burden. Not automated.

To address this latest challenge, organizations started adopting Application Programming Interfaces, or APIs. APIs help solve the problem by automating data transfer within disparate systems.  

What happened? You guessed it! APIs help, but in turn require custom development and ongoing maintenance. Manual. Not automated.

Robotic Process Automation, or RPA, is supposedly the next development, covering repetitive, rule-based challenges of API management.

RPA improves utility, but it too comes with challenges. For example:

• While RPA works well with structured data (like invoices and forms), it struggles with unstructured data (like emails, images, or customer feedback).

• RPA is limited to predefined workflows–it needs manual assistance to adapt to business changes, regulatory changes, and one-off exceptions.

In short: RPA helps, but it hasn’t solved the problem. It’s not useful for complex, multi-step processes that require decision-making, and the complexity involved makes it expensive to scale.

Luckily, we may have finally found a technology that will reduce system complexity for users once and for all.  

It’s called agentic AI, and it’s powerful and intelligent enough to finally bring the promises of ERP to fruition.

What is Agentic AI?

As we’ve seen, developments so far haven’t truly eradicated system inefficiency, and haven’t delivered true automation. So, what’s different about agentic ai? This technology is still evolving, but the linchpin difference is that agentic ai agents can make decisions and act without human intervention.

All agentic ai agents are trained on some kind of AI model. (You’ve probably heard of Large Language Models, or LLMs, but Small Language Models, or SLMs, can be even more effective for certain tasks. To learn more, click on the link.) Engineers train digital agents on advanced capabilities like data analysis, so that they can make decisions on your behalf and continuously learn from future interactions.

This ability to adapt, even when presented with new context and changing conditions, is what sets agentic AI apart. Built to adapt, it can succeed even in complex environments like ERPs.

Learn more: How AI Is Reshaping ERP Implementation Processes

How does Agentic AI work?

Agentic AI is a big development in a multi-decade story of neural nets and computer science. It combines the latest in machine learning, natural language processing, and language models to generate useful outputs.  

AI agents continuously learn, incorporating more data to hone analysis and, ultimately, to improve results for you. Digital agents continuously observe the system as humans use it and augment their ability to make decisions moving forward.  

How does Agentic AI fill the gaps in automation?

Unlike previous forms of automation, agentic AI is able to process and interpret unstructured data. For instance, agentic systems can extract information from the prose of customer emails and automatically update records in ERPs.

Agentic AI also excels at adaptive decision making. Since Agentic AI can analyze data in real-time, workflows can also be automatically modified accordingly. Leveraging RPA and cognitive capabilities like reasoning and learning, AI agents can manage end-to-end operations.

Agentic AI can also recognize patterns associated with errors and exceptions, predict and anticipate issues, and help you avoid them--correctly executing tasks, even in a completely new context.

Agentic AI can indeed fill gaps in automation left by RPA, APIs, and Business Process Management. But its utility and functionality go beyond that. At Opkey, we’ve launched an agentic platform. It’s so revolutionary in scope that it pushes the bounds of what we even imagine when it comes to automation. Opkey’s digital agents can help you achieve:

• Low/No-Downtime on Updates. Regular updates from ERP providers can be ridden with issues, costing you time and money. Opkey’s digital Testing Agent changes that. More than just test automation, Testing Agent delivers process mining, observability, predictive analytics, and built-in intelligence to anticipate business process changes. Sensing a potential problem, it executes tests and reports back to you, all while your team is busy focusing on higher priority tasks.

Learn more: Opkey's Agentic AI Automation to Maximize ERP Value

• Success in Big IT Projects. More than 70% of all digital transformation projects fail, and one of the most common reasons for failure is lack of end-user adoption. To get your people up to speed on new systems, you need built-in training that is personalized, interactive, and engaging. Armed with test case data and generative AI, Opkey’s Training Agent develops and edits user guides, making sure your people are trained on how to use new functionalities quickly and seamlessly.

Learn more: Opkey’s AI Test Automation

• Better Support & Change Management. ERPs require regular maintenance. IT teams accept support tickets to collect information on system issues. Responding to these queries and flags can be incredibly time consuming, and many of them are either knowledge-based questions or low-level IT issues–the kind of thing agentic can easily nip in the bud. Opkey’s Support Agent automatically resolves issues in tickets and observes and analyzes system function. With a reduced burden of tedious tickets, and greater visibility into issues, IT teams can focus on higher order tasks.  

Conclusion

ERPs are complex and crucial systems, and there isn’t room for failure. As a result, they’re slower to change than other SaaS apps, adopting and incorporating new technology over time. It’s now time, though, to bring the AI revolution to ERP, transforming this critical piece of business infrastructure.  

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