Agentic AI: Revolutionizing Enterprise Integration with Data-Driven Intelligence

Agentic AI refers to autonomous intelligent agents capable of independent action and collaboration to fulfill complex business tasks. These AI systems require extensive access to high-quality, reliable data from multiple systems to generate meaningful and actionable insights.

Integration becomes the backbone of this intelligence, connecting disparate systems such as ERP (SAP S/4HANA), cloud data platforms, and operational applications. The success of AI-driven initiatives hinges on providing agents with trustworthy data inputs that are synchronized, accurate, and timely.
Integration expert Roberto Viana, emphasizes:

"AI applications are hungry and thirsty for data. And of course, if you want to have convincing and meaningful results, valuable results for the business, you have to provide them with good data from many different angles."

This data-centric view elevates integration from a back-office technical task to a strategic enabler of AI-driven business processes.

Use Case Spotlight: AI-Enhanced Customer Service and Order Tracking

One of the clearest examples of agentic AI in action is the automation of customer service inquiries, such as order status requests. This seemingly simple question requires aggregating information from multiple sources:

• E-commerce systems
• ERP order management (e.g., SAP)
• Inventory and stock systems
• Shipping and logistics platforms

Failures or delays in any link directly result in disrupting the customer experience. AI agents that can autonomously query these interconnected systems and correlate events (like stock shortages or shipment delays) can drastically reduce response times and operational costs.
Roberto Acevedo explains:

'Instead of a customer service agent manually checking five different systems over hours, an AI agent can provide an answer in seconds, sometimes even resolve the issue directly.'‍

This automation is particularly impactful for call centers and outsourced customer service operations, delivering cost efficiencies alongside improved customer satisfaction.

Transitioning to AI-Ready Integration: Practical Data Strategy Approaches
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Implementing agentic AI does not require waiting for perfect data governance or fully mature data strategies. Enterprises can, and should, start with existing systems of record, typically trusted SAP ERP environments, as foundational data sources for AI agents. Roberto Acevedo advises:

"Most companies don’t have a fully ready data strategy. Waiting for that means missing the opportunity. The key is to start transitioning now.'‍

By progressively incorporating AI use cases into the integration landscape, organizations can iteratively improve data quality, synchronization, and security. This agile approach allows for testing and validation while building organizational support and capabilities around AI-driven processes.

Preparing SAP Integration for the Agentic AI Era

The rise of agentic AI calls for SAP integration teams to rethink their roles and toolkits:

• Expanding the scope beyond transactional integration to include real-time event streaming and multi-agent coordination
• Leveraging emerging adapters and connectors, such as those for Large Language Models (LLMs) and cloud data platforms (e.g., Snowflake)
• Supporting event-driven architecture principles to enable decoupled, scalable, and responsive business processes

Viana highlights the integration suite’s evolving capabilities:

“SAP is already delivering many adapters, for instance, the Snowflake adapter and soon an LLM adapter within the SAP integration suite, which will play a key role in this revolution of agentic AI.”

This paradigm shift ensures that SAP landscapes remain agile, intelligent, and ready to fuel AI-powered innovation across departments.

Conclusion: The AI-Integrated Enterprise is Within Reach

The combination of agentic AI with event-driven SAP integration is already delivering measurable business value, especially in customer service automation and operational responsiveness. Enterprises no longer need to wait for perfect data strategies or complex architectural overhauls. Instead, they can begin transitioning immediately, connecting AI agents to trusted systems of record and scaling use cases over time. Roberto Acevedo summarizes:

“It doesn’t really matter if you have a data strategy or not at this moment. It’s about starting, testing it out, and you’re going to get surprised about the results.”

This new era of integration to intelligence promises a future where intelligent agents streamline processes, empower employees, and create competitive advantages. Preparing SAP environments today for agentic AI will be critical to unlocking these opportunities tomorrow.

Watch the full conversation of our Integration Unplugged series on YouTube  to learn more about the evolution and future of enterprise integration shared by industry experts Roberto Acevedo and Roberto Viana.
Prefer to listen on the go? The Integration Unplugged Series is also available as a podcast.

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Ready to make your SAP environment AI-ready and event-driven? Get in touch today to learn how to streamline your processes and drive intelligent business outcomes.

Missed the first part:
You can find the first episode focusing on the strategic implications of the S/4HANA migration and integration modernization, here.