The Legacy IT Challenge: Bridging the Gap Between Established Systems and the AI Revolution
For decades, businesses have relied on core systems – the operational backbone that drives critical functions. But these systems, often built and refined over years, are increasingly facing a reckoning. The rise of technologies like Artificial Intelligence (AI) is exposing a fundamental challenge: how do you unlock the value trapped within legacy IT infrastructure and integrate it into a modern,data-driven future?
Forrester recently urged IT leaders to address the growing burden of technical debt and aging applications. While a complete overhaul isn’t always feasible – or even desirable – ignoring the issue is no longer an option. The reality is, many legacy systems still deliver significant business value. The problem isn’t necessarily that they’re broken, but that they often struggle to adapt to evolving business needs and, crucially, to fuel the data demands of emerging technologies like AI.
The Neutral Cost of Modernization – and why It Matters
As Jeremiah Stone, CTO at SnapLogic, points out, a significant hurdle in legacy modernization is that it often results in a business value-neutral exercise. Years of investment and refinement have created systems that, while perhaps not cutting-edge, are deeply ingrained in operational workflows. “They’ve become the operational backbone of the business,” Stone explains, “and in a perfect world, you wouldn’t touch them because they’ve been curated and loved, and put into a position where the business can run upon them.”
However, the “perfect world” rarely exists. Business requirements shift,and new technologies emerge that don’t seamlessly integrate with older systems. This creates a critical tension: the need to innovate versus the risk of disrupting established processes.
AI’s Insatiable Appetite for Data – and Legacy Systems‘ Data Silos
Perhaps no technology highlights this tension more acutely than AI. The promise of AI is immense, but its foundation is simple: data. As Ralf schundelmeier, Head of Enterprise Data and Platforms at Boehringer Ingelheim, succinctly put it at the recent Integreat conference, “AI needs data. Without data, there is no AI. You need good data and you need to get your data AI-ready.”
But what happens when that “good data” resides within legacy systems, often locked away in formats that are difficult to access and analyze? Boehringer Ingelheim, a pharmaceutical giant with a long history of data collection, faced this exact challenge. They discovered much of their valuable data was trapped on systems lacking modern Submission Programming Interfaces (APIs) and proper data cataloging.
This is a common scenario. Many enterprises find themselves sitting on a goldmine of details, inaccessible to the tools that could unlock its potential.
breaking Down the Silos: The Rise of Agentic Integration
The solution isn’t always a rip-and-replace modernization. Instead, a more pragmatic approach focuses on integration – connecting legacy systems to modern data pipelines and AI platforms.This is where tools like SnapLogic come into play.
SnapLogic, built on the principles of modern middleware, effectively acts as a bridge, connecting disparate data sources and enabling enterprise application integration. The company’s experience navigating numerous IT architectural shifts has positioned it as a key player in this space. Stone notes that a significant portion of the systems they encounter were originally deployed between 1995 and 2006 – predating the widespread adoption of cloud computing.
Despite the ongoing migration to the cloud, a substantial amount of enterprise infrastructure remains on-premise.Stone estimates that less than 50% of enterprise workloads have moved to the cloud, highlighting the continued relevance of legacy systems.
Accelerating Digital Transformation and Controlling Costs
The need for integration is driven not only by AI but also by broader trends in digital transformation. As Betsy Burton, VP of Research at Aragon Research, observes, enterprises are actively seeking ways to accelerate their digital initiatives while simultaneously controlling expenses and updating aging systems.
Recognizing this chance, SnapLogic is positioning itself as an “agentic integration” company. They understand that the vast majority of enterprise data still resides within legacy systems and are focused on providing solutions to seamlessly integrate these systems into modern AI strategies. Their latest offering, SnapLogic Clever Modernizer, aims to streamline the often-complex process of legacy workload migration.
The Path Forward: A Strategic Approach to Legacy IT
The challenge of legacy IT isn’t about eliminating the past; it’s about leveraging it to build a more intelligent future. Here are key takeaways
