MIT Technology Review has published analysis on the business case for modernizing legacy systems in an era of generative AI. The traditional narrative around legacy modernization has framed it as a cost center—a complex, disruptive project with unclear ROI. But with AI systems increasingly requiring structured, clean data and APIs to deliver value, legacy infrastructure has shifted from a "nice to have" modernization to a strategic enabler.

Companies maintaining isolated, decades-old systems struggle to feed high-quality data into AI systems, limiting ROI. Modernization now unlocks AI capabilities: better data integration, faster automation, predictive analytics. The business case has inverted—legacy systems are now the constraint limiting AI value capture.

What This Means for Your Business

If your organization has deferred legacy system replacements or upgrades, this is a forcing function to revisit those decisions. The ROI calculation now includes AI enablement, not just operational efficiency. Finance and IT leadership should jointly reassess legacy modernization roadmaps through the lens of AI readiness; the cost of modernization may now be lower than the opportunity cost of not doing so.