Why enterprise AI ambitions are outpacing legacy modernization (www.techradar.com)

In a rapidly evolving AI landscape, organizations are increasingly prioritizing legacy modernization to enhance operational efficiency and support AI initiatives. According to Cognizant research, 85% of senior executives express concern that outdated technology hampers AI adoption, yet only 18% expect to address over half of their technology debt by 2030. The urgency lies in ensuring that legacy systems, which often bear the weight of critical processes, can adapt to today's data-driven and secure AI demands. However, many businesses struggle with technology debt, complexity, and resource constraints, limiting their ability to modernize swiftly. Legacy systems, designed long before the rise of AI, hinder meaningful integration due to fragmented data and cumbersome manual processes. As organizations aim for substantial progress within two years, focusing on smaller, operationally beneficial changes—like improving system visibility or reducing manual tasks—can facilitate smoother modernization efforts. By systematically addressing technology debt and leveraging AI to automate documentation and improve legacy code comprehension, businesses can set the foundations for future growth. This approach allows firms to align AI aspirations with the realities of their existing infrastructure, ultimately determining their competitive edge in an AI-driven future.