Many large organizations struggle with outdated digital systems that hinder their ability to innovate quickly. A significant portion of the software used by major companies is over 20 years old. Modernizing these systems is often a complex and costly process, but McKinsey’s LegacyX platform aims to simplify this challenge. By leveraging generative and agentic AI, LegacyX can accelerate modernization efforts by up to 80%, significantly reducing costs and time. This advanced AI not only updates technology but also optimizes the associated business processes, making organizations more agile. McKinsey’s approach emphasizes the importance of integrating human expertise with AI to transform legacy systems intelligently and efficiently.
On March 20, 2025, a significant challenge faced by large organizations today is their aging digital infrastructure, which often hampers innovation and agility. Studies reveal that about 70 percent of the software utilized by Fortune 500 companies is over 20 years old. Modernizing these outdated systems is no simple task; it typically involves hundreds of engineers, lengthy timelines, and substantial financial investments. Additionally, the existing business processes intertwined with these legacy systems further complicate the modernization efforts.
To tackle this issue, QuantumBlack, AI by McKinsey has introduced a groundbreaking platform called LegacyX. Designed to leverage generative and agentic AI, LegacyX can speed up modernization efforts by up to 80 percent while simultaneously cutting costs and minimizing resource usage. This innovative approach not only rejuvenates technological frameworks but also optimizes business processes. By intelligently analyzing workflows, agentic AI ensures seamless integration of new technologies with existing systems.
The transition from generative AI to agentic AI marks a pivotal evolution in legacy system modernization. Generative AI has already proven useful in updating software code, significantly enhancing developer productivity. However, agentic AI takes this a step further by orchestrating autonomous teams of specialized agents to manage complex technological infrastructures in real time.
For instance, McKinsey recently collaborated with a global bank tasked with converting over 100 legacy risk models from SAS to Python. By implementing LegacyX and creating five specialized squads, the project achieved an 80 percent acceleration in its timeline, all while keeping human developers involved in the process.
The potential of LegacyX extends beyond just coding; it aims to make AI accessible to everyone within an organization. Business analysts without coding experience have successfully utilized the platform to create teams of agents for various tasks, showcasing how agentic AI can enhance productivity across different roles.
McKinsey’s approach, dubbed “Never Just Tech,” focuses not only on introducing AI but also on developing human-led, AI-powered solutions that facilitate meaningful transformations in businesses. LegacyX stands as a testament to this philosophy, enabling organizations to refresh their legacy systems with intelligence, speed, and efficiency.
Primary keyword: Legacy modernization
Secondary keywords: QuantumBlack, AI by McKinsey; agentic AI; generative AI; digital infrastructure.
Tags: Legacy Modernization, QuantumBlack, Agentic AI, Business Transformation, Digital Infrastructure Solutions, McKinsey AI.
What is agentic AI and how does it help legacy infrastructure?
Agentic AI is a type of artificial intelligence that can make decisions and take actions on its own. It helps improve legacy infrastructure by automating tasks, reducing downtime, and optimizing performance. This means old systems can work better and more efficiently.
Why should companies rejuvenate their legacy infrastructure?
Companies should rejuvenate legacy infrastructure to stay competitive. Upgrading helps enhance productivity, reduce costs, and improve security. This also allows businesses to adapt to new technologies and meet customer demands more effectively.
Can implementing agentic AI be expensive?
While there may be initial costs to implement agentic AI, it can save money in the long run. By improving efficiency and reducing errors, businesses can lower operational costs. Many companies find that the benefits outweigh the upfront investment.
How long does it take to see results from rejuvenating infrastructure with agentic AI?
The time it takes to see results can vary. Some improvements might be visible within weeks, while major changes could take months. It depends on the complexity of the infrastructure and the specifics of the AI solutions being implemented.
Is my business too small for agentic AI solutions?
No, businesses of all sizes can benefit from agentic AI solutions. There are many scalable options available that can fit different budgets and needs. Even small businesses can improve their operations with the right technology and support.