Can AI Solve Legacy Tech Problems? Companies Are Putting It to the Test

Introduction

In the ever-evolving landscape of technology, the challenge of dealing with legacy systems has become more pronounced. Generative AI is emerging as a transformative force, providing business technology leaders with innovative solutions for modernizing their aging information-technology systems. This article explores the dynamic intersection of artificial intelligence and legacy tech, focusing on how companies are leveraging generative AI to tackle the perennial problem of outdated code.

The Cobol Conundrum: An Aging Dilemma

Amin Venjara, Chief Data Officer of ADP, sheds light on the persistent issue of Cobol, a programming language that predates the Beatles and still lingers in many legacy systems. The scarcity of developers proficient in Cobol poses a unique challenge for companies, leading them to explore unconventional solutions. As organizations grapple with finding Cobol engineers, generative AI emerges as a potential savior, offering a novel approach to translate Cobol code into more contemporary languages.

ADP’s Quest for Modernization

ADP, a 75-year-old payroll-processing company based in Roseland, N.J., finds itself at the crossroads of tradition and innovation. Tasked with modernizing its mainframe code, which is predominantly in Cobol, the company is embarking on a journey to harness the power of generative AI. The goal is not only to translate code but to bridge the gap between the old and the new, enabling a smoother transition for a system that has stood the test of time.

The Evolution of Programming Languages

The programming landscape has evolved significantly since the inception of Cobol in the 1950s. ADP’s shift from Cobol to Java, a language that came into existence in 1995, signifies a broader trend in the industry. The quest for more modern and versatile programming languages reflects the necessity of keeping pace with technological advancements. Generative AI becomes the linchpin in this evolution, facilitating the seamless translation of code across different languages.

The Rise of Generative AI in Legacy Upgrades

In recent times, the spotlight has shifted from generative AI assisting in routine coding tasks to its application in upgrading legacy code. Tech giants like Microsoft-owned GitHub, Amazon, Google, and IBM have introduced coding assistants that utilize generative AI. Originally designed to enhance productivity in tasks like auto-completing code snippets, these tools are now venturing into the realm of legacy system upgrades, marking a paradigm shift in their utility.

Microsoft’s GitHub: Pioneering Generative AI

GitHub, a platform synonymous with collaborative coding, takes a pioneering stance in the realm of generative AI. Microsoft-owned GitHub’s coding assistant stands out as a testament to the evolving role of AI in the coding ecosystem. By addressing the challenges associated with legacy code, GitHub’s generative AI tool becomes a valuable asset for developers seeking efficiency in not just creating new code but transforming outdated systems.

Amazon, Google, and IBM: Collaborative Innovations

The collaboration between industry giants Amazon, Google, and IBM further underscores the collective effort to harness generative AI for legacy upgrades. These companies are at the forefront of the AI revolution, extending their coding assistants to support the transformation of old codebases. The convergence of their efforts signifies a shared commitment to leveraging cutting-edge technology for addressing the pressing challenges of legacy systems.

IBM’s Watsonx AI Coding Assistant: A Gateway to Modernization

IBM, a stalwart in the mainframe business, introduces its Watsonx AI coding assistant as a potent tool for addressing the complexities of legacy tech. Skyla Loomis, Vice President of IBM’s Z mainframe software, sheds light on the challenges companies face when dealing with extensive applications boasting millions of lines of code. IBM’s coding assistant, powered by generative AI, emerges as a gateway to modernization, offering a streamlined process for migrating from Cobol to Java.

Accelerating Legacy System Updates

Launched last fall, IBM’s coding assistant promises a significant reduction in the time required to update legacy systems. The traditional approach to updating extensive codebases could take several years, but with generative AI, IBM aims to condense this timeline to just a year or two. The ability of generative AI to understand the intent of the code and swiftly transform it into usable Java positions it as a catalyst for expeditious and effective legacy system upgrades.

Conversational Coding: IBM’s Innovative Approach

IBM’s coding assistant introduces the concept of conversational coding, allowing developers to ask questions in plain English. This innovative approach not only enhances communication between developers and the coding tool but also bridges the gap for those less familiar with the intricacies of legacy code. By democratizing the coding process, IBM aims to empower a broader spectrum of developers to engage in the modernization journey.

Wayfair’s Approach with Google’s Coding Assistant

Wayfair, a prominent online furniture seller with two decades of history, faces its unique set of challenges in modernizing its technology infrastructure. While Wayfair doesn’t contend with Cobol, it grapples with the intricacies of “legacy code” written in languages like PHP, old database code in SQL, and contributions from developers who have since left the company. Fiona Tan, Wayfair’s Chief Technology Officer, sheds light on how the company is leveraging generative AI, particularly Google’s coding assistant, to streamline the process of updating old code.

Navigating Multifaceted Legacy Code

Wayfair’s journey involves navigating a diverse landscape of legacy code, each with its own set of challenges. The use of generative AI allows the company to address not just a single language but a myriad of coding languages present in its system. This multifaceted approach ensures a comprehensive modernization strategy, minimizing disruptions and accelerating the overall digital transformation process.

AI Tools as Reducers of Technical Debt

Wayfair recognizes the significance of AI tools in reducing “technical debt,” a term referring to the flaws and costs that accumulate when companies attempt to fix technology problems hastily. The AI tools, by expediting the learning process of new languages and facilitating smoother transitions, play a pivotal role in minimizing the technical debt associated with legacy systems. As a result, engineers can focus on innovation rather than grappling with the complexities of outdated code.

Databricks: Navigating Codebases with Generative AI

Databricks, a San Francisco-based data storage and management firm, embraces generative AI to enhance engineers’ comprehension of the company’s codebase. Naveen Zutshi, Databricks’ CIO, emphasizes the challenges of picking up old codebases and the importance of quickly understanding the intricacies of a codebase. Generative AI becomes a valuable asset for engineers aiming to decipher complex systems efficiently.

Code Understanding for Enhanced Productivity

The role of generative AI in helping engineers quickly understand codebases cannot be overstated. Databricks relies on AI to alleviate the pain associated with deciphering intricate code, allowing engineers to focus on innovation and optimization. By accelerating the learning curve, generative AI contributes to heightened productivity and efficiency in navigating the complexities of a large-scale data storage and management system.

The Imperative of Swift Codebase Navigation

In the fast-paced tech landscape, the imperative of swift codebase navigation cannot be overstated. Databricks recognizes the significance of generative AI as a tool not just for code generation but as a facilitator for quick comprehension. As companies evolve, the ability to swiftly adapt to changing codebases becomes a competitive advantage, and generative AI proves to be a valuable.

Related Content:

Free Worldwide shipping

On orders dispatched and delivered within the same country.

Easy 30 days returns

30 days money back guarantee

International Warranty

Offered in the country of usage

100% Secure Checkout

PayPal / MasterCard / Visa