Legacy software systems, especially those built on COBOL, are both a marvel and a menace. As of 2023, these systems power 70% of financial institutions, handling $3 trillion in daily transactions--a figure drawn from a comprehensive industry report [1]. Globally, an estimated 200 billion lines of COBOL code remain in use, a testament to its durability since its inception in 1959, as noted in a 2024 IEEE analysis [2]. These systems underpin critical operations--think payroll processing, account management, and loan calculations in banks and insurance firms. Yet, their age is a liability: complexity averages 18 paths per module, well above the modern ideal of 10, while coupling averages 8 dependencies, fostering a 30% higher defect rate than languages like Java [3]. Maintenance consumes 60% of IT budgets, a burden intensified by a dwindling COBOL workforce--now just 5% of developers, per a 2025 Gartner estimate [4]. Modernization is not optional; it is a necessity, and this study proposes an AI-driven solution to transform COBOL into Java, with React illuminating the results.

This is our AI Daily Roundup today. We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities in artificial intelligence (AI), Machine Learning, Robotic Process Automation, Fintech, and human-system interactions. We cover the role of AI Daily Roundup and its application in various industries and daily lives. Businesses are immensely benefiting from AI adoption.

Artificial intelligence (AI), machine learning (ML), and predictive analytics (PA) are current buzzwords eclipsing the tech industry hype curve. At this point, most tech savvy people are tired of hearing how these techniques will save the day. Let's eliminate some of the hype and paint a more realistic picture of what's happening with these technologies. All three are surprisingly old concepts. Predictive analytics can trace its origins back to Thomas Bayes, who laid the foundation to Bayesian probability theory in 1736. Nothing new here, except within the last 50 years, computers have made it much easier to work with the math.

Robotic process automation (RPA) is a software designed to streamline business processes using automated'bots' that take over repetitive, rules-based tasks from employees. Based on mimicking how humans interact with technology, these bots learn from existing business processes and follow rules to create efficient workflows. RPA is becoming extremely popular in businesses today as a means to ultimately improve efficiency by alleviating workers from these mundane tasks to focus on higher-value activities. However, RPA solutions are imperfect and the ability to meet business's expectations is constrained by a few limitations. RPA is designed to automate only parts of tasks that are made visible through a user interface, and does not have the capability to automate complex processes from end-to-end.

Join our Vivit Ohio Vivit Local User Group and Micro Focus for discussion about the latest innovations in artificial intelligence and machine learning as they relate to quality assurance and functional testing, and how they will address and solve the continuous delivery issues facing the software industry today. The event, hosted by Micro Focus in partnership with Vivit will be held at SpringHill Suites Easton Area Columbus. Come have breakfast on us!

Join our Vivit Ohio Vivit Local User Group and Micro Focus for discussion about the latest innovations in artificial intelligence and machine learning as they relate to quality assurance and functional testing, and how they will address and solve the continuous delivery issues facing the software industry today. The event, hosted by Micro Focus in partnership with Vivit will be held at Springhill Suites & Townhouse Suites in Columbus. Come have breakfast on us!

Join our Vivit Arizona Vivit Local User Group and Micro Focus for dinner and discussion about the latest innovations in artificial intelligence and machine learning as they relate to quality assurance and functional testing, and how they will address and solve the continuous delivery issues facing the software industry today. The event, hosted by Micro Focus in partnership with Vivit will be held at The Capital Grille in Phoenix. We will also have a prize drawing for a HP Sprocket photo printer. You don't want to miss this incredible event.

Some attacks may still slip "under the radar" though, which is why tools that leverage machine-learning, like User and Entity Behavior Analytics (UEBA), are an important support to your SIEM as they will detect more unusual threats as well as greatly increase the overall fidelity of your security alerts. SIEM and UEBA are further supported by threat hunting tools that enable your hunt teams to track down any other threats that may still be lurking in your system. All three approaches are important to your threat detection and response ecosystem. Micro Focus is a global software company with 40 years of experience in delivering and supporting enterprise software solutions that help customers innovate faster with lower risk. Our portfolio enables our 20,000 customers to build, operate, and secure the applications and IT systems that meet the challenges of change.

Rob Roy, public sector chief technology officer at Micro Focus Government Solutions, has said machine learning and cloud platforms could help government agencies protect their networks from cybersecurity breaches and achieve efficiency. Roy wrote how unsupervised machine learning could assist agencies in detecting anomalous user behavior. "Unlike the rules-based approach, unsupervised machine learning lets the technology develop an understanding of how the network's users typically behave and alert administrators when something abnormal occurs, increasing the likelihood that a rogue event is detected and a response is orchestrated at machine speed," he added. He said data scientists could help agencies sort through raw data and determine relevant information to analyze in order to address a specific problem. He also mentioned the potential benefits of migrating common business-oriented language-based mainframe applications and other legacy systems running mission-critical functions to the cloud.

There is a pernicious myth floating around. It's that rule-based Security Information and Event Management (SIEM) is old technology, and is no longer worth using today. It's that modern attacks can bypass rule-based SIEMs. This is partly true, but mostly false. There are large, older companies out there that don't use SIEMs to defend their data, and they do so at their own risk.