The Role of AI in Application Modernization
As enterprises embrace digital transformation, AI is reshaping application modernization by automating complex tasks, optimizing cloud migrations, and enhancing operational efficiency. Organizations are leveraging AI-driven tools to refactor legacy applications, migrate workloads, and improve scalability, yet one critical challenge remains: accessing legacy mainframe data.
Mainframes continue to store the most valuable enterprise data, powering core business operations in banking, insurance, healthcare, and government sectors. While AI-based solutions can modernize applications, they often fail to seamlessly integrate with mainframe data — leading to stalled projects, increased costs, and inefficient data pipelines.
VirtualZ Computing solves this challenge by enabling real-time, secure access to mainframe data for application modernization projects — without replication, transformation, or traditional ETL (Extract, Transform, Load) processes. While VirtualZ does not develop AI solutions or modernize applications directly, we eliminate one of the biggest bottlenecks in modernization: ensuring reliable, secure, and efficient access to mainframe data.
Key Trends in AI for Application Modernization
Organizations are increasingly using AI to accelerate application modernization. Here are some of the top trends:
- AI-Driven Code Refactoring and Modernization
AI-powered tools are automating the conversion of legacy programming languages like COBOL, PL/I, and RPG into modern alternatives such as Java, Python, and C#. These tools analyze legacy applications, identify redundant code, and suggest optimizations, enabling faster modernization with reduced manual effort. - AI-Powered Application Migration
Enterprises rely on AI to determine the best migration paths, assessing dependencies, workloads, and business-critical processes. By evaluating which applications can move to the cloud and which should remain on-premises, AI reduces migration risks and infrastructure costs. - AI-Enabled Cloud-Native Development
As organizations move toward microservices architectures and cloud-native frameworks, AI is helping automate deployment, security enhancements, and performance monitoring. AI-driven DevOps tools streamline infrastructure provisioning, CI/CD pipelines, and runtime optimization, making cloud adoption faster and more efficient. - AI for Automated Testing and Validation
Machine learning models are now being used to predict application failures, automate regression testing, and validate functionality post-modernization. By minimizing manual testing, organizations reduce development cycles and improve software quality. - AI-Powered Data Analytics and Decision-Making
Beyond application modernization, AI is unlocking predictive analytics, business intelligence, and AI/ML model training. Enterprises are increasingly looking to integrate real-time mainframe data with cloud-based AI platforms to drive better decision-making and improve customer experiences.
The Biggest Roadblock to AI-Driven Modernization: Mainframe Data Access
Despite advancements in AI, modernization projects still struggle with mainframe data access. Many mission-critical applications rely on mainframe data, but connecting this data to cloud-based AI solutions remains one of the most significant challenges in digital transformation.
Traditional approaches like ETL (Extract, Transform, Load) and Change Data Capture (CDC) introduce:
- High costs and complexity: Custom coding, middleware, and manual tuning inflate costs.
- Performance degradation: Mainframe CPU and I/O resources are consumed by data extraction.
- Security and compliance risks: Data replication increases exposure to breaches and compliance violations.
- Data latency issues: AI and analytics require real-time data, but batch-based CDC processes create delays.
These challenges make it difficult for AI-powered applications to seamlessly interact with mainframe data in real time, leading to inefficiencies and stalled modernization initiatives.
How VirtualZ Enables AI-Driven Application Modernization
VirtualZ Computing does not develop AI solutions or modernize applications, but we provide a crucial missing piece — real-time, secure access to mainframe data, eliminating the biggest barrier to AI-driven modernization.
With Lozen™, PropelZ™, and Zaac™, enterprises can integrate mainframe data directly into AI, cloud, and analytics applications without replication, ETL pipelines, or CDC solutions.
- Lozen: Real-Time, Read-Write Data Access for Modern Applications
- Enables modernized applications to read and write mainframe data in real time without moving or duplicating the data.
- Allows AI-powered tools to maintain seamless access to live mainframe data after migration.
- Eliminates the need for costly ETL and CDC solutions.
- Keeps mainframe data secure without unnecessary duplication.
- PropelZ: No-Code Data Access for AI and Cloud Analytics
- Provides one-way, no-code mainframe data access to cloud-based AI, analytics, and data lakes.
- Enables AI and analytics applications to use real-time mainframe data without extensive integration work.
- Reduces cloud infrastructure costs by eliminating redundant storage.
- Supports seamless integration with cloud platforms like AWS, Azure, and Google Cloud.
- Zaac: Cost-Effective Mainframe Storage for AI Workloads
- Allows enterprises to store and retrieve mainframe data in hybrid cloud environments without expensive storage infrastructure.
- Provides AI-driven analytics and machine learning models with efficient access to historical mainframe data.
- Ensures compliance and security with encrypted storage options.
- Reduces costs by leveraging cloud storage instead of traditional DASD or tape.
Key Benefits of VirtualZ Computing for AI-Powered Modernization
By enabling seamless mainframe data access, VirtualZ helps enterprises:
- Accelerate AI-driven application modernization by allowing AI tools to access live data without ETL pipelines.
- Reduce costs by eliminating expensive CDC solutions and manual data replication.
- Enhance security by keeping data on IBM Z, minimizing exposure to breaches.
- Enable real-time AI and analytics by allowing AI models to work with live, up-to-date mainframe data instead of stale copies.
- Simplify cloud adoption by supporting direct integration with AWS, Azure, Google Cloud, and Snowflake.
Conclusion: AI-Driven Modernization Requires Seamless Data Access
AI is transforming how enterprises modernize applications, but legacy data access remains a major roadblock. Traditional ETL and CDC solutions introduce unnecessary costs, complexity, and delays, holding back enterprises from fully leveraging AI-powered transformation.
VirtualZ Computing removes this barrier by providing real-time, seamless access to mainframe data, ensuring AI-driven modernization efforts succeed without costly replication or performance trade-offs.
For IT leaders and AI teams looking to accelerate application modernization, reduce costs, and unlock the full potential of AI, the answer is clear: Unlock the power of mainframe data — without replication, transformation, or complexity — with VirtualZ Computing.
Learn More
- Learn more about our Application Modernization solution.
- Watch demos of Lozen, PropelZ, and Zaac.
- Try Lozen, PropelZ, and Zaac.
- Review all VirtualZ Solutions.
- Explore our Thought Leadership papers, YouTube channel, podcasts, and blog.
- Still have questions? Contact us.