Since its inception in 1988, the IBM i (formerly AS400, iSeries) platform has been renowned for its legendary reliability and uptime, particularly in sectors with high-volume workflows such as retail, manufacturing, finance, and logistics. Many of these longstanding systems remain in place today, and maintain the critical operations that power customer experiences all over the globe.

However, it’s this same longstanding history that tends to give the platform a bad rap. Many misconstrue the platform as outdated or legacy, and frankly, decades of existing code – and a classic green screen UI – can certainly make it seem like this is the case.

This doesn’t pair well with the rapidly evolving IT landscape in 2026. As technology leaders everywhere feel the pressure to modernize, many are looking to their trusty green screen systems and questioning whether they measure up to modern advances in cloud, AI, analytics, and customer experience. As a result, many feel constrained to migrate off the platform, but this doesn’t have to be the case.

IBM i has grown with the times, and offers more ways than ever before to remain agile and competitive in the age of AI. Before you decide to leave IBM i behind, let’s explore a few ways to modernize that are much easier, safer, and cost-effective than a complete platform migration.

IBM i, Cloud Integration, & Hybrid Architectures

One of the top ways enterprises are extending their core IBM i systems is through cloud computing and hybrid architectures. By selectively migrating certain processes to the cloud, businesses can modernize while maintaining the control and reliability of on-premises setups. In practice, this approach opens the doors to cloud-native technologies while still offering a secure, private environment for sensitive or intensive workloads.

In the context of modern use cases, many leaders are leveraging hybrid architectures to prepare the groundwork for machine learning (ML) and artificial intelligence (AI) while preserving core workflows and logic. In other words, this approach can be ideal for achieving AI readiness while minimizing disruption to the critical workloads that run the business.

The benefits of cloud computing don’t stop there. Common use cases for IBM i include many modern capabilities, such as:

• Testing and Development: Hybrid architectures can support DevOps processes, CI/CD pipelines, and other cloud-native advancements (i.e. microservices, serverless computing, and containerization) for expedited testing and development.
• Big Data Analytics: Major cloud providers offer scalable cloud storage on demand, as well as offer analysis services tailored for vast and/or complex data pools.
• Disaster Recovery (DR) and Backup: Cloud-based backup and recovery offers a cost-effective alternative to a traditional DR site due to remote storage and automated backup options.
• Frontend Services: Frontend cloud services seamlessly integrate with your on-prem backend, offer support for developer tools, and provide flexible performance that scales automatically during traffic spikes.

Rather than migrating your entire platform to the cloud, hybrid models allow IT leaders to precisely target the areas where operations are backed up or outdated. This tailored approach adds a layer of flexibility on top of existing systems, allowing businesses to leverage cloud capabilities only where they offer the greatest operational advantage.

APIs & Integration

For the demands of today, the ability to connect and move data seamlessly has become a competitive necessity. Well-organized, accessible data is crucial for modern business intelligence, reporting, and real-time updates, which not only impacts internal processes and strategy, but also directly influences the way your business interacts with your customer base. Brands that can’t deliver timely updates or a modern user experience can quickly find themselves losing customers to competitors.

As a result, recent trends for IBM i modernization have become increasingly focused on bridging the gap between legacy data and contemporary platforms. APIs and integration technologies accomplish just that, transforming IBM i from an isolated system into a fully connected platform that powers web, mobile, and cloud applications.

APIs serve as the primary mechanism for exposing IBM i data to other applications.

APIs provide a direct interface through exposing existing IBM i logic (i.e. RPG, COBOL, or DB2) for various web, mobile, and SaaS applications. Meaning, instead of rebuilding rules from scratch, a new application can simply call the API to execute your existing business logic.

While APIs provide a standardized interface, integration ensures that IBM i can participate in various workflows across your enterprise.

Integration tools and middleware allow IBM i to communicate with other applications, synchronize data across systems, and customize and manage complex business processes in real time.

So, what does adopting APIs and integration really mean in practice? The real-time data access from APIs and integrations remove the bottlenecks of nightly batch jobs, but in a broader sense, also allow teams to make more informed decisions with the most up-to-date information possible. Through APIs, organizations can deliver new applications quickly (not to mention with a more modern, intuitive UI), without the cost, risk, or disruption of rewriting proven code. Additionally, integration can enable tailored, end-to-end automation that greatly reduces manual effort and human error across your organization.

This highly customizable method of modernization is nothing short of a game changer for multigenerational IBM i/AS400 systems. As you think about next steps, consider talking to an experienced IBM i advisor who can recommend the best path forward to realizing both your immediate and long-term goals.

AI & Intelligent Automation

While enterprises everywhere are looking to incorporate AI into their business, there are many more that still feel AI adoption is out of reach. This feeling is especially reflected in longtime users of the IBM i/AS400 platform, who often see their most valuable data locked inside legacy systems, siloed platforms, and infrastructure that was never designed for AI.

However, modernization with AI is more than possible for IBM i – and with the right implementation partners, companies can hire teams that know how to cut costs and risk at every step. Not only is it practical to extend your IBM i system’s capabilities with AI, ML, and other similar tools, but it has become an imperative next step in the era of intelligent automation and foresight.

Similar to its cloud and API strategies, IBM has heavily invested in long-term support for AI on IBM i. With these advancements, users are using AI as a means to enhance their platform, rather than replace it. A few key use cases include:

Intelligent Assistants and Agentic AI: AI-driven decision support analyzes IBM i data in real time to surface insights, recommend actions, and flag anomalies.

Example: Finance teams can detect unusual transaction activity before it becomes a compliance or risk issue.

Advanced Analytics and Forecasting: Predictive models transform historical and real-time IBM i data into visual insights, helping organizations identify trends or forecast demand in a way that traditional reporting cannot easily detect.

Example: Logistics organizations can use enterprise-wide data to anticipate shipping delays or capacity constraints.

Automation and Operational Efficiency: Automated workflows for approvals, notifications, exception handling, and data validation can drastically reduce manual effort within your organization.

Example: Customer service teams can rely on automated systems that monitor orders, account data, and FAQs, as well as automatically trigger alerts for exceptions or unusual activity.

Developer Productivity: Intelligent tools assist with code analysis, documentation, testing, and modernization, allowing developer teams to move faster, reduce technical debt, and even provide reliable cross-language support.

Example: Cross-language support allows developers to see how changes in RPG code impact connected Java or .NET services, helping them update systems safely without breaking integrations.

AI and automation enhance IBM i by adding significant efficiency and flexibility to your operations. By making your data accessible to IBM i, organizations can introduce modern capabilities while continuing to rely on a proven and trusted foundation.

Looking Ahead

In the race to modernize, IBM i can often be misconstrued as a legacy system that can’t adapt to modern demands. However, there are plenty of modern examples that show that “rip and replace” isn’t the only path forward.

Extending the reach, lifespan, and capabilities of your IBM i system is more feasible than ever before, and more tools and modernization frameworks are being developed daily. Finding the right modernization partner is critical, as the right guidance can help you prioritize initiatives, avoid unnecessary risk, and strategically fill skill gaps where needed.

Regardless of the state of your current platform, with thoughtful, practical modernization, you can achieve the best of both worlds – preserving decades of reliable systems while embracing the agility and innovation of what’s next.

Have a modernization project on the horizon? Contact us here to connect with the world’s largest IBM i team.