AI-powered innovation to fuel business growth
Infuse AI into every transaction without data movement while meeting stringent service level agreements (SLAs) and response times.
Run AI where your data resides to protect sensitive information and meet regulatory requirements.
With IBM z17, process up to 450 billion inference operations per day with 1 ms response time for real-time use cases.1
Route inference requests to any idle Integrated Accelerator for AI to boost throughput up to 7.5x over IBM z16.2
Platform Transformation with AI for IBM Z
Explore our roadmap for the AI capabilities of IBM Z — production-ready function, emerging innovations, and a hybrid architecture built to run key AI workloads directly alongside mission-critical applications. This plan reflects continued momentum in delivering AI capabilities that extend the value of mission-critical applications and the teams that run them — positioning IBM Z as an integral and strategic part of how organizations build, deploy, and govern AI at scale.
| 2026 and earlier Trusted Enterprise AI | 2027 Expanding capabilities and ecosystem depth | 2028 and beyond Next-generation platforms & self-correcting AI |
| Real-time decisioning and governed AI lifecycle at the source Inference co-located with enterprise applications and data inside the governance boundary — classical ML through LLMs and embedding models on the Spyre Accelerator. MLOps and optimized open-source frameworks span the model lifecycle; AI-enhanced SQL adds similarity search and anomaly detection to Db2 for z/OS. Explore MLz Build AI on Z & LinuxONE See Red Hat OpenShift AI on IBM Z Accelerate Insights with SQL Data Insights Pro | Expanded data intelligence and high-value use cases A growing ecosystem of use cases on Spyre — semantic search, anomaly detection, and real-time decisioning driven by efficient, task-optimized LLM-based models — preserving data sovereignty and low-latency data access. Preview the future direction of Spyre | Agentic AI at enterprise scale — accessible across the business Pre-built domain agents, self-service deployment, and a growing ecosystem put agentic AI within reach of enterprise practitioners — with governance and data sovereignty maintained as agents act on the platform’s most sensitive data. |
| AI-native operations — from the OS up to the enterprise agent Simplified configuration and agentic system-health diagnosis boost productivity and accelerate triage. A deep operations agent reasons, plans, and remediates across multiple steps, with human approval throughout. AI-assisted development adds agentic automation, architectural impact analysis, and automated code refactoring. Meet watsonx Assistant for Z Discover Project Polaris Build with IBM Bob Premium Package for Z | Full-stack AI management for system operations teams System discovery through expanded z/OS APIs feeds platform-level intelligence — driving automated workload assessment, AI-generated remediation plans, and change orchestration validated in pre-production before reaching production. Navigate with IBM Z Atlas | Self-assessing, self-correcting operations Policy-driven agents continuously tune, remediate, and enforce compliance against defined targets, with human oversight. The platform manages its own operational health, broadly simplifying configuration and software management. |
| On-platform AI acceleration and a simplified path to production On-chip and attached acceleration delivers AI at transaction speed, co-located with mission-critical data inside the security boundary — in multi-frame, single-frame, and rack-mount configurations, with one integrated software appliance for simplified deployment. Power AI with z17, LinuxONE 5, Telum II & Spyre Optimize AI Workloads on Z | Expanding the AI model ecosystem on-platform Native integration with industry-standard AI frameworks enables open-source LLMs and automated model onboarding without changing developer toolchains. Intent-driven, Terraform-based infrastructure automation takes a simulate-first approach, so teams validate changes before production. Run PyTorch Natively on Spyre Simplify Terraform for Z | Next-generation inference and a dual-architecture platform Next-gen on-platform inferencing and a dual-architecture processor bringing the Arm software ecosystem natively to IBM Z — designed to support demanding enterprise AI workloads. Learn about IBM’s Dual-Architecture Processor |
Statements regarding IBM’s future direction and intent are subject to change or withdrawal without notice and represent goals and objectives only.
Use cases
Generative AI and Agentic AI with Spyre Accelerator
Increase productivity with agentic AI
Employee autonomy is enhanced by simplifying access to information and automating routine tasks with agentic AI.
Minimize the learning curve for IBM Z professionals
Faster onboarding and knowledge transfer for IBM Z users is enabled, reducing reliance on experts and enhancing workflows for experienced users.
Secure gen AI behind your firewall
Generative AI can run securely on-premises with Spyre™cards, ensuring privacy, compliance and complete control over operations.
Transactional AI with Telum
Anti-money laundering
A multiple AI model approach on IBM z17 accelerates AML efforts, improves accuracy and streamlines compliance.
Insurance claims processing
Combining encoder large language models (LLMs) with predictive AI creates a faster, more efficient claims process and improves service quality.
Real-time fraud detection
Fraudulent transactions can be detected instantly by deploying AI models in transactions on IBM z17 with Machine Learning for IBM z/OS, reducing risk and saving costs.
Featured products
IBM watsonx Assistant for Z delivers secure, AI-powered virtual agents at scale on IBM Z for smarter customer interactions and agentic workflows.
Machine Learning for IBM z/OS allows users to deploy machine learning models within transactional applications for real-time insights while maintaining SLAs.
AI Toolkit for IBM Z is a family of supported open source AI frameworks optimized for the Telum processor and use on-chip AI acceleration in IBM z16® and z17 systems.
IBM SQL Data Insights Pro enables organizations to uncover patterns in structured data and unstructured text in Db2 for z/OS – directly where their enterprise IBM Z data resides.
Related software
Resources
Learn about the key elements of current and next-generation mainframes and how they are transforming the AI landscape.
Discover how mainframes are more relevant than ever for hybrid cloud optimization, AI innovation and digital transformation.
Learn how to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform.
Discover low-latency AI on a highly trustworthy and secure enterprise system: the modernized IBM Mainframe.
Footnotes
¹ DISCLAIMER: Performance result is extrapolated from IBM® internal tests running on IBM Systems Hardware of machine type 9175. The benchmark was executed with 1 thread performing local inference operations using a LSTM based synthetic Credit Card Fraud Detection model to exploit the Integrated Accelerator for AI. A batch size of 160 was used. IBM Systems Hardware configuration: 1 LPAR running Red Hat® Enterprise Linux® 9.4 with 6 IFLs (SMT), 128 GB memory. 1 LPAR with 2 CPs, 4 zIIPs and 256 GB memory running IBM z/OS® 3.1 with IBM z/OS Container Extensions (zCX) feature. Results may vary.
2 DISCLAIMER: Performance results are based on internal tests exploiting the IBM Integrated Accelerator for AI for inference operations on IBM z16 and z17. On IBM z17, each IBM Integrated Accelerator for AI allows any CPU within a drawer to direct AI inference request to any of the 8 idle AI accelerators on the same drawer. The tests involved running inference operations on 8 parallel threads with batch size of 1. Both IBM z16 and z17 were configured with 2 GCPs, 4 zIIPs with SMT and 256 GB memory on IBM z/OS V3R1 with IBM Z Deep Learning Compiler 4.3.0, using a synthetic credit card fraud detection model. Results may vary.
