AI on IBM Z

AI-powered innovation to fuel business growth

What's next for mainframes and AI? Learn about Telum and Spyre
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Unlock AI insights and securely run gen AI

Transactional AI on IBM Z embeds real-time predictive AI directly into transaction systems and enables further optimization with agentic and generative AI.

By using the advanced hardware and software stack of IBM z17™, businesses can scale multiple AI models to power predictive use cases such as fraud detection and insurance claims processing. Spyre Accelerator on IBM Z is designed to enable generative AI (gen AI) and agentic AI capabilities on a secure on-prem system. With high performance, low latency, and industry-leading cyber resilience, IBM® Z is designed for mission-critical AI.
Discover AI in banking automation
Get real-time insights when needed

Infuse AI into every transaction without data movement while meeting stringent service level agreements (SLAs) and response times.
Keep data secure and compliant

Run AI where your data resides to protect sensitive information and meet regulatory requirements.
Scale seamlessly with transaction volume

With IBM z17, process up to 450 billion inference operations per day with 1 ms response time for real-time use cases.1
Boost inference throughput

Route inference requests to any idle Integrated Accelerator for AI to boost throughput up to 7.5x over IBM z16.2

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

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Generative AI and agentic AI

IBM watsonx Assistant for Z delivers secure, AI-powered virtual agents at scale on IBM Z for smarter customer interactions and agentic workflows.

 IBM watsonx Assistant for Z
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Transactional AI

Machine Learning for IBM z/OS allows users to deploy machine learning models within transactional applications for real-time insights while maintaining SLAs.

 Machine learning for IBM z/OS
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Enterprise open-source frameworks

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.

 AI Toolkit for IBM Z
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AI-powered semantic analysis in Db2

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.

 IBM SQL Data Insights Pro

Related software

AI Optimizer for Z
IBM AI Optimizer for Z delivers high‑performance, policy‑driven AI inferencing directly on IBM Z, engineered to meet the demands of GenAI at enterprise scale.
AI-powered IT operations management
IBM Concert for Z enables anomaly detection, smart event correlation, and expert advice through a unified user interface.
AI-driven threat detection
IBM zSecure Detection brings together threat monitoring, network insights, AI-driven access anomaly detection, and automated response capabilities to help organizations identify suspicious activity, contain threats, and strengthen cyber resilience across IBM Z.
Gen AI for DevOps
IBM Bob Premium Package for Z accelerates mainframe application development and modernization with generative AI and automation.
Python AI toolkit
Python AI Toolkit for IBM z/OS provides open-source tools to run AI and ML workloads.
In-memory analytics engine
IBM Z Platform for Apache Spark enables high-performance in-memory analytics with Java, Scala, Python, and R.
ONNX model compiler
IBM Z Deep Learning Compiler runs ONNX AI models as optimized libraries using the Integrated Accelerator for AI.
Artificial training data
IBM Synthetic Data Sets is a family of artificially generated datasets designed to enhance predictive AI model training and LLMs.

Resources

How mainframes are rewriting the AI playbook
Learn about the key elements of current and next-generation mainframes and how they are transforming the AI landscape.
Mainframes as mainstays of digital transformation
Discover how mainframes are more relevant than ever for hybrid cloud optimization, AI innovation and digital transformation.
AI on IBM Z Applications and Examples
Learn how to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform.
What if IBM Z might help stop fraud?
Discover low-latency AI on a highly trustworthy and secure enterprise system: the modernized IBM Mainframe.
Take the next step

Discover how to use AI and machine learning to convert data from every transaction into real-time insights. 

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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.