List of IBM Z AI Infrastructure Customers
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Since 2010, our global team of researchers has been studying IBM Z AI Infrastructure customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased IBM Z AI Infrastructure for AI infrastructure from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using IBM Z AI Infrastructure for AI infrastructure include: Ibm, a United States based Professional Services organisation with 288300 employees and revenues of $60.53 billion, Garanti BBVA, a Turkey based Banking and Financial Services organisation with 22724 employees and revenues of $19.56 billion, M&T Bank, a United States based Banking and Financial Services organisation with 22080 employees and revenues of $9.23 billion and many others.
Contact us if you need a completed and verified list of companies using IBM Z AI Infrastructure, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Garanti BBVA | Banking and Financial Services | 22724 | $19.6B | Turkey | IBM | IBM Z AI Infrastructure | AI infrastructure | 2024 | n/a |
In 2024, Garanti BBVA deployed IBM Z AI Infrastructure by implementing IBM Db2 Analytics Accelerator for z/OS on LinuxONE in Turkey to strengthen its AI infrastructure for analytics, reporting and ETL across core banking, risk and regulatory compliance workloads. The deployment targeted hybrid transactional analytic processing, enabling faster data preparation for analytics and AI and shifting analytic compute onto LinuxONE infrastructure while maintaining Db2 for z/OS as the transactional system.
The implementation instrumented IBM Db2 Analytics Accelerator for z/OS capabilities for query acceleration, HTAP style processing and ETL staging to shorten analytic query runtimes and streamline data pipelines used by reporting and model preparation. Configuration work focused on analytic workload offload, optimized data movement between z/OS and LinuxONE, and preparation of datasets for downstream AI and analytics workflows.
Operational coverage explicitly included core banking, risk and regulatory compliance workloads in Turkey, with the IBM Z AI Infrastructure integrated into the bank's mainframe data environment via Db2 on z/OS and LinuxONE deployment topology. The solution supported reporting, regulatory extracts and ETL flows that feed analytics and AI model training data sets across enterprise data consumers in those business functions.
Governance and workflow changes accompanied the rollout, with centralized analytic acceleration and revised ETL sequencing to exploit the IBM Z AI Infrastructure and Db2 Analytics Accelerator for z/OS acceleration layer. The engagement began in 2024 and produced explicit outcomes reported by the bank, including a regulatory report that previously required two days that now runs in about one minute, and mainframe CPU usage falling by roughly 45 hours per day.
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Ibm | Professional Services | 288300 | $60.5B | United States | IBM | IBM Z AI Infrastructure | AI infrastructure | 2024 | n/a |
In 2024, IBM's CIO Organization deployed IBM Z AI Infrastructure, implementing IBM watsonx Assistant for Z to simplify onboarding and automate mainframe IT operations in the United States. The deployment is in the AI infrastructure category and targeted incident analysis, patching and operational question and answer workflows for operations teams.
The implementation configured IBM watsonx Assistant for Z as an AI driven operational assistant embedded into mainframe workflows, providing automated incident triage, contextual operational Q and A, and orchestration for Db2 patching. Functional workstreams included knowledge ingestion from runbooks and operational documentation, conversational onboarding flows for new operators, and automation of patching steps to reduce manual intervention.
Rollout and governance were led by the IBM CIO Organization with a focus on United States mainframe operations and operations teams as primary users. Governance emphasized centralized content curation for the assistant and controlled provisioning of automation workflows, with staged operational onboarding to align operators and change control processes.
As reported by IBM the deployment in 2024 produced estimated outcomes including an 8% reduction in learning time, 10% faster incident resolution and a 50% decrease in Db2 patching time, outcomes attributed to IBM Z AI Infrastructure and IBM watsonx Assistant for Z. The IBM Z AI Infrastructure implementation consolidated AI infrastructure capabilities and conversational automation to streamline mainframe operational processes.
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M&T Bank | Banking and Financial Services | 22080 | $9.2B | United States | IBM | IBM Z AI Infrastructure | AI infrastructure | 2021 | n/a |
In 2021, M&T Bank deployed IBM Z AI Infrastructure to modernize z/OS application access and provision sub-second, self-service access to core deposit data for business analysts, data scientists and hybrid cloud applications in the United States. The implementation centered on the Z Digital Integration Hub pattern to expose mainframe data objects as directly consumable assets for downstream analytics and reporting workloads.
The deployment of IBM Z AI Infrastructure established real-time data access capabilities and integration points that make core deposit data available to data science workflows and hybrid cloud applications. The configuration emphasized low latency access, API driven consumption and direct data availability for model training and operational analytics, aligning with typical AI infrastructure functional requirements.
Operational coverage included business analytics, data science teams and hybrid cloud application stacks across the United States, with the pilot moving to production in 2021. Integrations were focused on z/OS application modernization and direct downstream consumption by analytics workloads rather than introducing new named third party systems.
Governance and rollout proceeded through a pilot to live path in 2021, with the implementation reducing data driven project timelines by about 40 percent and enabling real time decisioning as reported. AI and analytics infrastructure usage is inferred from the Z Digital Integration Hub making core data directly available to data scientists and downstream analytics workloads, supporting M&T Bank use cases for operational analytics and model orchestration.
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