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Yahoo
10-04-2025
- Business
- Yahoo
IBM's AI Mainframe Will Boost Revenue This Year
While International Business Machines (NYSE: IBM) generates most of its revenue from software and consulting services, the company's hardware business is still an important piece of the puzzle. IBM's mainframe systems, known for their extreme reliability, remain a workhorse in certain industries. Of the world's 50 top banks, 43 use IBM's mainframes to handle mission-critical workloads. Every two to three years, IBM refreshes its mainframe lineup with a new model that brings improved performance and expanded capabilities. IBM works with its clients to push the mainframe in the right direction, and lately, that direction has been toward artificial intelligence (AI). IBM announced its latest mainframe system, the z17, on Tuesday. The z17 is powered by the IBM Telum II processor, which the company detailed last year. In addition to general performance improvements over its predecessor, the Telum II features an on-chip AI accelerator capable of churning through 450 billion AI inferencing operations per day. Response times are around one millisecond, making the system ideal for use cases that need near-instant results. One example IBM noted was running a credit card fraud-detection model in real time as transactions are being processed. On top of the AI capabilities of the Telum II processor, IBM plans to launch its Spyre Accelerator in the fourth quarter of this year. Spyre is an AI expansion card that can be plugged into the z17 to provide more computational horsepower. With Spyre, clients will be able to make use of AI assistants and agents built on IBM's Granite models, bringing generative AI to the mainframe. Each time IBM launches a new mainframe system, sales temporarily boom as clients upgrade from older models. The z16, which is nearly three years old at this point, delivered a strong product cycle for IBM. As of the end of the fourth quarter of 2024, the z16 was the most successful mainframe cycle in company history. In terms of MIPS, a metric IBM uses to measure a mainframe system's processing power, the z16 install base increased by about 30% over its predecessor. The z17 launches in June, so IBM will see a meaningful increase in mainframe revenue during the second half of the year. In the third quarter of 2022, the first full quarter of z16 availability, mainframe revenue soared 88% year over year. IBM doesn't break out mainframe revenue directly, but hybrid infrastructure, which includes mainframes and other hardware products, generated revenue of $8.9 billion in 2024. Beyond an increase in hardware sales, the new mainframe can drive software and consulting sales, particularly related to AI. IBM has booked more than $5 billion worth of generative AI-related business so far, and the bulk of that came from consulting signings. As mainframe clients upgrade to the AI-enabled z17, other parts of IBM could get a boost. The new mainframe is one reason IBM was able to guide for revenue growth of more than 5% this year, an acceleration, compared to 2024. Achieving that outlook could prove challenging, considering the recent U.S. tariffs and the potential for a broad economic slowdown. However, IBM's mainframes are mission-critical systems, and the z17 delivers AI capabilities that are likely to be in demand from its clients. With the z17, IBM continues to evolve the mainframe and maintain its relevance. With a focus on AI, the z17 should drive another strong mainframe cycle for IBM. Before you buy stock in International Business Machines, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and International Business Machines wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $461,558!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $578,035!* Now, it's worth noting Stock Advisor's total average return is 730% — a market-crushing outperformance compared to 147% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of April 5, 2025 Timothy Green has positions in International Business Machines. The Motley Fool has positions in and recommends International Business Machines. The Motley Fool has a disclosure policy. IBM's AI Mainframe Will Boost Revenue This Year was originally published by The Motley Fool Sign in to access your portfolio
Forbes
10-04-2025
- Business
- Forbes
Do Mainframes Have A Role In The AI Era?
AI-Generated, AI-Enabled Mainframe Francis Sideco A couple of years after generative AI first entered mainstream consciousness, every industry segment is attempting to leverage it to improve efficiency and offer new products and services. While training will continue to evolve and drive innovation, inferencing will drive value creation through advanced AI capabilities such as chain of thought reasoning, multi-modal functionality and multi-model support combining different types of generative AI models with predictive AI. Most of the conversations on delivering these inferencing solutions gravitate around AI data centers, edge infrastructure, and/or on-device processing. This begs the question: Does the mainframe have a role in the AI Era? What Is A Mainframe? While servers are designed more for supporting general-purpose applications and multiple clients or functions like website hosting and email servers, mainframes are designed for high-volume, mission-critical tasks such as financial transaction processing and are often used in heavily regulated industries. As such, mainframes require a higher degree of capacity, reliability and security enabled with advanced virtualization, disaster recovery, backwards compatibility and built-in redundancy. Additionally, workloads are typically handled by a centralized mainframe system whereas a distributed architecture to spread workloads over many systems is commonly used in a server architecture. With the capacity, reliability and security that mainframes provide along with their ubiquity in supporting high-volume, high-value transactions and data processing, the answer to whether mainframes have a role in the AI Era is an unequivocal 'Yes!' IBM, the leader in mainframe solutions with 70% of all global financial transactions going through their mainframes, is a prime example. A Mainframe For The AI Era Telum II By The Numbers Francis Sideco IBM recently announced the latest in its Z family of mainframes, the Z17, with the goal of addressing the needs of the AI Era while still delivering on the rigorous expectations associated with mainframes. According to IBM, this Z17 generation is powered by its 5nm 5.5GHz Telum II CPU, which, compared to the previous generation, delivers an 11% increase in single-thread performance, up to 20% capacity expansion and up to 64 TB of memory, while also doing so with up to 27% power reduction. Additionally, Telum II has an enhanced on-board AI accelerator capable of predictive and some generative AI workloads. For the generative AI workloads that require more acceleration, the Z17 can also be upgraded with the new Spyre Accelerator PCIe card. Spyre Accelerator By The Numbers Francis Sideco Based on IBMs reported performance numbers, the Z17 provides 7.5x more AI throughput than the Z16 generation delivering up to 450 billion AI inferences with 1ms response times per day. What AI Workloads Need A Mainframe? Due to their heavy use in financial transactions and mission-critical data processing, mainframes are most effective when using a combination of predictive and generative AI models. For example, because of the high-volume, central processing, and multi-model capabilities, mainframes can effectively and efficiently analyze patterns from the transactions and data passing through the system and infer conclusions that can be used in advanced fraud detection and anti-money laundering applications for improved accuracy and fewer false positives. Mainframes also combine these capabilities with mission-critical business data to help enable business, code and operations assistants to increase productivity and reduce the time needed for skills training, and autonomous agentic AI applications like automated trading and healthcare applications. Other areas where AI-enabled mainframes are being used include, but are not limited tom loan risk mitigation, insurance claims fraud detection and prevention, payments fraud, geospatial analysis, climate change impact, loan risk mitigation, cybersecurity and sentiment analysis. These are just a small subset of applications where predictive, generative and even agentic AI leverage the mainframe for business outcomes that would otherwise be inefficient or not available because of the data and/or security requirements on standard server configurations especially in heavily regulated industries in which mainframes are typically deployed. The Future Of Mainframes In The AI Era According to IBM, there are already more than 250 client-identified AI use cases on the Z mainframe platform and growing. But it's not all about the hardware. IBM leverages its other AI assets like watsonx, Granite, InstructLab and even their consulting services, across IBMs solutions, including the Z platform, positioning the company as a strong partner for the age of enterprise AI. Competitors such as Dell, Fujitsu, and Unisys are also looking to leverage AI for mainframe workloads. Next generation mainframe development typically takes 5-7 years and if they're anything like IBM, it is safe to say that the next few generations of AI-enabled mainframes are already in the works. Not only are mainframes surviving in the AI Era, they are thriving.
Forbes
08-04-2025
- Business
- Forbes
AI Meets The Mainframe: Inside IBM's Bold Z17 Bet
IBM z17 Mainframe IBM recently introduced the z17, its latest generation enterprise mainframe system, powered by the new Telum II processor. The z17 offers significant performance gains over previous generations and integrates artificial intelligence with traditional mainframe capabilities. At the core of the z17 is IBM's Telum II processor, a second-generation chip that features eight 5.5 GHz cores and 360MB of on-chip cache and an embedded AI accelerator. The new processor enables the system to perform more than 450 billion AI inferencing operations per day, achieving latency as low as one millisecond. According to IBM, the z17 delivers 50% more AI inference capacity than its predecessor, the z16, while preserving the performance, security, and reliability for which the mainframe is known. Beyond its traditional mainframe attributes, the z17's ability to run generative AI workloads directly on the mainframe sets it apart. The Spyre Accelerator, expected to be available in Q4 2025, will make this possible. The Spyre Accelerator is a PCIe-based card that enables native support for large language models and other advanced AI applications. This eliminates reliance on external GPUs or cloud services. Both the Tellum II processor and Spyre accelerator were first detailed at the 2024 Hot Chips conference. IBM Tellum II (left) and Spyre (right) Processors By keeping AI workloads on-premises, businesses gain greater control over sensitive data, reduce architectural complexity, and achieve faster, more secure processing. This approach is particularly valuable in industries with strict regulatory requirements and high-security standards, such as banking, healthcare, and government. The z17 is also deeply integrated with IBM's watsonx platform, including tools like watsonx Code Assistant for Z and watsonx Assistant for Z. These AI-driven tools support the modernization of legacy COBOL applications by simplifying code maintenance, accelerating refactoring efforts, and lowering the learning curve for new developers. This increases development speed and improves consistency across enterprise systems. Beyond its AI capabilities, the z17 maintains the fundamental qualities that have defined the mainframe for decades. It offers built-in high availability through fault-tolerant design and advanced error detection, ensuring uninterrupted operations. Security remains a cornerstone of the platform, with end-to-end encryption and support for confidential computing that protects data while it is being used, not just during storage or transit. To complement the z17, IBM introduced z/OS 3.2, its AI-optimized operating system that supports hybrid cloud integration, NoSQL databases, and hardware-accelerated AI processing. Operational management is enhanced through IBM Z Operations Unite, which uses OpenTelemetry to unify and streamline observability and incident response. Security also sees a major upgrade with IBM Vault, based on HashiCorp's secrets management technology, now offering unified identity-based security for secrets, certificates, and tokens across both mainframe and hybrid environments. IBM's acquisition of HashiCorp was completed earlier this year. IBM backs the launch with expanded lifecycle support services and new AI-powered customer service tools like IBM Agent Assist, helping clients manage critical workloads with maximum uptime and resilience. Mainframes continue to serve as the backbone of industries where uptime, throughput, and security are non-negotiable. Sectors like financial services, healthcare, insurance, and public infrastructure still rely heavily on mainframe systems for their most critical workloads. In today's environment—characterized by rising cloud costs, heightened privacy concerns, and increasing interest in AI-enabled decision-making—many enterprises are reconsidering the value of maintaining secure, on-premises infrastructure. A recent IBM-sponsored survey found that 78% of global IT executives consider the mainframe central to their digital transformation strategies, while 88% consider application modernization a key priority. The z17 arrives when enterprises are under growing pressure to derive more value from existing data assets while improving security posture and managing talent shortages. IBM's positioning of the z17 as an AI-native mainframe—not a relic of the past but a platform for future innovation—aligns with these emerging business needs. By enabling AI directly on the platform, IBM reduces the need to offload sensitive data to external environments for analysis. This reduces security risks and latency, while also sidestepping the increasing difficulty of sourcing GPU capacity for enterprise AI workloads. While companies like Nvidia dominate the GPU market and cloud providers such as AWS, Microsoft Azure, and Google Cloud lead the AI services space, IBM is carving out a different path. With the z17, IBM offers an on-premises, vertically integrated solution tailored for industries that demand regulatory compliance, data control, and uninterrupted operations. This strategy gives IBM a unique position in the evolving AI infrastructure landscape. Despite lingering perceptions of the mainframe as outdated or complex, IBM is actively working to change that narrative. New AI-powered tools, along with low-code development environments and modern IDEs, are helping reduce complexity and make the platform more accessible to a new generation of developers. The z17 is also central to IBM's hybrid cloud vision. Though not cloud-native in the strictest sense, it integrates with Red Hat OpenShift and supports modern DevOps pipelines. Combined with advanced observability tools and AI-assisted development environments, the z17 complements, rather than competes with, cloud-native infrastructure. For organizations that require scalable, secure, and resilient infrastructure, the mainframe remains relevant and essential.
