IBMInternational Business Machines Corporation

“Our software book from an annualized revenue trailing 12 months, we finished last year at $30 billion, right? 80% of that, as I said earlier, high-value recurring revenue, 20% transactional. We did about $6 billion. Over the last trailing 12 months on an accelerating basis, our AI platform agents, assistance orchestration is north of $1.5 billion. It's already about 25% penetrated and our software business growing north of 40%. It's contributing 2 points of growth on an annualized basis.”

“We now see data up low 20-plus percent range. That's going to deliver 5 points of software growth. That's representative of new innovation GenAI, the value of our platform-centric model and strategic partnerships and then also M&A contribution from Confluent, which should be about a little bit north of 15 points of that 20% to 25% growth overall for the year.”

“Through disciplined execution, eliminating manual touch points, simplifying processes and applying data, automation and AI at scale, we have built a proven repeatable AI-enabled transformation engine that is accelerating. Since 2023, this has driven $4.5 billion of productivity savings, with an additional $1 billion expected in 2026.”

“We just anniversaried our first full year of z17. That first full year is z17 versus the prior program, z16 first full year, which, by the way, was the best on record at that point in time. We've increased hardware placement value by over $1 billion.”

“Consulting is about 40% of our signings, 30% of our backlog is GenAI now, over 20% of our revenue. And on an ARR revenue perspective, in the first quarter, we eclipsed $4 billion ARR.”

“Red Hat OpenShift accelerating $2 billion ARR virtualization, now north of [indiscernible] and consumption model returned back to expectation.”

“IBM Z delivers the lowest unit cost architecture at scale for workloads that require end-to-end encryption, continuous availability and ultra-high throughput. Clients rely on our Z platform to process billions of transactions reliably with 6 to 8 9s of availability. They run AI inferencing directly in line with those transactions. Our Spyre accelerator lets clients run AI on 100% of the transaction volume without moving data off platform, allowing them to embed AI directly into their transaction flows. Financial services clients are using this for real-time fraud detection, saving tens of millions of dollars.”

“As we have unlocked, Jim talked about the $4.5 billion of internal value, how do you reduce your total tax expense? How do you reduce procurement expense? How do you reduce accounts payable, how do you reduce [ quote to cash ] as we walk across these processes, we get a lot of knowledge on how to capture that into agents, but then we are not going to be fixated whichever model you want to use, you can use.”

“450 billion AI inferences at 1 millisecond of response time, 25 billion encryptions, transactions per day, up to eight 9s of availability, quantum-safe encryption and a TCO advantage running it on mainframe, on-prem versus the cloud anywhere from 3 to 15x depending on the size and complexity of that platform.”

“IBM Bob, our AI-based software development system, is now generally available. Our entire developer workforce is using Bob with average productivity gains of 45%. Bob automates the full software life cycle from legacy modernization to security using specialized agents and multimodal optimization.”

“In consulting, the quality of our backlog and momentum in GenAI with backlog penetration at about 30%, continue to support an acceleration in revenue growth to low to mid-single digits for the year.”

“Data revenue grew 16%, fueled by demand for our GenAI products, strengthen our strategic partnerships and inorganic contribution from data stack and Confluent, which closed in mid-March.”

“clients that have implemented watson Code assistant for Z, we're seeing 3x differential on growth and capacity, and you see in our distributed infrastructure, we're accelerating growth.”

“currently, I believe we have a fully populated system we can do about 450 billion inferences a day on the mainframe.”

“Clients who have deployed watsonx Code Assistant for Z are growing MIPS capacity 3x faster than those who have not.”

“Generative AI is now firmly integrated across our consulting engagements, representing about 30% of our backlog.”

“Today, if people are doing a payment authorization, almost all the credit card companies in the world use the mainframe for their credit card authorizations. If they want to do fraud, they can run a few rules in that engine, but then they'll take a sampling of the transactions, let's call it, 10% of the platform because the latency that it introduces to take it off platform, you can't take them all, just slow the whole system down. That's what they do off. What happens if you could run a 20 billion, 30 billion parameter model right on the mainframe, suddenly because that is only milliseconds of latency, you can do that to every single transaction.”

“clients such as NatWest and RBC are modernizing their mainframe environments using AI and automation capabilities, including watsonx Assistant and watsonx Code Assistant for Z to improve resiliency, security and developer productivity.”

“we are building, for example, our software development AI product, Project Bob. It is out, we actually chose not to announce it. Nevertheless, 200 people signed up to use it. So that gives us a signal that we have something.”

“ServiceNow is leveraging watsonx for automated data quality and observability to deliver AI-ready data and code generation to refresh legacy applications to modern application run times, including ServiceNow.”

“With Nestle, we are using NVIDIA accelerated watsonx.data to embed AI directly into core order-to-cash operations, enabling faster real-time insights across Nestle's global supply chain.”

“Enterprises are still figuring out where to deploy this technology and where competitive advantage truly sits. Every major technology wave has followed a pattern. Value begins with infrastructure, moves to enabling platforms and ultimately concentrates in the workflows where businesses operate. Right now, the spotlight is on foundation models. Enterprises are building portfolios, frontier models for some workloads, smaller models running on-premise for others and open source models where control and flexibility matter the most.”

“As people get serious, about AI because when they start experimenting, they may take a little bit of the data, they make a copy of it, they put it on a public cloud, they run it on some public frontier model, they get some results, and that's exciting to them. As they get to scale, they've got to use the data from their internal systems. If they're using data from the internal systems, many parts of our portfolio, be it Red Hat, be it Confluent, will come to be consumed more and more.”

“We made the decision about 3 years ago that we were going to be neutral and Switzerland like also on our usage of frontier models. Because I think when we are saying the GenAI applications, I think for many people that is synonymous with the frontier model providers, not just the fronter models, but all the surrounding software [indiscernible] that all of them are giving. So we are going to play where clients want to be hybrid.”

“During the quarter, we also announced strategic collaborations with NVIDIA, expanding our work across GPU native analytics. In addition, we announced a strategic collaboration with ARM to expand how AI workloads run across IBM infrastructure. By enabling the ARM software ecosystem within mission-critical environments like IBM Z, clients can scale AI closer to the data while preserving the security and resilience they require.”

“We are building the platform that lets enterprises put AI to work on their terms, wherever it runs, whichever models they choose and under governance they control. Our portfolio is built around world-class security, support and integration for an enterprise environment. Red Hat provides a common open platform that lets enterprises run applications in AI consistently across any infrastructure.”

“Value is going to decrease in that interaction layer because as agents replace people for some fraction, we can debate how much of the interactions, then the interaction layer by itself is not sticky. The agents are going to be interacting much more with the underlying data and the business logic. And we sort of saw that coming 6, 7 years ago, and that is why we picked the portfolio we did.”

“Confluent, which we closed this past quarter, solves that directly. It streams live, governed data to models and agents across the hybrid environment. And the orchestration layer ties it together. In a multi-model world, clients need to route between models, manage agent workflows and maintain governance. That is what watsonx Orchestrate and our watsonx platform deliver.”

“In automation, the logic is similar, agents multiply applications, integrations and execution paths. Managing that sprawl requires a controlled plane to provision infrastructure, integrate applications, secure environments and manage cost. This is what our end-to-end automation portfolio provides.”

“We have also created AI additions of critical software products like Db2, Cognos and MQ. These embed agentic AI that can reason, act and automate at scale while preserving IBM grade security and trust.”

“We also introduced Sovereign Core software that lets organizations run AI workloads under their own operational authority within a defined jurisdiction and auditable controls.”

“In storage, growth reflected strong adoption of our new flash offerings introduced in the first quarter, which incorporate industry-leading agentic AI capabilities.”

“IBM Concert identifies vulnerabilities proactively and automates remediation, helping enterprises maintain resilience at scale.”