IBM’s Emphasized Enterprise Flywheel
Following IBM’s recent Think Conference in Boston, our team came away increasingly constructive on the company’s long-term positioning across enterprise AI, hybrid cloud, and most notably quantum computing. The key takeaway from the conference was that IBM’s strategy is becoming increasingly interconnected as their different segments are no longer operating as separate initiatives. Instead, management repeatedly emphasized how these technologies feed into one another and strengthen IBM’s broader enterprise flywheel.
Orchestrating AI to Benefit from Enterprise Adoption
Rather than competing directly on building the largest consumer-facing AI models, IBM’s management emphasized a different approach focusing on the infrastructure and orchestration layer surrounding enterprise AI deployments regardless of which underlying model customers choose. Through this positioning, IBM benefits when enterprises use third-party models, like OpenAI or Anthropic, as IBM can monetize token usage, governance, orchestration, workflow integration, and security around those systems. Management noted that AI-related growth is now spreading across nearly every business segment, making the prior “AI book of business” metric less useful as AI becomes embedded throughout the company.
Regarding their internal AI developments, the conference shared extensive commentary on “BOB,” IBM’s internal enterprise AI assistant built on top of their Watsonx platform. Management demonstrated how BOB can modernize legacy enterprise systems, map architecture automatically, generate modernization plans, and even create entirely new workflows and applications. In their presentation, they describe examples where BOB generated more than 100,000 lines of code while helping enterprises reconstruct institutional knowledge trapped inside legacy systems or long-time employee workflows.1 This modernization opportunity appears substantial as enterprises increasingly seek to integrate AI capabilities into decades-old infrastructure. Roughly 80% of IBM’s AI consulting book is now coming from new clients, reinforcing that enterprise AI adoption remains in the early innings, with management believing monetization from AI orchestration could become significantly more visible over the next 12–18 months.2
Infrastructure, Mainframes, and Hybrid Cloud Remain Strategic Advantages
Beyond AI software, IBM continues to see strong momentum in infrastructure and hardware. Management noted that CPU and memory shortages are helping drive stronger server demand as enterprises handle increasingly compute-intensive workloads tied to payments, transaction growth, analytics, and AI. Management suggested the current z17 mainframe cycle could become one of the strongest adoption cycles the company has seen, particularly as inferencing workloads increasingly move closer to mission-critical enterprise data. IBM noted that its mainframes still process roughly 90% of global financial transactions, reinforcing how deeply embedded these systems remain inside the global economy.3 The company also emphasized that it has spent years preparing excess capacity on z systems specifically to support larger AI, software, and inferencing workloads layered on top of existing infrastructure. Flexible consumption pricing and OpenShift integration further strengthen IBM’s ability to modernize enterprise environments without forcing customers into hyperscaler lock-in and spending.
Hybrid clouds also remain a central pillar of IBM’s strategy. Management framed IBM’s infrastructure approach as differentiated from hyperscalers by emphasizing interoperability, governance, reliability, and cloud-agnostic deployment flexibility. Red Hat and OpenShift continue to serve as critical connective tissue allowing enterprises to operate across multiple cloud environments while avoiding dependency on a single vendor. IBM’s infrastructure positioning benefits from not only from AI adoption itself, but the growing complexity involved in integrating AI securely into existing enterprise architectures.
Quantum Computing Is Becoming Commercially Relevant
The most exciting portion of the conference centered around quantum computing. As we discussed previously in our prior IBM Quantum Day commentary, we continue to believe quantum computing represents one of the most compelling long-term opportunities in technology. The conference further reinforced our view that IBM is advancing developments across quantum hardware, software, scale, and enterprise ecosystem adoption. The company’s competitive position appears increasingly differentiated. IBM currently has more than 30 deployed systems with more deployed quantum computers than the rest of the industry combined. Management emphasized that deployment scale matters because real-world usage accelerates software, algorithm, and ecosystem development.4
Management argued the industry has already crossed into “quantum utility,” where quantum systems can solve certain problems beyond classical approaches, and is now progressing toward fault-tolerant systems expected around 2029. Estimates suggest quantum computing could ultimately create between $450 billion and $850 billion in economic value creation while supporting a potential $130 billion to $260 billion quantum technology market, generating a broader long-term opportunity approaching $1 trillion in market value by 2030.5
The earliest commercial opportunities appear particularly compelling in simulation-heavy industries where classical computing struggles with exponentially difficult calculations. IBM specifically highlighted opportunities across drug discovery, materials science, optimization, machine learning, logistics, energy, aerospace, and financial services. One especially important area discussed involves partial differential equations (PDEs), mathematical calculations which are heavily used in scientific and industrial simulations. IBM highlighted PDE-related workloads as a major future opportunity for quantum systems, particularly in areas such as financial modeling, industrial simulations, and complex optimization problems. Opportunities in healthcare also appear especially promising, referencing work with the Cleveland Clinic demonstrating rapid progress in molecular mapping capabilities. In October 2024, IBM could only map roughly 10 atoms simultaneously for scientific research. Management noted that the company can now map approximately 12,000 atoms at once, highlighting the immense scaling in compute capability.6 The implications for understanding proteins, molecular interactions, and accelerating drug discovery could be enormous over time leading to new products and innovations in the industry.
Increasing Value of IBM’s Quantum Ecosystem
Beyond hardware, IBM is benefiting from quantum software through Qiskit, its quantum software development kit. Management stated that Qiskit is now used by roughly 70% of quantum developers and supports thousands of dependent GitHub projects.7 Software optimization is just as important as hardware scale for commercially useful quantum systems with the opportunity for Qiskit to evolve into a highly valuable software ecosystem layered on top of quantum infrastructure. Given the strength of the current z17 mainframe cycle, growing AI inferencing opportunity, expanding consulting business, and Qiskit’s growing ecosystem importance, IBM may eventually choose to provide cleaner segmentation around quantum operations and monetization trends.
Importantly, IBM’s technologies increasingly reinforce one another for future growth. Watsonx and BOB help enterprises modernize applications and workflows. Consulting helps deploy and operationalize those systems. Red Hat and OpenShift provide interoperability across hybrid cloud environments. z17 mainframes support inferencing and mission-critical workloads. Confluent and enterprise data systems create AI-ready environments. Quantum computing then becomes the next major compute accelerator layered into that ecosystem over time. Taken together, the conference reinforced the view that IBM is evolving into a strategic player in the enterprise AI and infrastructure platforms space.
[1-6] IBM: Think Conference, as of May 6, 2026
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