Mainframe Modernization Market by Type (Rebuilding, Refactoring, Rehosting), Deployment Model (Cloud, Hybrid, On-Premise), Organization Size, Industry Vertical - Global Forecast 2026-2032

The Mainframe Modernization Market was valued at USD 10.12 billion in 2025 and is projected to grow to USD 11.45 billion in 2026, with a CAGR of 13.88%, reaching USD 25.15 billion by 2032.

Mainframe modernization has become a business-first reinvention of core systems, delivery speed, and risk posture in hybrid environments

Mainframes continue to run the operational core of many enterprises because they deliver unmatched reliability, predictable performance, and mature transactional integrity. Yet the same strengths that made these platforms enduring can become constraints when organizations need faster product releases, elastic capacity, and simpler integration with cloud-native services. Executive teams are therefore reframing mainframe modernization from a technical refresh into a broader operating-model shift that touches risk management, talent strategy, security, and customer experience.

In this environment, modernization is less about abandoning legacy systems and more about reshaping how value is delivered. Leaders are pursuing approaches that preserve what works-such as proven business logic and high-volume processing-while removing bottlenecks in release cycles, data accessibility, and integration. As a result, modernization programs increasingly combine application rationalization, API enablement, data modernization, and selective platform transformation, guided by measurable business outcomes rather than technology milestones.

At the same time, the definition of “mainframe modernization” has expanded. It now includes initiatives such as hybrid operations, DevSecOps adoption for COBOL and PL/I teams, automated testing for batch and online workloads, and governance models that align platform engineering with product teams. This executive summary frames the pivotal changes shaping the market, the policy and supply-chain pressures influencing delivery decisions in 2025, and the practical insights leaders can use to act with confidence.

Landscape shifts are redefining modernization through hybrid-by-default architectures, AI-assisted delivery, and portfolio-based transformation models

The modernization landscape is undergoing a set of shifts that are simultaneously technological, organizational, and economic. One of the most consequential changes is the move from monolithic transformation programs to portfolio-based modernization. Instead of a single, multi-year “big bang,” enterprises are decomposing work into value streams, prioritizing high-change domains, and using measurable increments to manage risk. This shift is reinforced by improved tooling for discovery, dependency mapping, automated code analysis, and continuous testing-capabilities that reduce uncertainty and make staged modernization more feasible.

Another major shift is the normalization of hybrid architectures. Enterprises are increasingly comfortable keeping the highest-throughput transactional workloads on the mainframe while moving adjacent services, digital channels, and analytics workloads to cloud platforms. This is accelerating the adoption of API-first integration, event streaming, and data virtualization patterns that allow mainframe-based systems of record to participate in modern digital ecosystems without forcing immediate migration of all compute.

Generative AI and advanced automation are also changing how modernization work is executed. While they do not eliminate the need for deep domain knowledge, they are improving productivity in code comprehension, documentation generation, test creation, and refactoring assistance. Importantly, organizations are pairing these capabilities with tighter governance, secure-by-design practices, and auditability to ensure that accelerated delivery does not create new operational or compliance risks.

Talent dynamics represent a parallel transformation. Organizations are investing in upskilling, modern IDE experiences, and platform engineering practices that make mainframe development more accessible to new engineers. This is complemented by an ecosystem shift in which vendors and integrators package modernization accelerators, reference architectures, and managed services to help organizations close skills gaps and sustain momentum post-migration.

Finally, security and resilience expectations are reshaping priorities. Modernization roadmaps now routinely include identity modernization, privileged access controls, continuous compliance evidence, and improved observability across hybrid transaction paths. The result is a market that rewards solutions and service partners capable of delivering modernization with minimal disruption while strengthening governance, traceability, and cyber readiness.

United States tariffs in 2025 introduce procurement and delivery pressures that reshape sequencing, sourcing strategy, and modernization risk governance

United States tariff actions anticipated for 2025 create a material planning variable for modernization programs, particularly where hardware supply chains, third-party components, and cross-border delivery models intersect. While software modernization is often viewed as insulated from trade policy, the reality is more interconnected: infrastructure refresh cycles, procurement timelines, and managed service economics can be indirectly affected by changes in duties applied to certain technology goods and associated components.

A primary impact area is infrastructure sourcing and refresh decisions. Organizations maintaining or expanding on-premises footprints may face higher acquisition costs or longer lead times for specific equipment categories if tariffs affect upstream components. Even when direct mainframe systems are procured through established channels, surrounding infrastructure-networking gear, storage subsystems, and data center hardware used for development and testing environments-can become more expensive or harder to source predictably. This introduces an incentive to reassess environment strategies, including greater use of cloud-based development and test environments where feasible, and stronger asset lifecycle planning to avoid forced purchases during periods of cost volatility.

Tariffs can also influence the cost structure of modernization partners. Integrators and managed service providers that rely on global delivery models may need to adjust contracting assumptions as procurement shifts, logistics costs fluctuate, or compliance requirements change for certain imported products bundled into solutions. In response, enterprises are strengthening contractual clarity around substitution rights, lead-time commitments, and contingency planning. They are also scrutinizing the resiliency of vendor supply chains and the geographic distribution of critical support capabilities.

From an execution standpoint, the potential for tariff-driven cost pressure tends to increase interest in modernization paths that prioritize software-led outcomes over heavy capital investments. This can translate into greater emphasis on application rationalization, code remediation, DevSecOps enablement, and API modernization before major platform shifts. Where platform transformation is still required, leaders are more likely to demand phased delivery with explicit business checkpoints, ensuring that each phase yields operational benefits that can offset macroeconomic uncertainty.

In short, tariffs are unlikely to change the strategic necessity of modernization, but they can change sequencing, sourcing, and governance. The most resilient programs treat trade policy as a risk factor to be modeled-alongside cybersecurity, talent, and regulatory risk-so that modernization remains on schedule even when procurement and cost assumptions shift.

Segmentation insights show modernization choices vary by component, approach, deployment, organization scale, and industry-specific risk tolerance

Segmentation reveals how modernization strategies diverge based on what organizations are modernizing, how they choose to execute, and the outcomes they prioritize. By component, enterprises balance software with services, frequently relying on specialist advisory and implementation capabilities to reduce uncertainty in discovery, dependency analysis, and architecture decisions. This is reinforced by a growing need for structured change management, as modernization increasingly impacts operating models and cross-functional delivery practices, not just code.

By modernization approach, rehosting and replatforming remain relevant where time constraints or infrastructure imperatives dominate, but refactoring and re-architecting gain momentum when organizations need sustained agility, cloud-native integration, and improved maintainability. In many programs, multiple approaches coexist across the application portfolio: stable, high-throughput workloads are optimized and API-enabled, while customer-facing and integration-heavy domains undergo deeper transformation. This portfolio view reduces risk and helps align investment with business value.

By deployment model, hybrid is the pragmatic center of gravity. Organizations are using cloud environments for adjacent services, analytics, and development tooling while keeping core transaction processing where it best meets resilience and performance requirements. This drives demand for secure connectivity, end-to-end observability, and consistent identity controls across environments. It also increases the importance of data strategies that support replication, synchronization, and governed access without disrupting core processing.

By organization size, large enterprises often pursue multi-year modernization programs with formal governance, while mid-sized organizations tend to prioritize targeted modernization that delivers faster operational wins. The difference is less about ambition and more about constraints: larger firms must coordinate across more stakeholders and regulatory obligations, whereas smaller organizations emphasize streamlined execution and vendor-led accelerators.

By industry vertical, regulated sectors such as BFSI and healthcare prioritize traceability, auditability, and minimal downtime, shaping decisions around testing automation and compliance evidence. Retail and e-commerce place heavier emphasis on rapid feature delivery and seasonal scalability, strengthening the business case for API enablement and event-driven integration. Telecommunications and manufacturing often focus on high-volume operational processes and the modernization of complex billing, provisioning, and supply chain workflows, where dependency mapping and phased migration matter greatly. Public sector organizations weigh modernization against procurement rigidity and long system lifecycles, making incremental modernization and skills transfer central to long-term sustainability.

Across these segmentation lenses, one pattern stands out: the most successful modernization strategies are not defined by a single technology choice but by a coherent operating model that ties modernization decisions to product velocity, resiliency objectives, and governance maturity.

Regional insights highlight how regulation, talent, and cloud maturity in the Americas, EMEA, and Asia-Pacific shape modernization execution

Regional dynamics shape modernization priorities through regulatory environments, talent availability, cloud adoption patterns, and infrastructure economics. In the Americas, modernization is frequently anchored in large-scale transformation programs within financial services, insurance, and retail, where customer experience and cybersecurity pressures are pronounced. Enterprises increasingly pursue hybrid architectures that keep core transaction processing stable while expanding digital services and analytics capabilities, supported by stronger DevSecOps adoption and modernization factories.

In Europe, the Middle East, and Africa, modernization is strongly influenced by data governance expectations and sector-specific compliance, prompting careful attention to auditability, identity controls, and cross-border data handling. Many organizations balance the desire for cloud agility with sovereignty and regulatory considerations, which can favor hybrid or regionally constrained deployments. This environment elevates the importance of architecture patterns that enable modernization without unnecessary data movement, alongside robust documentation and controls that support regulatory review.

In Asia-Pacific, modernization momentum is shaped by rapid digital growth, expanding fintech ecosystems, and large-scale consumer platforms that demand high availability and continuous feature delivery. Organizations often combine modernization with broader cloud adoption initiatives, emphasizing integration, real-time data capabilities, and scalable digital channels. At the same time, talent strategies can differ widely across markets, driving demand for automation, standardization, and managed services to sustain consistent delivery quality.

Across all regions, a unifying trend is the shift toward outcome-driven modernization. Even when regulatory and market pressures differ, leaders converge on the same operational imperatives: reducing cycle time, improving resilience, and enabling secure interoperability across a hybrid estate. Regional differences primarily influence how modernization is governed, how data is handled, and which sourcing models are most viable.

Company insights reveal differentiation through hybrid interoperability, repeatable delivery patterns, and disciplined governance that protects uptime and compliance

Company activity in mainframe modernization reflects a convergence of platform providers, cloud and infrastructure leaders, specialist modernization vendors, and global service integrators. Platform-centric players continue to invest in capabilities that improve developer experience, observability, security controls, and interoperability with modern tooling. Their strategies increasingly emphasize making core systems easier to evolve, rather than positioning modernization as a forced departure from the platform.

Hyperscale and cloud-adjacent providers focus on connectivity patterns, migration tooling, and managed services that simplify building digital services around systems of record. Their influence is particularly visible in areas such as API management, event streaming integration, and data platform modernization that extends mainframe value into analytics and AI use cases. This is complemented by vendors that specialize in application discovery, code transformation, automated testing, and portfolio analysis, often providing the accelerators that make staged modernization viable.

Service providers play a defining role in execution, especially for organizations with complex portfolios and stringent uptime requirements. Leading integrators differentiate through modernization factories, reusable reference architectures, and domain expertise that reduces rework. Increasingly, they also compete on governance maturity-how effectively they can run modernization as a product-aligned program with measurable outcomes, strong security practices, and disciplined change control.

A key competitive theme is the ability to deliver modernization without disrupting business operations. Providers that can demonstrate repeatable approaches for parallel run, cutover planning, performance validation, and compliance evidence tend to gain trust at the executive level. As AI-assisted delivery becomes more common, differentiation is also emerging around responsible use, explainability, and the integration of AI outputs into auditable engineering workflows.

Overall, the company landscape rewards those that combine technical depth with operational discipline. Buyers are increasingly selecting partners based on proven delivery patterns, ecosystem interoperability, and the ability to support modernization beyond initial implementation through managed operations, skills transfer, and continuous optimization.

Actionable recommendations emphasize portfolio-based roadmaps, integration-first design, secure delivery discipline, and workforce sustainability at scale

Industry leaders can make modernization more predictable by anchoring it to a portfolio strategy and a clear value narrative. Start by classifying applications by business criticality, change frequency, technical debt, and integration intensity, then align each cluster to an approach such as retain-and-optimize, API-enable, replatform, or refactor. This prevents over-investing in low-change systems while ensuring high-change domains receive the architecture attention needed to sustain agility.

Next, treat data and integration as first-class modernization workstreams rather than secondary tasks. Establish standardized API governance, eventing patterns, and data access controls early, because they become the connective tissue of a hybrid estate. In parallel, invest in observability that traces transactions across mainframe and cloud components, enabling faster incident response and more reliable change management.

Operationally, adopt a secure-by-design delivery model that combines automated testing, continuous compliance evidence, and release governance suited to high-stakes environments. Modernization programs frequently fail due to testing bottlenecks and insufficient end-to-end validation, so prioritizing test automation for batch, CICS/online flows, and data reconciliation can materially reduce risk. Where generative AI is used, define policies for data handling, human review, and audit trails to ensure outputs are trustworthy and regulator-ready.

To address talent constraints, modernize the developer experience and invest in structured knowledge capture. Pair experienced engineers with newer talent, adopt contemporary tooling that supports collaborative workflows, and institutionalize documentation practices that keep domain knowledge from remaining implicit. When partnering with vendors, negotiate for measurable skills transfer and operational handover outcomes rather than treating them as optional.

Finally, strengthen procurement and program governance to withstand macro volatility. Build flexibility into contracts for tooling, infrastructure, and delivery capacity, and maintain contingency plans for environment sourcing and lead times. By sequencing modernization so that early phases deliver operational improvements-such as faster releases, reduced incident frequency, or improved integration-the program can sustain executive sponsorship even when economic conditions fluctuate.

Methodology blends structured primary interviews and rigorous secondary validation to capture repeatable modernization patterns and decision criteria

The research methodology integrates primary engagement with ecosystem participants and rigorous secondary review to ensure a grounded view of modernization practices and decision criteria. The process begins with defining the scope of mainframe modernization across technology, services, and operating-model dimensions, then mapping the typical modernization lifecycle from assessment through execution and post-transformation operations.

Primary inputs are gathered through structured conversations with stakeholders across the value chain, including enterprise decision-makers, architects, engineering leaders, and solution and service providers. These discussions focus on modernization drivers, program constraints, workload selection rationale, tooling preferences, governance practices, and common failure modes. Emphasis is placed on capturing patterns that repeat across sectors and regions while recognizing that modernization outcomes depend heavily on starting conditions and organizational maturity.

Secondary research complements these insights through review of publicly available technical documentation, product information, standards references, regulatory guidance where applicable, and vendor materials. This is used to validate terminology, understand solution capabilities, and identify how offerings have evolved with trends such as hybrid operations, DevSecOps for mainframe environments, and AI-assisted engineering.

Findings are synthesized using a triangulation approach that cross-checks claims, reconciles conflicting perspectives, and prioritizes consistent signals across multiple inputs. Throughout, the methodology focuses on practical decision support: how organizations evaluate options, manage risk, govern delivery, and operationalize modernization as an ongoing capability rather than a one-time project.

Conclusion underscores modernization as a continuous capability built on hybrid pragmatism, disciplined delivery, and resilient governance amid uncertainty

Mainframe modernization is entering a phase defined by pragmatism and precision. Organizations are no longer debating whether change is necessary; they are determining how to modernize in a way that preserves resilience, accelerates delivery, and strengthens governance across a hybrid estate. This has shifted the center of gravity toward portfolio-based roadmaps, integration and data modernization, and disciplined execution practices that reduce operational risk.

Meanwhile, external pressures such as evolving security expectations and 2025 tariff-related procurement uncertainty reinforce the need for resilient program design. Modernization leaders who model these risks and build flexibility into sourcing and sequencing are better positioned to sustain progress without compromising uptime or compliance.

Ultimately, modernization success depends on aligning technology choices with operating-model maturity. The organizations that win will be those that treat modernization as a continuous capability-supported by automation, skills development, and measurable outcomes-rather than a one-off migration event.

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