When a historic UK-based retailer set out to modernize its IT environment, it was wrestling with systems that had grown organically for more than 175 years. Prior digital transformation efforts had resulted in a patchwork of hundreds of integration flows spanning cloud, on-premises systems, and third-party vendors, all communicating across multiple protocols. 

The company needed a way to bridge the invisible seams stitching together decades of technology decisions. So, rather than layering on yet another patch, it opted for a more cohesive approach: an integration platform as a service (iPaaS) solution, i.e. a cloud-based ecosystem that enables smooth connections across applications and data sources. By going this route, the company reduced the total cost of ownership of its integration landscape by 40%.

The scenario illustrates the power of iPaaS in action. For many enterprises, iPaaS turns what was once a costly, complex undertaking into a streamlined, strategic advantage. According to Forrester research commissioned by SAP, businesses modernizing with iPaaS solutions can see a 345% return on investment over three years, with a payback period of less than six months.

Agile integration for an AI-first world

In 2025, the business need for flexible and friction-free integration has new urgency. When core business systems can’t communicate easily, the impacts ripple across the organization: Customer support teams can’t access real-time order statuses, finance teams struggle to consolidate data for monthly closes, and marketers lack reliable insights to personalize campaigns or effectively measure ROI.

A lack of high-quality data access is particularly problematic in the AI era, which depends on current, consistent, and connected data flows to fuel everything from predictive analytics to bespoke AI copilots. To unleash the full potential of AI, enterprises must first solve for any bottlenecks that prevent information from flowing freely across their systems. They must also ensure data pipelines are reliable and well-governed; when AI models are trained on inconsistent or outdated data, the insights they generate can be misleading or incomplete—which can undermine everything from customer recommendations to financial forecasting.

iPaaS platforms are often well-suited for accomplishing this across dynamic, distributed environments. Built as cloud-native, microservices-based integration hubs, modern iPaaS platforms can scale rapidly, adapt to changing workloads, and support hybrid architectures without adding complexity. They also help simplify the user experience for everyday business users via low-code functionalities that allow both technical and non-technical employees to build workflows with simple drag-and-drop or click-to-configure interfaces.

This self-service model has practical, real-world applications across business functions: For instance, customer service agents can connect support ticketing systems with real-time inventory or shipping data, finance departments can link payment processors to accounting software, and marketing teams can sync CRM data with campaign platforms to trigger personalized outreach—all without waiting for IT to come to the rescue.

Architectural foundations for fast, flexible integration

Several key architectural elements make the agility associated with iPaaS solutions possible:

1. API-first design that treats every connection as a reusable service
2. Event-driven capabilities that enable real-time responsiveness
3. Modular components that can be mixed and matched to address specific business scenarios

These principles are central to making the transition from “spaghetti architecture” to “integration fabric”—a shift from brittle point-to-point connections to intelligent, policy-driven connectivity that spans multidimensional IT environments.

This approach means that when a company wants to add a new application, onboard a new partner, or create a new customer experience, they’re able to do so by tapping into existing integration assets rather than starting from scratch—which can lead to dramatically faster deployment cycles. It also helps enforce consistency and, in some cases, security and compliance across environments (role-based access controls and built-in monitoring capabilities, for example, can allow organizations to apply standards more uniformly).

Further, studies suggest that iPaaS solutions enable companies to unlock new revenue streams by integrating previously siloed data and processes. Forrester research found that organizations adopting iPaaS solutions stand to generate nearly $1 million in incremental profit over three years by creating new digital services, improving customer experiences, and automating revenue-generating processes that were previously manual.

Where iPaaS is headed: convergence and intelligence

All this momentum is perhaps one of the reasons why the global iPaaS market, valued at approximately $12.9 billion in 2024, is projected to reach more than $78 billion by 2032—with growth rates exceeding 25% annually.

This trajectory is contingent on two ongoing trends: the convergence of integration capabilities into broader application development platforms, and the infusion of AI into the integration lifecycle.

Today, the boundaries between iPaaS, automation platforms, and AI development environments are blurring as vendors create unified solutions that can handle everything from basic data synchronization to complex business processes. 

AI and machine learning capabilities are also being embedded directly into integration platforms. Soon, features like predictive maintenance of integration flow or intelligent routing of data based on current conditions are likely to become table stakes. Already, integration platforms are becoming smarter and more autonomous, capable of optimizing themselves and, in some cases, even initiating self-healing actions when problems arise.

At the same time, this shift is transforming how businesses think about integration as a dynamic enabler of AI strategy. In the near future, robust integration frameworks will be essential to operationalize AI at scale and feed these systems the rich, contextual data they need to deliver meaningful insights.

Building integration as competitive advantage

In addition to the retail modernization story detailed earlier, a few more real-world examples highlight the potential of iPaaS:

• A chemicals manufacturer migrated 363 legacy interfaces to an iPaaS platform and now spins up new integrations 50% faster.
• A North American bottling company reduced integration runtime costs by more than 50% while supporting 12 legal entities on a single cloud ERP instance through common APIs.
• A global shipping-technology firm connected its CRM and third-party systems via cloud-based iPaaS solutions, enabling 100% touchless order fulfillment and a 95% cut in cost centers after a nine-month rollout in its first region.

Taken together, these examples make a compelling case for integration as strategy, not just infrastructure. They reflect a shift in mindset, where integration is democratized and embedded into how every team, not just IT, gets work done. Companies that treat integration as a core capability versus an IT afterthought are reaping tangible, enterprise-wide benefits, from faster go-to-market timelines and reduced operational costs to fully automated business processes.

As AI reshapes business processes and customer standards continue to climb, enterprises are realizing that integration architecture determines not only what they can build today, but how quickly they can adapt to whatever comes tomorrow.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.