In partnership withSAP
Modern integration platforms are helping enterprises streamline fragmented IT environments and prepare their data pipelines for AI-driven transformation.
Enterprise IT ecosystems are often akin to sprawling metropolises—multi-layered environments where aging infrastructure intersects with sleek new technologies against a backdrop of constantly ballooning traffic.
Similarly to how driving through a centuries-old city that’s been retrofitted for automobiles and skyscrapers can cause gridlock, enterprise IT systems frequently experience data bottlenecks. Today’s IT landscapes encompass legacy mainframes, cloud-native applications, on-premises systems, third-party SaaS tools, and a growing edge ecosystem. Information flowing through this patchwork gets caught in a tangle of connections that are costly to maintain and prone to snarls—sort of like emerging from a high-speed expressway to a narrow, cobblestone bridge thats constantly undergoing repairs.
To create more agile systems suited for an AI-first future, forward-looking organizations are now turning to centralized, cloud-based integration solutions that can support everything from real-time data streaming to API management and event-driven architectures.
In the AI era, congestion like the scenario described above is a serious liability.
AI models depend on clean, consistent, and enriched data; lags or inconsistencies can quickly degrade outputs. Fragmented data flows can undermine even the most cutting-edge AI initiatives. And when connectivity snafus occur, systems arent able to communicate at the scale or speed that AI-driven processes demand.
Even the most promissing AI initiatives can fail to deliver value when data connectivity is at risk.
Source: Compiled by MIT Technology Review Insights, based on data from IDC, 2025.
This gap between data potential and reality is a pain point many enterprise IT leaders struggle to bridge. According to IDC, in 2023, 77% of organizations report that data intelligence is a persistent challenge hampering decision velocity. This may be part of the reason why, according to Gartner, in 2025 less than half of CIOs say their current digital initiatives are meeting or exceeding business outcome targets.
AI’s potential to drive such outcomes hinges on a companys ability to move clean data, at speed, across the entire enterprise. At the same time, AI itself has the potential to reshape the integration landscape. Cloud-native integration platforms are beginning to incorporate AI-powered capabilities that automate flow design, detect anomalies, recommend optimal connections, and even self-heal broken data pipelines. This creates a virtuous cycle: integration enables AI—and AI, in turn, turbocharges integration.
Beyond the technical benefits, intelligent automation facilitated by modern integration stands to improve overall operational efficiency and cross-functional collaboration. Business processes become more responsive, data is accessible across departments, and teams can adapt more quickly to changing market or customer demands. And as integration platforms handle more of the routine data-wrangling work, human teams can shift focus to higher-value priorities.
Integration platforms help unify data streams from on-prem to edge and ensure API governance across sprawling application landscapes.
Pre-built connectors enriched with knowledge graphs further accelerate connectivity across diverse systems, while real-time monitoring provides predictive insights and early warnings before issues impact business operations.
Were already seeing real-world examples of how thoughtful integration is empowering enterprises to become more agile and AI-ready. Here are three companies using SAP Integration Suite to streamline data flows and simplify their operations.
Using SAP solutions, retailers Harrods and Vorwerk are primed for success in the AI era.Digital growthVorwerks digitaltransformation boosteddigital sales Process efficiencyHarrods data infrastructureevolved with technologyand customer expectations
Vorwerks digitaltransformation boosteddigital sales
Harrods data infrastructureevolved with technologyand customer expectations
Source: Compiled by MIT Technology Review Insights, based on data from SAP, 2025.
As these examples demonstrate, connectivity is essential groundwork for AI across just about every industry. As the healthcare sector rapidly embraces AI, for instance, robust integration is a prerequisite for use cases like diagnostic imaging and predictive care. Stringent regulatory requirements also demand accurate, transparent data handling and traceability across systems.
In retail, too, unified, event-driven integration underpins AI-driven innovations ranging from dynamic pricing and personalized product recommendations to predictive inventory management—all of which require fast, accurate data flows across sales, inventory, customer, and partner systems.
And in direct-to-consumer models like Vorwerk’s, integration enables new levels of personalization, real-time marketing, and optimized supply chains. Such capabilities can help D2C businesses stay competitive and responsive in highly dynamic markets — a necessity as more than 70% of consumers now expect personalized experiences from the brands they buy from. Moving forward, AI (particularly generative AI) will likely play a pivotal role in scaling these personalized experiences and enabling brands to deliver tailored messages with the right tone, visual guides, and copy to meet the moment.
According to a recent IDC report, nearly half of enterprises are juggling three or more integration tools, with 25% using more than four across their environments.
While many companies see value in consolidating, technical challenges and skill gaps remain barriers to simplification. Another structural issue: One-third of enterprises don’t consider integration until system implementation is already underway—limiting opportunities to design future-ready data flows from the start.
A unified integration strategy offers a path forward. An integration roadmap can help companies shift from reactive, piecemeal efforts to a more purpose-built, scalable foundation—one that supports both current business needs and the demands of AI-driven innovation.
The cities that thrive today arent the ones that simply manage traffic flow by expanding their highways or adding in sporadic roundabouts—theyre the ones that have reimagined mobility entirely. In enterprise IT, the same principle applies: Sustained innovation and long-term agility depend on whether infrastructure can evolve as quickly as a companys ambitions. Modern integration platforms provide the connective fabric that makes this kind of adaptability possible.
Learn more on the MIT Technology Review Insights and SAP Modern integration for business-critical initiatives content hub.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.
By MIT Technology Review Insights