Building connected data ecosystems for AI at scale
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 that’s constantly undergoing repairs.
Forward-looking organizations are now turning to centralized, cloud-based integration solutions.
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 aren’t 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.
Integration enables AI—and AI, in turn, turbocharges integration.
AI’s potential to drive such outcomes hinges on a company’s 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.
We’re 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.
- Siemens Healthineers: In the healthcare sector, where data accuracy, timeliness, and security are non-negotiable, Siemens Healthineers is using integration solutions to make health services more accessible and personalized.
Siemens Healthineers operates a diverse business landscape spanning diagnostics, medical imaging, and therapy, each with unique data requirements and processes. To enable more autonomous decision-making, the company’s integration layer helps streamline core financial processes, such as closing and reporting, while also supporting flexible planning and instant insights into operations. It also enables seamless data access across systems without the need for data replication, an important consideration in a highly regulated industry. - Harrods: Luxury retailer Harrods operates a complex hybrid IT landscape that supports both its flagship London store and a growing e-commerce business; the company now offers 100,000 products online and processes 2 million transactions per day through digital channels. To modernize and simplify this growing footprint, Harrods leverages SAP’s pre-built B2B connectors and Event Mesh architecture to orchestrate more than 600 integration flows across key business processes.
Since implementing the SAP solutions, Harrods has reduced integration-related process times by 30% and cut total cost of ownership by 40%. More importantly, the company has created a nimble data and application backbone that can adapt as customer expectations — and digital retail technologies — evolve.
- Vorwerk: German direct-sales company Vorwerk, known for products like smart kitchen appliances and cleaning systems, has undergone a sweeping digital transformation in recent years. Between 2018 and 2023, the company grew its digital sales from just 1% to 85%.
Vorwerk relies on SAP solutions to automate data flows across critical systems, including CRM and inventory management, payment processing, and consent management. The updated system has helped eliminate manual paperwork, significantly accelerate order-to-cash cycle times, and improve the accuracy and consistency of customer data.
Using SAP solutions, retailers Harrods and Vorwerk are primed for success in the AI era.
Digital growth
Vorwerk’s digital
transformation boosted
digital sales
Process efficiency
Harrods data infrastructure
evolved with technology
and customer expectations
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.
Sustained innovation and long-term agility depend on whether infrastructure can evolve as quickly as a company’s ambitions. Modern integration platforms provide the connective fabric that makes this kind of adaptability possible.
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 aren’t the ones that simply manage traffic flow by expanding their highways or adding in sporadic roundabouts—they’re 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 company’s 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
