Building connected data ecosystems for AI at scale
Modern integration platforms help enterprises optimize fragmented IT environments and prepare data pipelines for AI-driven transformation.
Enterprise IT ecosystems often resemble sprawling metropolises—multi-layered environments where aging infrastructure intersects with today's new technologies amid ever-increasing traffic.
Just as driving through a centuries-old city converted to cars and skyscrapers can lead to gridlock, enterprise IT systems often face data bottlenecks. Today's IT environments include legacy mainframes, cloud applications, on-premises systems, third-party SaaS tools, and an evolving ecosystem. Information passing through this patchwork quilt ends up in a tangle of connections that are expensive to maintain and prone to failure—like exiting a high-speed expressway onto a narrow cobblestone bridge that is constantly being repaired.
Forward-thinking organizations are now turning to centralized cloud integration solutions.
To create more flexible systems fit for an AI-first future, forward-thinking organizations are now turning to centralized cloud integration solutions that can support everything from real-time data streaming to API management and event-driven architectures.
In the era of artificial intelligence, road congestion like the above scenario is a serious problem.
AI models depend on clean, consistent, and enriched data; delays or inconsistencies can quickly degrade results. Fragmented data streams can undermine even the most cutting-edge artificial intelligence initiatives. And when connectivity issues arise, systems cannot communicate at the scale or speed that AI-driven processes require.
Even the most promising AI initiatives can fall short when data connectivity is compromised.
The potential for AI to achieve these results depends on a company's ability to quickly move clean data across the enterprise. At the same time, AI itself has the potential to change the integration landscape. Cloud integration platforms are beginning to include artificial intelligence 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 accelerates integration.
In addition to technical benefits, intelligent automation supported by modern integration improves overall operational efficiency and cross-functional collaboration. Business processes become more responsive, data becomes available to all departments, and teams can more quickly adapt to changing market or customer requirements. And because integration platforms take care of much of the grunt work for processing data, human teams can shift their attention to more important priorities.
Integration platforms help unify data flows from on-premise to the edge and enable API management across vast application environments.
Pre-built connectors, enhanced with knowledge graphs, further speed up interactions between different systems, while real-time monitoring provides predictive information and early warnings before issues impact business operations.
We're already seeing real-life examples of how smart integration is helping businesses become more agile and AI-ready. Here are three companies using SAP Integration Suite to optimize data flows and simplify their operations.
- Siemens Healthineers specialists: In the healthcare sector, where data accuracy, timeliness and security are non-negotiable, Siemens Healthineers uses integration solutions make medical services more accessible and personalized.
Siemens Healthineers operates a diverse business environment spanning diagnostics, medical imaging and therapeutics, each with unique data requirements and processes. To enable more autonomous decision-making, the company's level of integration helps streamline core financial processes such as closing and reporting, as well as support flexible planning and instant operational analytics. It also allows seamless access to data between systems without the need for data replication, which is important in a highly regulated industry. - Harrods: Luxury retailer Harrods operates complex hybrid IT landscape this supports both its flagship London store and growing e-commerce business; The company now offers 100,000 products online and processes 2 million transactions per day across digital channels. To modernize and simplify this growing presence, Harrods is leveraging SAP's pre-built B2B connectors and Event Mesh architecture to deliver over 600 key business process integration flows.
Since implementing SAP solutions, Harrods has reduced integration process time by 30% and TCO by 40%. More importantly, the company has created a flexible data and application foundation that can adapt as customer expectations and digital retail technologies evolve.
- Vorwerk: German direct selling company Vorwerk, known for products such as smart kitchen appliances and cleaning systems, has undergone a major digital transformation in recent years. Between 2018 and 2023 the company increased its digital sales only from 1% to 85%.
Vorwerk uses SAP solutions to automate data flows in mission-critical systems, including CRM and inventory management, payment processing and consent management. The updated system helped eliminate manual documentation, significantly speed up the order-to-payment cycle, and improve the accuracy and consistency of customer data.
Using SAP solutions, retailers Harrods and Vorwerk are poised for success in the age of artificial intelligence.
Digital growth
Vorwerk digital format
transformation accelerated
digital sales
Process efficiency
Harrods Data Infrastructure
evolved with technology
and customer expectations
As these examples show, connectivity is an important foundation for artificial intelligence in virtually every industry. For example, as the healthcare sector rapidly adopts AI, robust integration is essential for use cases such as diagnostic imaging and predictive care. Strict regulatory requirements also require accurate and transparent data processing and tracking across all systems.
In retail, unified, event-driven integration is also at the heart of AI-driven innovations, from dynamic pricing and personalized product recommendations to predictive inventory management—all of which require fast, accurate data flow between sales, inventory, customers and partners.
And in direct-to-consumer models like Vorwerk's, integration enables new levels of personalization, real-time marketing and supply chain optimization. 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. In the future, AI (especially generative AI) will likely play a key role in scaling these personalized experiences and enable brands to deliver tailored messages with the right tone, visual guidance and copy that speaks to the moment.
According to a recent IDC reportNearly half of enterprises use three or more integration tools, and 25% use more than four in their environments.
While many companies see value in consolidation, technical challenges and skills gaps remain barriers to simplification. Another structural challenge: A third of enterprises don't consider integration until system implementation begins, limiting the ability to design future-ready data flows from the start.
Sustained innovation and long-term agility depend on infrastructure being able to evolve as quickly as the company's ambitions. Modern integration platforms provide the connective tissue that makes this adaptability possible.
A unified integration strategy opens the way forward. An integration roadmap can help companies move from reactive, siled efforts to a more specialized and scalable framework that supports both current business needs and the demands of AI-driven innovation.
The cities that thrive today are not those that simply manage traffic flow by widening their highways or adding periodic roundabouts—they are those that have completely reimagined mobility. In enterprise IT, the same principle applies: sustainable innovation and long-term agility depend on whether the infrastructure can evolve as quickly as the company's ambitions. Modern integration platforms provide the connective tissue that makes this adaptability possible.
Learn more about MIT Technology Review Insights and SAP. Modern integration for mission-critical business initiatives content hub.
This content was created by Insights, the content creation arm of MIT Technology Review. It was not written by the editors of MIT Technology Review.
This content has been fully researched, developed and written by human writers, editors, analysts and illustrators. This includes writing surveys and collecting survey data. The AI tools that could be used were limited to secondary manufacturing processes that had undergone extensive human testing.
