In collaboration withSAP
For many years, companies responded to evolving market demands with temporary technological fixes. To manage escalating infrastructure expenses, they embraced cloud solutions that could grow as needed. When consumers transitioned their activities to smartphones, enterprises launched mobile applications to keep up. And when organizations began requiring real-time insights into production facilities and storage areas, they implemented IoT technologies to provide that visibility.
Each new integration or system promised enhanced, more effective operations. And in many cases, they delivered that promise. However, as the number of solutions accumulated, IT teams were required to weave together a complex web to interconnect them—less an IT ecosystem and more a makeshift assembly of temporary measures.
This situation has resulted in bottlenecks and maintenance challenges, which are reflected in performance metrics. Currently, fewer than half of CIOs (48%) indicate that their existing digital projects are meeting or surpassing business outcome expectations. A separate survey conducted in 2025 revealed that operations executives cite integration difficulties and data quality problems as primary reasons why investments have not achieved anticipated results.
Achim Kraiss, chief product officer of SAP Integration Suite, sheds light on the extensive issues present in fragmented IT: “A disjointed landscape hinders the ability to observe and manage comprehensive business processes,” he explains. “Oversight, diagnostics, and governance all take a hit. Expenses increase due to the complex mappings and multiple application integrations that must be maintained.”
These obstacles assume new importance as businesses seek to incorporate AI. With AI becoming woven into daily operations, systems are suddenly required to handle much larger amounts of data, at greater speeds, and with closer coordination than the architectures of the past were designed
to sustain.
As organizations now gear up for an AI-driven landscape, whether that entails generative AI, machine learning, or agentic AI, many are coming to realize that the manner in which data flows through their business is as crucial as the insights it produces. Consequently, firms are shifting away from dispersed integration tools and towards unified, comprehensive platforms that bring structure and streamline system interactions.
This content was generated by Insights, the bespoke content division of MIT Technology Review. It was not authored by the editorial team of MIT Technology Review. It was researched, crafted, and written by human writers, editors, analysts, and illustrators. This includes the composition of surveys and data collection for surveys. AI tools that may have been utilized were restricted to secondary production processes that underwent thorough human evaluation.
