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Investments in these transformations are of critical importance. For companies, however, this was not the finish line; rather, it laid the groundwork. And it is precisely this foundation that they are now leveraging as they implement AI solutions designed to deliver measurable business results.<\/p>\n
But another element of this foundation is becoming increasingly important: data. Companies that have invested in a data foundation can achieve the greatest value from AI\u2014because this provides AI solutions with a trustworthy business context that enables them to draw conclusions, make recommendations, and take action.<\/p>\n
In my conversations with customers in the Americas and around the world, a new pattern is now emerging. The focus is less on the potential use cases for AI and more on what happens when intelligent technologies are integrated into a company\u2019s core processes.<\/p>\n
Although every transformation is always tailored to a company\u2019s specific needs, three trends are evident that are common to all transformation projects.<\/p>\n
The first wave of AI adoption focused primarily on demonstrating the value of AI. Companies identified use cases with particularly high value to achieve measurable results and build confidence that AI can help optimize processes.<\/p>\n
They continue to work on this. However, customers are increasingly asking how intelligent technologies can be embedded in the business processes their employees use every day. In practice, there are already concrete examples of this.<\/p>\n
The Brazilian company HR Path Brazil provides recruiting and talent management services for international companies and, for example, uses Joule\u2014a solution integrated into SAP SuccessFactors HCM\u2014to automate typical HR interactions. This enables HR Path Brazil\u2019s employees to find the information they need more quickly, leaving HR teams with more time for strategic tasks. As a result, the company was able to reduce the number of standard HR support cases by seven percent and cut the HR support team\u2019s workload by two hours per week. This quickly translates into significant cost-saving potential. This example demonstrates how integrated and connected AI solutions are becoming an integral part of workflows.<\/p>\n
One of the biggest changes I\u2019m currently observing concerns the way companies define success. ROI is increasingly becoming a given. This is also supported by research, particularly a study published this week by Oxford Economics. It shows that companies investing in AI expect an average return of 21% this year and as high as 38% in two years. Against the backdrop of the ongoing development of Agentic AI, experts are also forecasting a return of $17.6 million. This represents more than a fourfold increase from last year\u2019s estimates, which stood at $4.3 million.<\/p>\n
Companies can therefore specifically explore the question of what business results their AI enables. They want to know how they can shorten cycle times and make better decisions. They are also interested in whether AI reduces the workload on their employees, leaving them more time for value-added activities. Finally, they are also concerned with whether AI helps them become more resilient and respond more quickly.<\/p>\n
This shift is significant because it demonstrates that the focus is shifting from the implementation of technology to the improvement of business performance.<\/p>\n
In my assessment, the third development will have the greatest long-term impact. For decades, enterprise software primarily mapped transactions, standardized processes, and automated routine tasks. Now, it is increasingly helping companies identify changes early on, recommending appropriate measures, coordinating workflows across functions, and\u2014with growing frequency\u2014making routine decisions that are then reviewed by humans.<\/p>\n
For this reason, I believe the autonomous enterprise is far more than just the next phase of automation. It represents a new business model.<\/p>\n
In the autonomous enterprise, employees are no longer occupied with linking information from finance, the supply chain, procurement, human resources, and customer business processes in order to derive further actions. Rather, intelligent systems are increasingly capable of providing contextual information, making recommendations, coordinating workflows, and supporting teams in implementing strategies.<\/p>\n
Control always remains with humans. However, they are supported by enterprise software that is directly integrated into the company\u2019s business processes and actively contributes to their execution\u2014rather than merely recording what has already happened.<\/p>\n
The greatest long-term benefits will not go to the companies that implement the most AI use cases. Rather, the greatest benefits will be realized by those who use these initial successes as a foundation for fundamentally redesigning workflows across the entire company.<\/p>\n
The evolution toward an autonomous enterprise is a lengthy process that will continue to require a strong leadership culture, governance, and qualified employees in the future. These factors will become even more important.<\/p>\n
It is very likely that, at some point, we will look back on today\u2019s AI projects the way we look back today on the early days of cloud transformation: We will not view them as an end in themselves, but as the foundation for an entirely new operating model and new opportunities to drive continuous innovation.<\/p>\n
The true beneficiaries of this transformation will be the companies that become increasingly intelligent, adaptable, and autonomous.<\/p>\n
Jan Gilg is a member of the Extended Executive Board of SAP SE and Global President of Customer Success & Americas.<\/p>\n
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