For years, businesses have built application estates by selecting what is considered the best software for each functional task, such as customer relationship management, procurement, and human resources management.
However, the rise of artificial intelligence (AI) has made its strategy outdated, using business applications that have spent millions at risk of becoming a product, according to SAP's senior executives.
“The application layer is now commoditized along with AI,” Muhammad Alam, a member of the SAP's Product and Engineering Executive Committee, said in a recent interview with Computer Weekly. He likened this to the way public cloud suppliers such as Amazon Web Services and Microsoft Azure have commoditized their computing infrastructure over the past 15 years.
“I don't think that SAP Ariba vs. coupa, or some of the functions of working hours and success factors, really makes a big difference,” he said. “We're trying to build these features, but differentiation doesn't seem like a work day or a success factor. Differentiation is a way of applying AI on top of them.”
The heart of Alam's argument is that AI fundamentally changes how users interact with technology. If an intelligent assistant, like SAP's Joule, can perform tasks and retrieve information through conversations, the underlying application becomes secondary. “AI will become a new user experience or engagement layer,” he said.
This reduces the need for SAP to rely on a business suite set of integrated business applications, winning patchwork of applications from various suppliers, reducing the need to build integrations and connectors, and increase the total cost of ownership. “To get the best value from AI, you need to simplify and standardize the situation in your application because it feeds the data layer,” Alam said.
Against this background, Alam pointed out two areas where SAP is innovating, starting with creating a “appless” experience for common business tasks.
For example, employees can submit their entire expenses report immediately without opening SAP using an AI agent that works through a chat platform like the Microsoft Teams to compile expenses reports from credit card data, flight information, and calendar invitations.
“I know which credit card transactions you've made, which flights you're using, and what the company's policy is,” he said.
The second area is to build a new class of AI-Native applications that solve problems that were previously thought to be impossible. Alam cited SAP's new supply chain intelligence application, which uses AI to map the entire supply chain of a company, including suppliers.
The system uses real-time data signals to predict risks and disruptions, assess orders and manufacturing impacts, and propose actions. “This is possible because we have the AI and data we can infer to build a multi-tier supply chain,” Alam says.
While these new AI systems promise unprecedented efficiency, Alam said underlying applications such as finance, manufacturing and logistics still exist as “systems of execution” to ensure regulatory compliance and manage core business rules, as well as take corrective action such as changes to production plans.
“The application doesn't go anywhere,” Alam said. “But do you need to be involved in the application? Probably not, most of the time.”
