Philipp Herzig, SAP's newly appointed Chief Artificial Intelligence (AI) Officer, announced the company's AI focus on building artificial intelligence capabilities into business applications to make AI more accessible to customers. We have outlined our strategy.
During a recent visit to Singapore, Herzig, who reports to SAP CEO Christian Klein, told the media that the cornerstone of SAP's AI strategy is to integrate data and processes across SAP applications to support so-called business AI. He said it was in his ability.
“Business AI first and foremost means embedding AI into business applications such as supply chain, finance, human resources, procurement, travel, expenses, and a variety of other business processes,” he said. .
SAP has already started building AI capabilities into its SuccessFactors HR suite as well as Sales Cloud and Service Cloud. These features include the ability to leverage generative AI to help recruiters craft job descriptions and customer service teams to improve ticket resolution times.
We also developed the Joule copilot. It not only provides contextualized information and assistance to users of SAP applications, but also improves developer productivity by incorporating code generation capabilities for data models, application logic, and test scripting.
“We are constantly innovating new ways to generate job descriptions using Joule, and now we are expanding to even more use cases in the HR space,” said Herzig. He added that SAP is building capabilities for approximately 30 AI use cases. These will be expanded to cover over 100 use cases this year.
As for how SAP is prioritizing AI use cases, Herzig said the company prioritizes based on value. “A lot of things are possible with AI, but if it’s not worth it or costs too much, it won’t be adopted. Whether it's part of a premium AI product, we always look at it through the lens of benefit to the customer.”
“Currently, of the 27,000 customers actively using SAP Business AI, less than 1% are on-premises. Going forward, this is the only way we will design AI. You won't be able to scale up to that number.”
Philipp Herzig, SAP
Equally important is the need to ease AI adoption for customers. When it comes to embedded AI, Herzig said, SAP has “learned the hard way that unless it's delivered out-of-the-box and as a service, not via the cloud, it won't be adopted.”
“Currently, less than 1% of the 27,000 customers actively using SAP Business AI are on-premises,” he adds, noting that customers using it as a service see immediate benefits. I pointed out that I have received it. “Going forward, this is the only way we will design AI, otherwise we will not be able to scale with the number of customers.”
SAP's approach makes AI capabilities more accessible to organizations that don't have the expertise to implement the technology. “For example, after you ship a model, if you have to retrain that model and do data cleansing, those things require a lot of skills. And many of our customers have 100 data scientists. “No,” he said Herzig.
Still, organizations with the skills and a need for a slightly different version of AI-enabled applications can play around with technology through the SAP Business Technology Platform (BTP), which has pre-built integrations between SAP applications.
“Our customers and partners can build their own versions of applications by slightly modifying and customizing what we design,” Herzig said, adding that they can do it more quickly through BTP. He added that this reduces integration issues.
“We can build on Azure, Google Cloud, Amazon Web Services, but we have to address security, build data pipelines, and integrate with identity management. We have to solve these challenges ourselves. This is where our strategy makes sense: We offer BTP as a by-product for customers to build custom applications.”
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