SAP: Building an AI Platform to Drive Business Value
Generative AI (Gen AI) is continuing to shape the global business landscape as we know it. According to a recent report by the Oliver Wyman Forum, Gen AI could add up to US$20tn to global GDP by 2030, whilst saving 300 billion work hours a year.
With that in mind, it’s no wonder that organisations across the globe have accelerated their AI adoption. SAP, for example, has revealed extensive plans to further implement AI into its solutions, using the technology to help its customers solve their most pressing problems.
Leading SAP’s AI team is Walter Sun, the company’s Global Head of Artificial Intelligence, who joined SAP in September 2023 after 18 years at Microsoft. Having held a variety of roles focused on AI both in consumer and business scenarios, including Bing search, Bing Predicts, and Windows Media, he most recently led AI efforts for the company’s business applications.
“When the opportunity presented itself to come to SAP, it was something I couldn’t pass up because SAP is synonymous with business applications,” Sun tells us. “We run companies’ most mission critical systems that drive every part of an organisation, from finance and supply chain, to HR, procurement, travel & expense, commerce and the world’s largest business network.”
AI growth: Moving past the hype phase
As Sun describes, with the advent of generative AI (Gen AI), the world finds itself at the beginning of a major cycle of technological innovation.
“We are rapidly moving past the hype phase and lots of various pilots, into meaningful adoption of generative AI to deliver value. That is exactly what SAP is delivering.”
In September 2023 SAP announced its enterprise generative AI assistant Joule, a natural-language, Gen AI copilot that the company said will transform the way business runs.
Building on and enhancing existing SAP Business AI offerings, Joule is embedded into SAP applications from HR to finance, supply chain, procurement and customer experience, as well as into SAP’s Business Technology Platform (BTP).
“This quarter we are coming out with our regulatory change manager embedded with Joule,” Sun describes. “This will help customers better understand upcoming regulatory changes that impact SAP products and business processes. It evaluates a vast number of regulatory updates, putting them into the context of a customer’s business and their SAP solutions. It also provides impact analysis across SAP products and solutions to help customers maintain compliance and run their day-to-day business without disruption.”
SAP's use of AI setting it apart from competitors
Leveraging AI in its solutions is nothing new for SAP. The organisation has been applying traditional AI to its business processes for at least a decade – for pattern detection, image recognition and classification to regression analysis, decision making and more.
Famously, Gen AI is only as valuable as the data it draws from. “Competitors who can combine business data with Gen AI to provide strong context for the AI scenarios embedded in their solutions will have a significant advantage,” Sun asserts. “This is where SAP is in a unique position to deliver value to our customers, by leveraging our robust data model to build highly relevant AI business scenarios.
“For over 50 years, business data has been moving through SAP systems. And today, thousands of businesses allow us to use their data – with all proprietary information removed – to build AI business models we can leverage to develop business scenarios across the entire SAP portfolio.”
Another clear SAP differentiator is its reputation for being a responsible custodian of its customers’ sensitive data and mission-critical processes.
“AI has the potential to unlock vast potential for society, businesses, and governments,” Sun adds. “But it could also create economic, political, and societal challenges, depending on how it is implemented and used. SAP is committed to running responsible AI built on leading ethics and data privacy standards.”
Implementing AI into business workflows: The challenges
Implementing AI in business is not without challenges. Sun identifies the complexity of business-specific data and the risk of context loss as significant hurdles.
“Businesses have always required relevant and reliable business results,” he says. “That means they’ll need to find ways of combining generative AI with their business-specific data. These data are notoriously complex and often sit in multiple systems, so there is a high risk of losing valuable context when they are extracted and combined.
“Since Gen AI is only as valuable as the data it draws from, companies that can best combine their own business data with Gen AI to provide the strongest context to the models will have a significant leg up on the competition.”
Solutions cutting through the 'AI hype'
Sun acknowledges the risk of disillusionment with AI technologies that fail to deliver tangible business gains. To combat this, he stresses the importance of applying business context and additional grounding to AI inputs, ensuring the reliability of the results.
“Customers can quickly become disillusioned if they don’t see tangible business gains from AI technology.
“With public LLMs released for consumers, nearly every business person understands the potential power of generative AI, but most realise that deriving useful insights is tough. This is due to errors from hallucinated responses or correct but irrelevant information. To address this, we apply the company’s business context and additional grounding to the input along with other post-processing tools to ensure the highest level of reliability in the results.”
Building AI capabilities to bring strong value and positive change
Although early in his tenure, Sun is focused on embedding top-tier AI capabilities into SAP's offerings. His goal is to ensure that SAP's AI solutions bring substantial value and positive change, emphasising efficient and cost-effective technology application.
“Businesses trust SAP to improve their processes and help them be successful. To that end, I want our AI unit to build the best capabilities into our offerings to ensure our customers get differentiated AI capabilities which can truly bring strong value and positive change into their daily work through the use of the latest technology available.
“I hope we can make it easier for customers to use AI, encapsulating LLMs and other technology into our platform and then recommending the exact models needed to maximise return on investment in their businesses. Namely, we apply only the best technology needed to get a correct answer, not using more computational resources than necessary as that would be unnecessary and more costly.”
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