How SAP Is Using Gen AI To Transform Business Across Its Portfolio

SAP Labs is harnessing the power of generative AI to enhance business processes across industries, from e-sports to guitar manufacturing, with the hopes of driving unprecedented innovation and efficiency.

Scaling AI across the enterprise: SAP Labs is focused on quickly integrating generative AI across its broad software portfolio, with insights from one customer’s AI adoption being directly transferable to others:

• Over 24,000 SAP customers are currently using the company’s AI solutions, with AI integrated into more than 10,000 published and 5,000 scenario-based interfaces and messages.
• SAP’s AI in Concur Invoice Management automated the processing of 40 million invoices in 2022, saving customers a combined €440 million.
• The SAP AI framework aims to provide a unified AI solution that scales across various functional areas of an enterprise, with Joule, SAP’s copilot, providing access to embedded AI capabilities.

Enhancing game analysis for e-sports: SAP analyzes over 320 million data points to help e-sports organization Team Liquid optimize strategies and performance:

• Team Liquid’s SAP platform stores 2.5 million hours of competition data in SAP HANA Cloud and has saved more than 300 hours of match preparation time in one year.
• Lessons learned from solving Team Liquid’s challenges with generative AI are being applied across multiple industries to help SAP scale its AI solutions.

Optimizing marketing campaigns and customer engagement: SAP’s generative AI tools are helping iconic guitar manufacturer Gibson personalize marketing campaigns and enhance customer engagement:

• Gibson reported a 50% increase in email revenue and a 10% increase in overall revenue within a year of using SAP’s automated campaign management tools.
• Generative AI is enabling Gibson to tailor communication and marketing strategies to meet the unique preferences of its diverse fan base, from novice guitar players to professional musicians.

Improving supply chain and logistics performance: SAP is aggregating and learning from supply chain and logistics-related use cases across its customer base to help generative AI models learn faster and handle greater complexity.

Analyzing deeper: As SAP transitions from its ERP roots to an AI-centric future, the company is leveraging its experience managing massive data sets across its customer base to make AI accessible throughout its broad application portfolio. However, integrating generative AI at such a large scale is likely to come with significant challenges, such as ensuring data privacy, security, and ethical use of AI. SAP will need to address these concerns as it continues to push the boundaries of what’s possible with generative AI in the enterprise.