SAP, the world-renowned enterprise resource planning (ERP) software behemoth, based in Germany, is breaking new ground in the AI landscape by employing large language models (LLMs). An internal ‘Generative AI interest group’ has sparked innovations, and a hackathon event has opened the doors to myriad novel use cases. The aim of these initiatives is to expand SAP AI capabilities and continue to shape the future of the software industry.
Before the inception of ChatGPT, SAP had already commenced its exploration of generative AI. The focus was primarily on the auditing sector where it used this AI type to validate contracts and legal notices within its applications. Utilizing Google’s existing LLMs, SAP developed and implemented innovative models internally.
However, the leap towards a broader application occurred in 2023 when SAP Labs India in Bengaluru launched the ‘Generative AI interest group’. The formation of this group, part of the Leader Together Data Science forum, sought to inspire a spirit of curiosity and exploration among AI enthusiasts in the company, urging them to discover the potential of generative AI and foundational models.
This endeavor was successful in attracting an astounding 2,500 participants, encompassing developers, product owners, and UX/UA designers. The highlight of the group’s initiative was the ‘Idea2Impact’ generative AI hackathon, which happened in March 2023 across SAP Labs India. The primary goal of this hackathon was to uncover generative AI applications in product innovation, developer efficacy, and social impact, among others. A total of 179 ideas were submitted by more than 550 participants, leading to 40 ideas reaching the Proof of Concept stage, and 11 showcased at the Development to Community event. Impressively, one idea even spurred a patent application.
Generative AI’s Integration Across Core Domains and the SAP AI Vision
In a strategic move to drive innovation and efficiency, SAP has been incorporating generative AI across its suite of applications, from SAP Transportation Management to SAP SuccessFactors, SAP Analytics Cloud, SAP Signavio Process Manager, and the SAP Digital Assistant. One such example is its application in SAP’s document processing solution for the automotive and manufacturing industries. Generative AI automates manual checks of goods receipts and delivery notes, leading to significant time and cost savings.
Partnerships are also on the horizon, as seen with SAP’s collaboration with Microsoft on SAP SuccessFactors. The partnership aims to streamline recruiting and employee development processes, including auto-generating job descriptions and interview questions via GPT models provided through the Microsoft Azure OpenAI Service.
The SAP AI strategy is not confined to in-house development and deployment. The company also aims to create a diverse ecosystem of partner technologies, factoring in variables such as cost, enterprise readiness, economies of scale, market reach, and data privacy. The objective is to select and integrate technologies that align best with SAP’s offerings and provide the most value to their customers.
SAP’s endgame with its AI strategy is to deeply embed AI into business applications and processes. Leveraging its own AI technology and strategic partnerships, SAP envisions a future where its solutions will generate insights and optimizations by connecting relevant business knowledge and process data. This transformative vision sees AI making businesses more productive, efficient, and resilient.
However, the German tech giant firmly believes in a human-centric approach, and therefore, they design their AI solutions to keep humans in the loop, approving AI-generated information. This way, SAP is not just harnessing AI’s potential but also shaping the future of AI-human collaboration.
