Innovation and digitalization
What is SAP Joule?
Generative AI made by SAP
Since ChatGPT was released to the broad public in November 2022, it is not just the IT industry that talks about (generative) artificial intelligence (AI) and machine learning (ML), or Large Language Models (LLM).
After various partnerships in the field of AI, SAP has now announced its own spin-off in the area of generative artificial intelligence. With Joule , a digital assistant is set to be created, leveraging generative AI to effectively process the vast amount of enterprise data available within SAP systems at their customers' disposal, presenting it in a useful format.
What exactly will SAP Joule be able to do?
According to current information, Joule will initially present itself as a chat window, similar to the current standard for text-based generative AI applications.
The significant difference and potential strength of Joule, however, will be its ability to access and analyze the actual data of the company. This capability might enable SAP Joule to provide more precise, targeted, and tailored answers to company-specific queries compared to what the competition can offer.
In the sample applications already disclosed by SAP, company data is visually processed as a response to a text prompt. In SAP SuccessFactors, for instance, Joule is known to be utilized as a tool for quick navigation or application functions. An example provided was giving feedback to a colleague via SuccessFactors, where Joule analyzes the subject for which feedback is to be given, suggests relevant questions, thus facilitating the feedback process.
So far, it's not entirely clear to what extent SAP Joule will indeed represent a genuine innovation in enterprise software. As merely a type of Alexa for operating the SAP system, SAP Joule might not find sufficient justification for its existence.
How does SAP Joule fit into existing software landscapes?
SAP will continue its cloud-first strategy with Joule. It is expected that SAP Joule will be available only in the cloud.
Initially, SAP announced integration with SAP SuccessFactors , where Joule is set to be used as a digital navigation aid and also for transaction processing. This is a reasonable step, as it allows the language model and the user interface to evolve in an environment where the benefits of generative AI in the HR sector are immediately visible.
Afterwards, Joule is expected to be available in SAP S/4HANA, Public Cloud in spring 2024.
What is the potential of Joule?
It is to be expected that SAP will, in the medium term, provide and integrate a variety of AI-supported functions, building upon Joule, among others, into their software.
There are already competitors like BlueYonder that can suggest sales forecasts, sales probabilities, and supply chain replenishment paths through machine learning from a multitude of data points.
Similar approaches are already known in sales, for instance, for sales forecasting. In customer service, chatbots are already widely deployed and are increasingly becoming more helpful through generative artificial intelligence.
Here, the strength of AI applications will demonstrate itself in the future: Through AI, it might be possible to react to a changing market environment earlier and faster than humans can. For instance, it could be possible to identify new delivery routes and suppliers based solely on the data available within the considered company – for example, through Ariba, SAP LBN, SAP Integrated Business Planning, and integration into the SAP Manufacturing Cloud. The result would be a more resilient supply chain for the entire company.
At this point, indeed, SAP possesses a strong unique selling point: While other software providers rely on elaborate integration tools or even CSV interfaces, SAP could directly access company-specific data through the Business Technology Platform.
Joule would be an important front-end tool that makes the underlying complex AI application easily manageable. SAP Joule becomes particularly intriguing when it transcends the role of a mere assistant that only reacts to queries. Instead, leveraging additional underlying AI applications, Joule could even proactively signal areas needing attention and articulate them in natural language through its LLM (Large Language Model).
Bottom Line
With Joule, SAP will take a significant step towards significantly narrowing the gap with competitors in artificial intelligence. If a meaningful integration with actual business-relevant and company-specific data is established, along with the integration of additional AI applications, Joule will prove to be a robust assistant in the daily workflow for material planning, procurement control, and operations management within SAP software.
