In a webinar hosted by SAPinsider and presented by SAP, Robert Holland from SAPinsider speaks to SAP’s Anurag Barua, Executive Advisor in the Customer Success Group and Rob Seifert, SAP S/4HANA Cloud Senior Solution Advisor, about the fundamentals of SAP Business AI and what sets it apart.   There is evidence to demonstrate that AI helps to improve both the top line and the bottom line for organizations; the former through revenue increases and the latter through decreases in cost. The impact of AI is expected to be around $4.1tn over the next three years, equalling the size of the GDP of Germany, and SAP is certainly in pole position steering this bandwagon with more than 27,000 customers utilizing the value of its business AI. The company is proud to have invested more than $1bn in AI that’s designed to be “helpful, honest and harmless.”   There are several success stories bolstering SAP’s confidence, including customers such as Chobani, who have made significant savings through embedded AI in auditing and approving expenses from photos of receipts. Automatically parsed into expense claims, expenses are subsequently audited and approved with minimal human intervention, enabling Chobani’s finance department to gain a single view of spend across the entire business. Another example is music provider Gibson, which has successfully used SAP’s AI to provide personalized journeys and connected all touchpoints to drive customer engagement with Gibson’s content across every channel, paving the way for stable revenue growth. Zalando, a payment services provider processing payments for more than 250 million orders a year, used SAP to develop forecasting for open and unresolved payments that’s twice as efficient.   While SAP employs the whole gamut of AI models and corrective implements, its AI mission remains consistent for Barua and Seifert – the company remains firmly grounded in providing Business AI – in the context of its customers’ unique business data. What’s clear is that SAP is not competing with the vendors of what it calls “general-purpose AI” such as created by Google or Azure.   From the outset, SAP has been unequivocal about the importance of ethics in AI. There’s a human in the loop and SAP applications are, as explained by Seifert, “a place for people to engage, validate and finish the final product you get from AI”.. Deriving value from AI is commonly achieved through natural language interfaces to make interaction easier; automation to reduce repetitive tasks; insights, optimization, and prediction to make better decisions. But, for Seifert, “only SAP can provide all three sources of value.” What SAP has set out to provide is a system of intelligence based on three cores principles - ‘Relevant,’ ‘Reliable’ and ‘Responsible.’ With SAP committed to delivering AI with the highest degree of concern for privacy, security, compliance, AI ethics are playing a big part of the AI use case development cycle.   Now, AI use cases are available across finance, supply chain, customer experience, procurement, HR and IT. Moreover, regardless of the touchpoint or use case, role-based data security is always at play; a user is only ever able to see information that they have legitimate access to.   However, this is not SAP’s first foray into the world of AI – it has catered for “Narrow AI” scenarios in the past such as cand learning recommendations for and automation of Concur invoices. Newly released Gen AI scenarios also allow SAP customer systems to directly liaise with third-party applications. Plus, there are some ‘Premium AI’ use cases for that next level of functionality.   One of SAP’s newer offerings is a one-stop Gen AI Hub in SAP AI Core, that gives users instant access to 20 different LLMs, such as ChatGPT 4, Falcon DB and so on. Users can submit a prompt to multiple LLMs and compare the outputs returned by them.   Meanwhile, Joule is SAP’s AI-powered digital assistant, surfaced either through a conversational interface or in-app Help/Chat/Just Ask options and has been built to be business context-aware. Joule can be accessed within SAP products. E.g., if you’re a recruiter in SuccessFactors, it can give you a set of role-appropriate interview questions that are tailored, logical and free of bias.   Another Gen AI offering is SAP Build Code, a full-blown development environment, currently available for JAVA (and expected for ABAP by year-end), that generates code, automates the creation of data models and produces relevant test cases. Lastly, Just Ask with SAP Analytics Cloud allows users to query data in natural language and returns an intuitive and incisive view of data.   For Holland, Barua and Seifert, Gen AI is increasingly available at your fingertips, especially as a business user interacting with SAP Cloud applications. That being said, “Cloud” is the operative word here as that’s what is affording SAP users access to the contextual business data.