The News: SAP announced new generative AI capabilities across the SAP Customer Experience portfolio, including SAP’s natural language generative AI copilot Joule, which are designed to improve efficiency and automatically deliver insights that can be used to improve personalized experiences for customers. SAP also announced new AI risk-based authentication capabilities within its SAP customer identity and access management solutions to address critical data privacy and security concerns.
You can read the details about these use cases on the SAP website.
SAP’s New Generative AI Capabilities to Enhance Customer Experiences
Analyst Take: SAP announced in late October several new generative AI capabilities that are designed to bolster efficiency and productivity within commerce, sales, customer service, and marketing teams. These new capabilities, which can be applied across the entire SAP CX portfolio, are designed to leverage SAP’s wealth of experiential and operational data, as well as data from third-party sources, to provide businesses with a holistic view of their customers and offer proactive, contextual, AI-powered insights to optimize business processes.
SAP, like other enterprise software vendors, has realized the value in infusing AI functionality across the entire technology stack, leveraging customer and process data wherever it is held within an organization, to ensure that all teams and functions can benefit from those insights in the form of smarter automation, greater efficiency, and the delivery of deeper, more personalized service.
The key enhancements announced by SAP include:
- Supercharge Catalog Management and Product Discovery with AI
- Automate Labor-Intensive Tasks with Curated Role-Based AI Tools
- Retrieve Answers in Natural Language with Proactive AI
- Surface Customer Profile Intelligence in Context
- Create Personalized Content Creation Powered by Generative AI
- Fortify Customer Identity and Access Management with AI
The generative AI capabilities, use cases, and features mentioned and described in greater detail in SAP’s press release likely will provide significant efficiency and productivity enhancements to customers.
Leveraging SAP’s Massive Dataset to Enable More Accurate AI
Although there are certainly nuances in terms of how each AI use case is enabled, depending on the vendor, the end benefits are generally somewhat similar. The key differentiator with any generative AI capabilities revolves around how well the vendor can properly tailor the use of generative AI functionality with the platform’s own functions and the customer’s data, and that is where large vendors such as SAP often have an advantage.
Indeed, a key benefit of using a platform from a large, enterprise-focused vendor such as SAP is that they have data at scale, which can be used to train and refine their AI models. The millions of interactions that are captured across SAP’s customer implementations can be used to train and refine the model, while obscuring each end-customer’s private information, resulting in more powerful generative AI capabilities, better accuracy, and sharper predictions.
Fortify Customer Identity and Access Management with AI
However, one element from this announcement was particularly interesting. SAP announced that its customer identity and access management solutions are debuting new generative AI risk-based authentication capabilities that secure user identity data and help prevent threats by gaining intelligence across all digital properties and brands.
The use of AI to conduct this type of work is clearly rising in popularity. According to data within The Futurum Group’s Artificial Intelligence & Data Analytics IQ Dashboard, the use of pattern identification, analysis, and decisioning AI is projected to reach $9.5 billion in 2027 annual revenue, up from $4 billion in 2022.
According to SAP, the new risk-assessment generative AI capabilities are applied in the authentication process of end users to their accounts. The aim is to protect against account takeover attacks and uses both the customer identity access management knowledge and analysis of each unique end user’s behavior to assess whether the end user requesting the access is a real user or an attacker.
The ability to conduct real-time risk scoring assessments using AI is particularly valuable to organizations, especially as worker profiles become more complex, thanks to remote and hybrid work arrangements. Relying on humans to spot anomalies and conduct risk assessments is simply too time consuming to scale across an enterprise.
SAP’s AI risk scoring capabilities assesses real-time authentication activities and assigns a risk level based on the deviation from normal behavior, device, and geographic data. For example, if a user accesses their account from their office in Virginia 90% of the time from a registered laptop, and 10% of the time from a mobile device within the US, there would be a higher risk score associated with a login attempt from a non-registered terminal in an airport in Dubai. This approach to managing account risk is automatic, and perhaps most importantly, scalable across an entire distributed enterprise.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
SAP Announces AI Across SuccessFactors HXM Suite
SAP’s Generative AI Copilot, Joule, Coming to SAP Applications
SAP Q3 Revenue Up 4% to €7.74 Billion as Cloud Growth Continues
Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
