SAP Labs’ top four ways generative AI is improving business

As AI models, particularly deep neural networks, can be complex and difficult to interpret, trust and adoption can be hindered as well as implementation can be perceived as costly for smaller companies. The AI industry is also facing a shortage of skilled professionals, making it difficult to find and retain talent. As more users engage with ambient technology applications, both hardware and software, it will put increasing pressure on brands to rethink their digital experiences to accommodate how their customers interact with them.

Moving Forward with Trust at the Center

These protection systems safeguard your application through content moderation, input validation, and output verification protocols. Like a modern vehicle’s advanced driver assistance systems, these controls actively monitor operations, detect potential issues, and prevent harmful outputs. This layer includes governance policies, bias detection, content filtering, and comprehensive audit logging—all working together to ensure your GenAI application operates safely and reliably within defined parameters. To build trusted GenAI applications, you need multiple layers of protection working together—similar to how modern vehicles combine various safety systems, from structural safeguards to advanced collision prevention. The latest and greatest grocery shopping experience is a digital one, using platforms like Instacart or retailers’ websites to order, purchase and often deliver groceries. This digital experience saves time compared to physically going to the grocery store and can be further streamlined with features such as saved items and automated repeat orders.

In Deloitte’s latest report, Building and Maintaining Health Care Consumers’ Trust in Generative AI, the findings underscore the critical importance of trust in harnessing the transformative potential of generative AI (gen AI) in healthcare. The rapid advancement of generative AI (GenAI) is fundamentally reshaping the modern workplace, creating new businesses and solutions unlike anything imaginable just two years ago. As users become more and more used to conversational AI technology, they will engage with companies and technology in new and different ways. Conversational AI has the potential to provide information to the user such as job details, job matches and company insights. It would be very useful to have this solution as a preemptive guide for predicting the likelihood of success and candidate-job match before a candidate even applies. “The future belongs to those who can harness the power of data, and at SAP, we are committed to helping our customers achieve that future,” Oren concluded.

• In the second stage, a transformer model is trained to predict the next SID in an input sequence.
• As scepticism creeps more and more into the generative AI discussion, I’ve been trying to gain a clearer view of where real value lies, particularly for tools used directly by end users.
• It would be very useful to have this solution as a preemptive guide for predicting the likelihood of success and candidate-job match before a candidate even applies.
• Machine learning is a subset of AI that focuses on building systems capable of learning from data, identifying patterns, and making decisions with minimal human intervention.
• Conversely, generative AI can enhance machine learning by creating synthetic data to train models in scenarios where real-world data is scarce or expensive to obtain.

ways SAP Labs is using gen AI to improve business (whether for gamers or guitarists)

For startups aiming to break the mold, generative CRM is a goldmine of untapped opportunities. Free from the inertia of legacy systems, these agile companies can integrate advanced CRM right from the start. The new frontier isn’t just about creating a top-notch product; it’s about architecting an entire customer persona. Enter the era of generative CRM—a game-changing paradigm where we don’t just respond to customer needs but anticipate, influence and even invent them. PAIAs will evolve, learning from each individual’s interaction patterns, preferences and feedback. This continuous learning will enable the PAIA to refine its recommendations, ensuring they align closely with the individual’s evolving needs and preferences, thereby fostering more personalized and anticipatory assistance.

• AI can significantly enhance human capabilities by augmenting decision-making and automating routine tasks.
• A player’s interactions with the shop and NPCs around them — from gameplay mechanics to content and dialogue creation — are fueled by AI rather than a predetermined script to create more options for chatting and using objects in the shop.
• Oren’s keynote included an overview of the SAP AI framework, which centers on scaling embedded AI capabilities across an enterprise’s functional areas.
• Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation.

It would be intelligent, intuitive and proactive, and it would provide a far more streamlined experience for users. In short, it would be a digital augmentation of the human being in a way we have never seen before. With this article, since generative AI is something most people can now relate to and understand, I am going to use the technology as a jumping-off point to discuss how companies should be looking to improve user experience in the coming years.

For those who might be hesitant, potentially from older generations, Kenny’s main advice is not to shy away. Instead of fearing or avoiding the technology, he suggests embracing challenges and venturing into the unknown. This is hardly surprising as the emergence of AI, and generative AI in particular, has prompted fears ranging from a decline in demand for humans in creative jobs to a “dumbing down” effect on culture stemming from a surge of AI-generated art.

Bringing AI To Data Management—And Vice Versa

In his recent book The Sound Of The Future – The Coming Age Of Voice Technology, Dengel explores the ways in which the world is likely to change as the final technical barriers to programming and controlling machines come crashing down. Put your brand in front of 10,000+ tech and VC leaders across all three days of Disrupt 2025. This trust will be instrumental in transforming gen AI from a promising tool into a trusted ally in achieving better health outcomes and more affordable healthcare.

These include interfaces for model selection and interaction, systems to manage tokens and API calls, and mechanisms for handling prompts and responses. Your foundation also needs memory management capabilities, performance optimization through caching, load balancing for stability, and basic error handling protocols to ensure reliable operation. The evolution of LLMs continues to expand these possibilities, with newer models offering enhanced capabilities in processing text, images and videos. Another exciting development is the use of multiple models in a network of agents to achieve more complex outcomes with greater levels of automation.

Having learned the lessons from managing massive data sets across its customer base, SAP shows that it understands how AI needs to be accessible in its broad base application portfolio. The approach described by Callens, and reflected in the broader industry trends, suggests that you don’t have to go all-in on AI to reap benefits. Using generative AI as a front-end to enhance the user experience can deliver substantial value, and this doesn’t mean taking away familiar interaction mechanisms that many users will find more accessible or, indeed, more efficient. As scepticism creeps more and more into the generative AI discussion, I’ve been trying to gain a clearer view of where real value lies, particularly for tools used directly by end users. I was therefore in the right frame of mind during a recent briefing with Karel Callens, CEO of Luzmo, who offered some interesting and useful insights into AI’s role in analytics.