One of the most enriching human experiences takes place in an educational facility. There, students learn soft skills and theoretical background from their teachers, which are the first steps toward becoming a trustworthy professional. Just as students learn and apply knowledge to real-world scenarios, agentic AI systems learn from data inputs to perform tasks autonomously, embodying a modern interpretation of this learning-teaching dynamic. As these systems are designed to achieve complex areas with limited commands, there is a growing demand for tools that learn from input and provide results with thorough reasoning.
Agentic AI Capabilities
Agentic AI combines large language models, machine learning, and natural language processing to carry out autonomous activities on behalf of the user. It is embedded with self-organizing capabilities and self-learning features, which include:
AI-driven support across all case handling stages – It’s intended to be implemented at multiple stages of the case handling process, from information and log collection to triage, troubleshooting, analysis, and action recommendation.
Enhanced efficiency and experience - The goal is to considerably reduce customer effort and engineer workload while improving case resolution times and overall satisfaction.
Automation of repetitive tasks - Repetitive tasks such as writing emails, summarizing cases, and searching for past solutions are automated with AI, allowing agents to focus on problem-solving. Within SAP systems, it can analyze situations, formulate strategies, and execute actions autonomously using SAP Build Process Automation. Just as budding professionals apply tools and methods for learning, agentic AI accelerates task proficiency by providing real-time, context-aware answers to new support engineers. This capability narrows the distance between knowledge acquisition and effective application.
AI-assisted communication - AI-assisted responses help agents craft clearer, more customer-friendly messages, leading to stronger customer satisfaction. AI-generated responses also allow agents to maintain the right tone and empathy in emotionally charged cases and helps non-native speakers communicate more clearly.
Proactive and preventative support - AI is used to detect and resolve system issues proactively. Preventative Customer Care is expanded across all products and integrated with PARIM to bring a true end-to-end Preventative Risk Identification, Risk Mitigation, and Risk Tracking solution.
Flexible architecture - A flexible architecture is in place for consumption of the upcoming SAP Agentic Framework. Based on perception, decision-making, learning, and action components, it enables adaptation over time through implementation of safety measures through monitored performance.
Continuous improvement - There is an evaluation of current existing data, data pipelines, and AI Services to identify areas of growth and continuous improvement.
Best Next Action recommendation - Agentic support offers engineers the ability to get Best Next Action recommendations from a chain of agents and trigger agents at will using prompts to solve cases. The overarching aim is to introduce AI and automation to offer intelligent insights and reduce engineer effort on case resolution. It doesn’t replace human support but rather augments their capabilities, making the learning-teaching dynamic more effective and efficient in the digital age.
Smart response capability - The implementation of smart response capability offers AI-generated responses to selective customer cases, to reduce the volume of cases processed by engineers and enable deflection of cases through Smart Respond. The aim is to auto-respond to selective cases, and constantly increase the proportion of cases that we can Smart Respond to by deriving the confidence from responses offered by engineers to trivial cases, where they are using the Best Next Action recommendations, as-is.
While generative AI primarily creates content, agentic AI focuses on decision-making and actions, making it action-oriented. Furthermore, this customer-centric approach provides nuanced, conversational support beyond traditional chatbots, and offers personalized recommendations and experiences.
The Path Ahead for Agentic AI Integration
The foresight looks promising, with developments for agentic AI in SAP products that encompass:
- Connection of support agents with self-healing and reasoning agents to fix issues automatically.
- Improvement of natural language interfaces with SAP products, allowing real-time insights about business processes.
- Integration with emerging technologies like Internet of Things and blockchain.
As in an educational system, agentic AI is set to learn from data to make informed decisions. At SAP Sapphire 2025, to take place in Orlando and Madrid, we’ll showcase how our agents identify and mitigate risks to prevent business impact to customers, as we point towards a future of seamless integration between learning and problem-solving skills.
A special thanks to Bharath Ramamurthy, Vice President of Strategic Initiatives, Customer Support, and Tarun Luthra, Global Head of Technical Support, Industries & Customer Experience, SAP experts who have contributed to this article.
