Agentic AI is redefining how businesses operate, blending automation with decision-making in ways that were once only imagined. As enterprises strive for greater efficiency and intelligence, AI-powered agents are stepping in to handle complex workflows, enhance data-driven insights, and optimise operations. But how does this technology truly work, and what does it mean for the future of enterprise software?
To explore these questions, we spoke with Bulut Altintas, Senior Solutions Advisor at SAP UAE, about how SAP is integrating Agentic AI into its solutions, the industries that stand to benefit most, and the challenges of scaling AI-driven automation. Kasun Illankoon, Editor-in-Chief of Tech Revolt, reports on this exclusive discussion.
________________________________________________________________________
How does SAP define Agentic AI, and what makes it different from traditional AI models?
At a high level, AI agents are digital systems capable of performing tasks independently, often in a dynamic, adaptive way. They are a new breed of technology that can think, plan, and act in ways we have only recently begun to realise.
The rise of generative AI has made these agents even more powerful, moving beyond basic automation and revolutionising our technological interactions.
Foundation models, which are the backbone of generative AI, allow these agents to handle more complex and varied types of data, creating outputs such as code, text, or even media that are highly contextualised to the task at hand. This ability to process and generate diverse data types enables agents to reason and operate autonomously at a much deeper level.
With these enhanced capabilities, agents can now manage more complicated, irregular problems involving multiple steps, producing solutions independently and effectively.
What key industries stand to benefit the most from Agentic AI, and why?
Agentic AI holds transformative potential across all industries, as automation and augmented decision-making are essential for enhancing efficiency, accuracy, and innovation. The ability of AI agents to learn, adapt, and scale makes them invaluable for organisations seeking to optimise operations, reduce costs, and enhance customer experiences.
How is SAP integrating Agentic AI into its existing enterprise solutions?
We are transforming enterprise software by combining SAP’s process expertise with leading-edge AI capabilities. Our AI agents are designed to streamline and automate cross-system tasks, making everyday operations smarter and more efficient.
By integrating context-aware automation with decision support, we are setting a new standard for business process automation and smart decision-making. Joule, SAP’s AI co-pilot that truly understands businesses and revolutionises interaction with SAP business systems, is at the heart of this transformation, bringing our AI agents seamlessly into our data and workflows. This integration enables us to tackle complex tasks with ease and adaptability.
As we grow, so can scenarios, evolving from basic to more advanced agent capabilities. When you interact with agents through Joule, you can rely on smooth experiences with existing scenarios and functions, making interactions intuitive and powerful.
What are the biggest challenges in deploying Agentic AI at scale?
Deploying Agentic AI at scale brings challenges such as ensuring business process contextualisation, data accessibility, scalability, collaboration, and reliability. SAP addresses these challenges with Joule AI Agents by grounding them in 50 years of SAP’s business process expertise through the SAP Knowledge Graph, enabling them to solve complex, cross-functional problems. Additionally, they access all relevant data via the SAP Business Data Cloud, providing a single trusted data layer for accurate, context-aware decisions. With a library of over 1,300 prebuilt skills, Joule AI Agents automate complex workflows across SAP and third-party applications, working collaboratively rather than in isolation.
By integrating knowledge, data, and skills, Joule AI Agents achieve unmatched precision, scalability, and reliability. A powerful illustration of these capabilities can be seen with Bosch, which integrated a Joule-powered case classification agent in SAP Service Cloud. This deployment replaced hundreds of routing workflows with a single prompt, significantly improving accuracy, reducing manual effort, and accelerating resolution times.
How does Agentic AI enhance automation and decision-making within business processes?
Advancements in generative AI have enabled today’s agents to go beyond simple automation, tackling multi-step tasks with greater autonomy and flexibility. Agentic AI delivers business value through two key dimensions: business task automation and business decision augmentation. By automating repetitive, rule-based tasks, Agentic AI significantly reduces human workload and enhances operational efficiency. At the same time, it augments decision-making by providing data-driven insights and strategic recommendations, enabling businesses to make more informed choices and drive better outcomes. This dual capability of automation and enhanced decision-making makes Agentic AI a powerful tool for improving efficiency and effectiveness across various industries.
What security and ethical considerations come with implementing Agentic AI?
Implementing Agentic AI requires strong security and ethical measures to ensure data privacy, prevent biases, maintain transparency, and provide human oversight. As AI systems become more integrated into business processes, organisations must adopt ethical frameworks that prioritise fairness, accountability, and safety, while complying with legal regulations.
From our perspective at SAP, we emphasise a high standard of AI ethics, data privacy, and security to uphold human agency and oversight. Our approach includes a comprehensive governance structure for AI development, providing guidance for high-risk use cases and ensuring alignment with global governmental policies such as the EU AI Act. We have established an AI ethics framework designed to foster a fair and transparent society by implementing binding ethical principles for all our employees and partners. Additionally, we employ strict data usage policies, advanced anonymisation techniques, and robust governance controls to protect customer data. Our security practices adhere to the NIST Cybersecurity Framework, incorporate secure development lifecycles, and utilise proactive threat management to ensure the safe and responsible deployment of AI.
How do you see Agentic AI influencing supply chain management and ERP systems?
Agentic AI is set to significantly influence supply chain management and ERP systems by enhancing efficiency, responsiveness, and decision-making capabilities. In supply chain management, Agentic AI can optimise operations by analysing large volumes of data to forecast demand, manage inventory, and streamline logistics. It enables proactive identification of potential disruptions, allowing businesses to adjust supply chain strategies swiftly. Within ERP systems, Agentic AI enhances automation and integration across business processes. It can automate routine tasks such as data entry, financial reporting, and order processing, freeing human resources for more strategic activities.
SAP’s integration of Agentic AI into supply chain processes and S/4HANA creates adaptive systems that dynamically adjust to changing demands, enhancing resource planning and operational efficiency. A powerful example is service agents, which are more productive and save up to 70% of time managing service tickets with next-generation service automation in the new SAP Enterprise Service Management solution.
What is SAP’s vision for the future of Agentic AI in enterprise technology?
SAP’s vision for the future of Agentic AI in enterprise technology revolves around seamlessly integrating AI agents into core business workflows to drive automation, enhance decision-making, and foster continuous innovation. Unlike traditional fragmented automation, SAP’s AI agents operate cohesively across entire organisations, enabling smarter and more efficient operations.
SAP aims to achieve new levels of autonomy by embedding AI into the SAP Business Suite, a transformation engine built on three pillars: Out-of-the-Box Agents that provide immediate value across processes and vendors, Joule Agents leveraging deep business expertise for intelligent decision-making, and Joule as a Central Agent Hub for effective governance and deployment, keeping humans involved in critical decisions. This integrated approach drives continuous innovation and operational excellence.
SAP’s Agentic AI strategy is further empowered by the SAP Business Data Cloud, which plays a pivotal role in enhancing the capabilities of AI agents. The Business Data Cloud serves as a unified data foundation that provides ready-to-use SAP Data Products and integrates and harmonises SAP data from various non-SAP sources, providing AI agents with comprehensive, high-quality data to process and analyse.
