AI is becoming the backbone of decision-making and customer engagement in business. This emerging reality was the focus of a recent episode of the CLARITY.SHOW podcast, hosted by Karyna Mihalevich.
In this conversation, Karyna, AI Stream Lead and SAP Intelligent Enterprise Ambassador, sat down with Vivien Boche, Senior Director at SAP’s Business Technology Platform, to explore how AI is shaping the enterprise environment and discuss several real-world AI applications.
AI as a Strategic Business Catalyst
According to the podcast guest, SAP sees AI not as a separate tool, but as an integral part of its core business processes across a wide range of industries. This approach is built on SAP’s strong background in SAP ERP systems and its focus on improving business operations.
Vivien Boche explains the strategy: “Our goal is to make AI not just accessible but meaningful within the 27 industries we serve. This involves identifying where AI can enhance efficiency and effectiveness – such as in the hire-to-retire process – while adhering to the three guiding principles: relevant, reliable, and responsible AI.”
- Relevant: AI should focus on solving real business challenges, delivering answers and insights that directly align with the enterprise’s needs, not irrelevant or unrelated information.
- Responsible: AI must adhere to established ethical guidelines, company policies, and industry regulations, ensuring trust and accountability.
- Reliable: AI solutions should be accurate and consistent, avoiding errors or hallucinations, and providing dependable outcomes rooted in business data.
This vision is closely connected to SAP’s Business Technology Platform (BTP), which Vivien Boche described as the tool that helps businesses bring AI into their daily operations. BTP makes it easy to integrate AI into existing systems, helping businesses adapt to changing market conditions with real-time data and predictive insights that allow leaders to make smarter, faster decisions.
Vivien also pointed out that SAP doesn’t just offer ready-made AI solutions – BTP gives businesses the tools to build their own AI systems too. This approach allows businesses to either use pre-built AI features or customize them to meet their specific needs, making AI adoption more flexible and effective.
Architecture for Rapidly Evolving AI Landscapes
In their conversation, Karyna and Vivien shifted from discussing the broader vision of AI to exploring the more technical aspects of how businesses can implement these innovations effectively. One key concept that emerged is the importance of adopting a composable architecture – a software design approach that emphasizes modularity, scalability, and adaptability. Composable architecture involves building applications as a collection of independent components, each with a specific function. These components can be combined, replaced, or scaled independently without disrupting other parts of the system.
- Composable ERP: SAP enables enterprises to integrate multiple SAP solutions and third-party applications within a single framework.
- Scalable Solutions with BTP: BTP offers elastic database capabilities through SAP HANA Cloud, ensuring enterprises can scale AI initiatives without overhauling their infrastructure.
- Accelerated Prototyping: SAP’s focus on low-code/no-code tools empowers users to rapidly develop prototypes, reducing time-to-value for AI projects.
With this composable architecture, businesses can build what they need using a Lego-like approach, solving problems at their pace.
AI Implementation Challenges & Solutions
Adopting AI in business often faces roadblocks, particularly regarding data readiness and security, as both Vivien and Karyna pointed out. Based on their conversation, it’s possible to identify three key challenges and potential solutions in AI implementation. These include:
1. Harmonizing Data in Complex Landscapes
Challenge: Enterprises typically operate with diverse applications and siloed data. Consolidating this information into a usable format for AI without losing semantic richness is critical.
Solution: SAP DataSphere uses a data federation approach, preserving context while unifying data. This enables organizations to create robust datasets without duplicating or degrading data quality.
2. Ensuring Security and Governance
Challenge: AI solutions require stringent data privacy measures, especially in sensitive sectors like government or finance.
Solution: SAP offers built-in security frameworks and policies on BTP, including advanced data masking and agreements with LLM providers to prevent data storage or retraining. Additionally, tools like SAP Master Data Governance ensure data consistency and compliance.
3. Choosing the Right AI Model
Challenge: Enterprises often struggle with identifying the most suitable LLM for their specific use case.
Solution: The Generative AI Hub allows users to compare and switch between models, facilitating a flexible and exploratory approach to AI adoption.
Looking Ahead: The Future of AI in Enterprise
As the episode drew to a close, Boche shared her vision for the future of AI in enterprise. The future of business is being shaped by AI agents, and SAP is leading the way in this area. AI agents are like smart assistants designed to handle specific tasks on their own.
“AI agents are autonomous, they interact with their environment and can reason through multiple steps to achieve a particular goal,” Vivien said.
For example, one agent could help with scheduling and planning, while another might be better suited for reading and sorting emails or managing invoices. These agents are trained to perform certain tasks efficiently and independently. SAP’s vision for what they call “autonomous enterprises” is all about having these specialized AI agents work together to automate business processes.
Boche added, “At TechEd, we launched a dual studio where businesses can create their own AI agents. It’s like a toolbox where you can build an agent that suits your needs.” The idea is that businesses can activate agents for specific tasks, like finance or customer support, and let them work in the background.
“You wake up in the morning, have your coffee, and by the time you sit at your desk, the agent has already identified problems and suggested solutions,” she explained. This kind of automation could drastically improve efficiency, and with SAP’s tools, businesses can either use pre-made agents or create their own to fit their needs.
The Bottom Line
According to Vivien, the gap between companies using AI and those not using it will become increasingly evident over time. The expert stressed the importance of businesses staying ahead by defining a clear AI strategy and making informed decisions about where to invest.
By focusing on areas where AI can bring the most value and measuring its impact with concrete numbers, businesses can make better decisions about where to allocate their resources.
“Don’t be the next Nokia,” Boche warned, cautioning against falling behind as technology continues to evolve.