How to Integrate AI into an Enterprise System?

We hope that you all had a relaxing summer and recharged with fresh energy and inspiration for your work. In this and several upcoming posts, we return to what is currently the biggest trend in innovation—solving business challenges using AI. In the past, we approached AI more from a theoretical perspective. However, since our BTP.Team at ORIWIN, s.r.o. continued working at full speed throughout the summer, theory has now turned into reality. Today, we already have our first real-world experiences and solutions using SAP Business AI, which is fully integrated into enterprise information systems through the SAP BTP platform.

SAP Business AI is a technology built specifically for business use. Therefore, AI in the enterprise comes with significantly greater potential—but also greater risks—than its use by individuals. That’s why security, compliance, ethics, and trust are key pillars of Business AI. Without these attributes, using AI in business would be more of a gamble than a benefit. To effectively harness AI in a business environment, a company must first establish a verified and reliable IT environment that meets these critical requirements.

SAP AI technology provides pre-built and embedded AI services across many standard SAP products, eases the user experience through the generative AI assistant “Joule,” and offers unlimited solution potential through AI Foundation services on the SAP BTP platform. One key component of this platform is the Generative AI Hub—a BTP service for exploring various LLM (Large Language Model) options.

👉 Generative AI Hub helps accelerate the development of any generative AI applications on SAP BTP. It gives developers instant access to a wide range of LLMs from various providers, such as GPT-4, GPT-3.5 from Azure OpenAI, Llama 2 from Meta AI, or open-source models like Falcon 40B, among others. Once a custom AI service is created, you can select different AI providers and models for it. This flexibility is extremely valuable, especially during testing, as it allows you to identify the model that delivers the best results and the most cost-effective performance. This is a key business factor, enabling companies to build not only effective but also economically sustainable AI solutions. The ability to easily switch between LLM models in a unified environment offers tremendous flexibility in both the design and operation phases of innovative business AI solutions. As you might expect, running AI models—especially with a high number of requests—incurs costs. Therefore, the economic viability of the entire solution becomes a critical element that can impact the success of the AI-driven innovation.

For comparison: using a simple wheelbarrow to move a small pile of dirt makes perfect sense, while transporting a rare and valuable painting might call for an armored vehicle with a security team. Sure, the armored truck could carry the dirt too—but doing that for a whole month would be wildly uneconomical 😊.

👉 The good news is that AI technology is now truly available for enterprise information systems, and companies can begin using AI-driven innovations immediately. Our BTP.Team has spent the summer preparing the first AI models and solution examples so we can gradually introduce you to these innovative capabilities. Based on our experience, we are confident that AI technology can deliver real business value, and we’re excited for our customers to test and experience these benefits in their own operations.

Whether, how, and when you choose to leverage this breakthrough technology for your business is entirely up to you.