Embrace the Generative AI revolution: a guide to integrating Generative AI into your operations
Generative AI (GenAI) is not just the topic of the hour – it may well be the topic of the decade and beyond.
Generative AI (GenAI) is not just the topic of the hour – it may well be the topic of the decade and beyond. Until a year ago, when people suggested that AI was already mainstream and asked what the next big thing would be, I replied that we had not reached the end state of AI yet.
All of us have experienced this with ChatGPT – the conversation has shifted completely. With relevant, reliable, and responsible Business AI, we can use this new toolbox to drive innovation, enhance efficiency, and redefine industries.
As CTO of SAP, I witness firsthand the potential business benefits and ground-breaking use cases that GenAI brings to the table. However, with this transformative technology also come questions that keep tech leaders awake at night. Let me share some of my experiences and learnings to provide actionable insights on navigating the GenAI revolution.
First, a clear vision and strategy for integrating GenAI is essential. It is crucial to pinpoint where and how GenAI can generate tangible business value and how your customers will interact with it. At SAP, we want to support everyone who regularly works with our cloud solutions, with Generative AI – currently, approximately 300 million people.
How will companies consume GenAI capabilities? I am convinced that built-in GenAI is the way to go. In our case, it makes most sense to embed GenAI capabilities into our SaaS and PaaS solutions so that customers can benefit from promising use case patterns such as summarization, crafting job descriptions, and analyzing data. Just this week, we announced Joule, our own GenAI copilot which will provide AI-powered insights and assistance throughout our cloud enterprise portfolio. Joule is embedded in our business applications, from HR and finance, to supply chain, procurement, and customer experience, as well as into SAP Business Technology Platform. Knowing a user’s unique role, Joule can streamline tasks and generate the needed content by simply being asked, e.g., for job descriptions or coding assistance. The answers will be drawn from the wealth of business data spread across SAP’s solution portfolio and third-party sources, retaining context. In short, this copilot will know what users mean, not just what they say.
GenAI models are trained on huge volumes of data. This means that good proprietary data leads to superior GenAI outcomes compared to pre-trained models. At SAP, we have obtained consent from thousands of customers to train our GenAI with their data, ensuring the top-notch quality that is needed in business. We have also implemented federated machine learning capabilities, ensuring that data never leaves customers’ SAP systems.
CIOs are however, understandably concerned about the operational and development risks associated with GenAI. Therefore, stringent technical and process controls must be in place to detect any potential tampering of trusted data sources used for training, fine-tuning, and embeddings. What are your unique data sets?
GenAI represents a powerful new technology that comes with a lot of responsibility. Educating the workforce is essential to apply GenAI effectively and responsibly. Developers and code-writers for example will also benefit from GenAI because it will allow them to describe entire applications through natural language conversations, generate code, refine application logic, and create unit tests. And by taking over standardized repetitive tasks, GenAI will enable employees to focus on more complex aspects of their work. This means soft skills like problem-solving, critical thinking, teamwork, and communication will become increasingly important. In the future, skills in areas such as data science, machine learning, and natural language processing will be in high demand.
As CTOs and CIOs, we must provide resources and strategies to enable employees to thrive. At SAP for example, we have set up an internal ‘AI playground’ that is very popular with employees. More than 80% of our early adopters using GitHub Copilot say it has increased their development productivity. At this year’s SAP TechEd event, we will be announcing tools that will help our customers do exactly that as well.
This is one of the most exciting times in my 25 years in the technology space. I can’t wait to see how the GenAI revolution will unfold and the impact it will have on businesses and society. When GenAI is used responsibly, it can improve the lives of all of us.
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