Earlier this year, Muhammad Alam was appointed to the executive board of SAP SE to lead the SAP Product Engineering board area, succeeding Thomas Saueressig in the role amid a key transition that will find Saueressig heading a new Customer Services & Delivery board area focused on cloud growth and adoption.
After spending two years as the president and chief product officer for SAP Intelligent Spend and Business Network, Alam brings a wide range of experience to his new role; previously, he spent 17 years at Microsoft. Alam joins the SAP executive board in the midst of a major transition for SAP. As the software company continues to emphasize the importance of cloud migration for on-premises customers, SAP recently renewed its focus on artificial intelligence (AI) for the world of business. As SAP seeks to expand and innovate in cloud and AI spaces, it also is deep in the process of migrating its customer base from SAP ERP Central Component (ECC) to SAP S/4HANA Cloud.
ASUG sat down with Alam to discuss his new role at SAP. During this second part of our conversation (you can read the first part here), we discussed SAP’s approach to AI, the trends shaping SAP product engineering, and SAP low code/no code solutions.
This interview has been edited and condensed. This is the second part. You can read part one here.
ASUG: Let’s talk about AI, which is at the top of everyone's mind, especially in the SAP ecosystem. SAP recently shared many announcements and investments related to generative AI. How does SAP plan on differentiating itself both on the business and application side of AI from its competitors?
Alam: AI—and generative AI in particular—has progressed significantly in recent years. In fact, I think AI has been on the hype cycle for many years, but now, it’s delivering tangible results. It’s created a willingness—and anxiousness, to be frank—in our customer base to quickly innovate with Gen AI and other available AI tools. It is a unique environment the technology has created.
SAP is different, from a value differentiation perspective, to our customers in several meaningful ways. First, to enable AI, you must have data. And data is what SAP and our customers have across business processes. I’d argue that very few companies in the world possess that scope of data. So, this ability to apply AI on top of that data to create additional insights, along with predictive and autonomous capabilities is, I believe, up to SAP to unlock. How do we unlock that data for our customers in a secure, privacy-compliant, reliable, and relevant manner?
We’re also looking at how SAP customers are leveraging AI. You need AI embedded in daily processes and applied on top of the data available in the applications that you use. That's something we can uniquely do because we have hundreds of millions of users leveraging SAP applications and they want that interaction to be intelligent.
With both of my previous points, we can unlock increased productivity and efficiency scenarios. But then there's also a set of high-value scenarios that just wouldn't have been possible without AI. For example, in terms of supply chain resiliency, how do you plan across an enterprise and how do you think of benchmarks for predictive and autonomous capabilities? It's about taking the data to create unique insights, embed them in context, and create differentiation. The real value is not just increased productivity and efficiency, it’s productivity, efficiency, and high-value use cases, and uniquely SAP can bring all three together.
ASUG: How is SAP ensuring that we can trust AI tools to perform as they are instructed and expected to perform?
Alam: This is critical. And this is a differentiating factor for SAP, because the data that our customers have on top of our applications is some of the most sensitive, and in some cases, most regulated data that they possess. How do we create trustworthiness and privacy for customers to feel confident about working with AI? This is where we go back to reliable, relevant, and responsible AI, which is ingrained in the core of the AI scenarios we’re enabling. How do we make sure that the data itself is available in a secure, privacy-focused framework that not only improves the accuracy and generates more relevant content, but also takes out the hallucinations that sometimes are present in public models?
The other question we are asking ourselves is how we ensure we can leverage the models without providing the public models with customer proprietary data. We take great pains to create separation there. But then, of course, some of our customers have enough data, that they can just have a model learn in their own tenant for their own value. Enabling that function creates a unique value proposition for our customers. Ensuring SAP is reliable, relevant, and responsible in the use of data and AI is priority number one for us.
ASUG: How would you assess the major trends shaping the direction of SAP product engineering? And what are some of the key factors influencing the direction of SAP innovation?
Alam: We’re looking at how we can unlock the power of data and then apply AI on top of it to create differentiated value. When I listen to our customers and think about the potential of incremental value that data and AI can create, I think it's limitless. In every part of our product engineering organization, we have massive amounts of mental, product management, and engineering energy focused on creating these embedded, contextual, reliable, and relevant scenarios for our customers.
In many parts of our portfolio—automatic table maintenance with SAP SuccessFactors, for instance—we have AI capabilities in the application that our customers are excited about. It's already much further along than what they see from our competitors. Similarly, in our SAP Intelligent Spend solutions, the modern experience we’re creating with SAP Customer Experience, the public cloud scenarios with Joule, our co-pilot, and the list goes on, our customers are impressed with our SAP Business AI solutions.
ASUG: One of the main issues in the SAP ecosystem—and in the IT ecosystem at large—is the growing skills gap. In your position, you oversee the way SAP customers actually interact with SAP solutions. How is this issue influencing the way you approach product engineering?
Alam: We’ll go back to AI because that has the potential to allow people to create efficiencies and acceleration in the work they are doing, so they can do more work as well. If you make tasks simpler and quicker to complete, you can do more of that work in the same amount of time. It also enables us to address more customers, too. So, there's a lot of energy in SAP BTP, with ABAP Cloud, where we bring the power of generative AI to create an acceleration of the skills that exist in the SAP ecosystem.
From a product and engineering perspective, we’re focused on ensuring that we—particularly in the cloud world—build the capabilities, use cases, and scenarios that are easy and quick to deploy. That speeds up the value for our customers while also decreasing the stress and pressure we put on the ecosystem to do long implementation cycles. We want them to be shorter and more predictable. And now we can devote more effort to higher value, advisory-type capabilities, as opposed to just the mundane. Internally, from a product perspective, having this mindset that you should be able to adopt and start using things as quickly as possible is vital.
From an SAP perspective, there's a significant amount of energy expending and making material collateral, training, and skill sets available to our employees, customers, and partners. We can grow the ecosystem as aggressively as possible. AI allows us to release more relevant materials and provide more relevant feedback and insights to that broader growing ecosystem.
ASUG: In recent years, SAP has invested a lot in its low-code/no-code solutions. What are some ways you plan on continuing to expand the functionality of these options?
Alam: We announced SAP Build Code at SAP TechEd 2023. In April 2024, it became generally available to all developers around the world. This provides AI-based code generation with SAP’s copilot, Joule, optimized for Java and JavaScript. With low code/no code—going back to one of the things we discussed earlier—the breadth and depth of business processes are so wide. We're trying to bring the experience together, both from an integration and user perspective. Extensibility, in my mind, is another facet of this same topic. If you look at this portfolio, and if a customer wants to do something unique, they look to their business processes. They should be able to leverage our low code/no code to make their processes unique. Having this tool as the natural extensibility layer across our applications is one of the things driving both adoption and integration across our products. From a customer perspective, these solutions also give them one place to go and think about how to make their applications fit their specific needs.
ASUG: What are you excited about in the coming months, both as it applies to your new role and the overall direction of SAP?
Alam: Learning! That excites me the most, personally. There's just so much learning ahead, again, across those three pillars: people, product, and our customers and partners. I’m excited to be refining the right strategies and focusing on the right things to make an outsized impact for our customers, SAP, and our shareholders. As we’ve discussed, I’m also thrilled about figuring out how to take the amazing set of SAP products and the data that it creates and apply AI on top of it to build impactful value for our customers in a way that nobody else can. Along the way, I look forward to creating an employee force and set of colleagues who are excited, energized, and looking to learn as well.