Walter Sun joined SAP on September 1 as Global Head of Artificial Intelligence. In this interview, he talks about opportunities for SAP, the importance of academic collaboration, and how SAP is balancing the urgency of innovation with responsible AI.
Before joining SAP, Sun worked for Microsoft, where he led an interdisciplinary team developing business-ready AI and machine learning capabilities. Before that, he also worked at BlackRock Financial Management as a quantitative portfolio analyst and at Apple Inc. as a senior software engineer and scientist.
His applied research includes work in stochastic processes, signal processing, machine learning and deep learning, operations research, and large language models. He has been an adjunct professor at Seattle University and an affiliate faculty member at the University of Washington. He is currently an advisory board member at Georgia Tech.
Walter obtained his PhD in statistical signal and image processing and computer vision with applications in medical imaging from the Massachusetts Institute of Technology.
Q: What is your vision for how AI will shape the future of the IT industry?
Sun: Like with other major technology shifts, such as the breakthrough of the Internet, consumer understanding and adoption pave the way for more rapid business adoption. I think the same thing is happening in generative AI. The rapid consumer awareness of artificial intelligence, especially generative AI, in the past year was largely due to the November 2022 Chat GPT consumer release opening the door for AI and business applications.
Practically speaking, I’m seeing a crawl, walk, run approach to adoption. First of all, business leaders want to see it work. So, they’re going to try it out with close supervision and in smaller, more cautious ways to start.
After they’ve gained some trust, they’ll deploy it more broadly. Later, they will be so comfortable that they’ll use it in all lines of their business. That will be a great opportunity for SAP to help these businesses crawl, then walk, then run through this process.
Where do you see the biggest opportunity for SAP in the AI space?
As a global leader in business applications, we can play a very big role in shaping how businesses adopt AI. It’s very exciting to be at the forefront of technology and also be in a position to do it responsibly.
At SAP, we want to grow trust from our customers. As you know, SAP Business AI is relevant, reliable, and responsible. This position is deeply rooted in adhering to EU data protection laws. We have content filters, data provenance checks, and other features to help ensure accurate and reliable results. Our ethically responsible handling of AI helps ensure that customers can trust how we’re building these capabilities.
We are built for business: we have the deep knowledge and the shipped capabilities to make AI work for our customers. They know what their pain points are, and we can figure out how to solve the problem with technology. This is also about democratizing information for everybody, and we’re democratizing the ability for all businesses – large and small – to use AI.
I think we can use SAP’s unique selling point, which is our access to business data combined with this strong data privacy and protection standards, to get customers to understand that they can trust our technology. With Joule, SAP is already shipping generative AI capabilities and, as we saw at SAP TechEd, we have plans for delivering more both in product and for our developers in SAP Business Technology Platform.
How do we balance the urgency of innovation with the prudence of ethical consideration in the deployment of AI?
I think AI ethics is an extremely important part of our equation. Trust takes years to earn but can be lost in seconds with one failure or one mistake. At SAP, we have made investments in AI ethics to ensure we’re building responsible AI for our customers. This includes fairness, explainability and transparency, reliability, and safety. It also includes having accuracy of information, privacy, and security in place. We also have our SAP AI Global Ethics Steering Committee helping to ensure further safeguards.
If we miss any aspect of this, we run a risk of breaking trust and moving backwards in our fast push to progress. From talking to customers, I’ve been reaffirmed that they want to know what’s going on under the hood.
This is not just for knowing so they can share with their company leaders, but to help everyone be comfortable with generative AI because it is new to everybody. People are a little bit cautious as to what is possible, and they want to know what’s happening.
The more we can explain, the more we show that we have the technology under control, the more comfort people will have in adopting and using it, which then creates that flywheel of more usage, more trust, and more adoption.
How do you view the collaboration between academia and industry?
With any new innovation, having the collaborative effort is really important to move fastest.
As someone who has worked both in academia and industry, I see exciting opportunities in collaboration. At SAP, we want to build bridges, not silos. Let’s acknowledge academic priorities of publishing papers and state-of-the-art science and ask ourselves, “How can we partner so that it is a win-win situation for both of us?”
We collaborate with academic research institutions to understand what state-of-the-art development is in the pipeline. Our role is to provide business knowledge and use cases and then merge that with the research scenarios to identify what could be practically implemented and be valuable to our customers.
SAP’s relationships with many top institutions, such as Stanford, Berkeley, MIT, and Technische Universität München, are really great. Our membership into the Stanford HAI program is a specific example. Beyond the research collaborations, the relationships help ensure that the best graduates from these universities think of SAP when looking for their first job and guarantee that we’re on top of the latest technology.