An increasing number of C-suite executives recognize the importance of leveraging AI not only to achieve business objectives but also to stay ahead of competitors and tap into long-term opportunities. In this interview, find out more details from leadership perspective also on how to build an AI centre of excellence.


Interview with Dalith Steiger-Gablinger, Co-Founder of Swiss Cognitive, World-Leading AI Network


In this video interview Swiss Cognitive’s co-founder, Dalith Steiger joins Kim Koszuszeck at Meta Znüni Episode 41 and sheds light on the key levers to unleash Artificial Intelligence in businesses.



Interview topics

– Key levers to unleash AI in Business
– How to set up an AI Centre of Excellence
– Tips & Guidance on how you can approach the topic AI as a business leader in Switzerland


00:28 – Kim: “AI is one of the passwords that every CEO talks about today. Also, our Meta products leveraged a lot of AI-based technology. I would love to hear a little bit more from you, and about your work with Swiss Cognitive, and also what you see as key levers to unleash AI more in a business context.”

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01:02 – Dalith: “Just to start before I am digging into the question: we actually rather talk about “cognitive technology” than “AI” because for me artificial intelligence is kind of misleading. If we’re talking about artificial joints, artificial, organs, even artificial plans, we think about something that is as natural as possible. But at the end of the day, if we’re talking about artificial intelligence, we are still not seeking to copy the human brain.”

02:01 – Dalith on Swiss Cognitive: “We are a cross-industry, global community of business leaders and AI experts transparently exchanging about the development and implementation of AI. We’re not a techy community. We’re about business-related, down to earth use cases. No sci-fi and no Terminators. While spotlighting hands-on use cases, challenges, successes, and opportunities, both in the boardrooms and also on global stages, we are driven by turning AI into a key economy booster.”

02:58 – Dalith: “By listening to other experts from across industries, how they adapt, how they implement and how they develop their use cases with AI, you can think a step further and think of ways how you can adopt AI in your own industry and business. In a way, we let experts think outside of the box. Our “share for success” motto is however not only about best practices but also about worse failures.”

03:50 – Dalith: What does it mean to unleash the potential of AI in businesses, especially for C-suit executives and also how to build an AI centre of excellence? It is core for companies to be able to advance. By using AI they can advance in a sustainable way. An increasing number of C-suite executives recognize the importance of leveraging AI not only to achieve business objectives but also to stay ahead of competitors and tap into pioneering long-term opportunities. The fear of becoming irrelevant in the industry if AI is not being incorporated is increasing. But just to implement AI just for the sake of AI, doesn’t make any sense. The risk of getting trapped in the proof of concept loop is high.”

05:25 – Kim: “I like two points that you mentioned: The expectation management, so AI is not a one size fits all. And also moving from a proof of concept to a use case that can ultimately drive and help the business.
To make it a little bit more concrete, we can talk about one or two of those use cases that you’ve seen being implemented successfully. I used to live in China and I remember I wasn’t speaking Chinese, so communication with other people was quite difficult and involved a lot of hand gestures. And that’s a use case I’m very fascinated about how AI can help to translate to a different language while you’re speaking with another person.
We’d love to hear if you have one or two examples where AI was not only a proof of concept but really became a clear use case”

06:30 – Dalith: “There are quite some, I must admit, Sometimes people tell me when we’re talking about Siri, Alexa that it doesn’t really work. And I say, it always depends on the angle that you look at. AI and cognitive technologies are like children, they are learning systems. There is no talent born, even not technology, so these technologies need to learn. The more you’re working with it, the better results you’re gaining. All the successful use cases came a long way and they had their pitfalls and their obstacles, and this is what we need to be aware of. ”

07:50 – Dalith: “One of the most important examples for me from healthcare is a personal one, as unfortunately, my mother had breast cancer during COVID. I dug a little bit more into this technology and all the possibilities and had some very interesting discussions with experts, looking at the possibility of prevention and early prediction of breast cancer. This is so important. Here we are talking about image recognition where the system is only learning yet. I must tell you if you get such a result for your beloved one, that’s really, really tough. And there you think of why can’t we just predict this earlier? Why so late?”

8:58 – Dalith: “Other important use cases within healthcare: supporting disabled people, blind people who are suddenly being able to code. Or people with Parkinson’s disease who are suddenly able to write and draw again. Or another really interesting use case is about the early prediction of reduced vision in children, even in newborns who can’t talk and can’t express themselves.
There are a lot of other use cases around healthcare, around the sustainable development goals of the UN about poverty about education, accessibility, global accessibility for education, I could go on for ages”

10:26 – Kim: “This kind of technology already has an impact on our daily lives and that’s not an understatement at all. I know you do a lot of articles about what are the common misconceptions, but also how AI already helps today to really draw some of the most important courses, that are happening all around the world. Thank you so much for sharing that. I think we could talk for another 20-30 minutes, but the attention span as we like to say on LinkedIn is limited, so thank you so much Dalith, for being here and sharing your insights.”