On Artificial Intelligence

A series of articles on the topic of Artificial Intelligence and business

When small is beautiful

In the search for the ‘winners’ of the AI race, Chinese and American companies are often the usual suspects. Yet upon closer inspection, smaller nations like Israel are thriving amongst these digital giants. But how – and why – has it succeeded where others have failed?

China got AI right, but did we get China right?

Chinese President Xi is determined to bring the power of artificial intelligence into Chinese people’s daily lives and work to reap the full economic and social benefits of innovation. So far, so good.

The problem with digital: zebras, horses and unicorns

Recently, a group of faculty was part of a delegation from IMD to visit a number of digital start-ups in Israel, a country at the center of high technology innovation. One of them was called Zebra Medical Vision, a company that develops technology for reading medical scans. When we asked about the rather unusual name, we were told that it is a play on the saying, “When you hear hoofbeats, think of horses not zebras.”

Artificial intelligence: one area where startups can teach established firms

Firms with a solid past may still be inventing as well as ever, but they need to look up to startups when it comes to implementing their AI. During the last few years, immense hype has built up around artificial intelligence (AI) and machine learning. Thought leaders and industry captains alike have been hailing them as inventions that will transform humanity.

Beyond algorithms: the impact of AI and ML on organizations

As companies are increasingly seduced by the siren call of data science, there is a strong need to understand what it does and what it does not contribute to business. ML/AI developers do not understand and/or address the organizational implications of their technological ideas. (in Chinese)

Learning through bonding and bonding through learning

In early 2020, five colleagues and I visited Tel Aviv and Jerusalem to expand our knowledge and understanding of artificial intelligence (AI) and machine learning (ML). Specifically, we wanted to discover what was real versus what was hype, and then understand how and where this mattered for business.