UTM appointed Zack Kass to advise its AI faculty—here's what he told Malaysia

Universiti Teknologi Malaysia brought Zack Kass to its Kuala Lumpur campus in March 2024 as it was building the country's new Faculty of Artificial Intelligence. UTM said Kass had been appointed a Distinguished Adjunct Professor and would advise the development of AI academic programmes as well as contribute to the Malaysia Artificial Intelligence Consortium, known as MAIC.[1]

The appointment began with more than a ceremonial lecture. UTM's follow-up account recorded four sessions across 8 and 9 March for senior guests, about 100 academics, 110 SME representatives and roughly 120 students. The groups discussed productivity, curriculum, entrepreneurship, privacy, security, misinformation and possible job disruption. Those concerns made the visit a useful snapshot of what Malaysian adoption looked like before generative AI became routine in many workplaces.[2]

Kass's public lecture argued that Malaysia could gain from adopting available AI technologies even if it could not compete directly with the largest technology powers. UTM reported his view that faster adoption could support economic and social growth, including smaller businesses, while the university's vice-chancellor connected the faculty's work to humanistic values and ethics.[1]

That distinction matters. Buying access to a model is not the same as building national capability, and neither guarantees a useful outcome. Adoption becomes productive only when an organisation chooses a real workflow, prepares its data, trains the people responsible for it and measures whether the result is more accurate, faster or more valuable than the previous method.[1][2]

The academic session focused on skills and teaching. UTM said Kass encouraged educators to guide students in the use of AI tools and consider how those tools could support curriculum delivery, research and routine functions. The SME session shifted to business operations and efficiency, while the student session explored entrepreneurship, privacy, security and how education might change over the following decade.[2]

The audience split is more useful than a single broad AI seminar because each group owns a different part of adoption. University leaders set academic policy, lecturers design learning, business owners decide whether a use case can pay for itself, and students must learn to evaluate outputs rather than merely produce them. A shared vocabulary helps, but each group needs its own operating rules and evidence.[2]

UTM's reports attributed several forward-looking claims to Kass, including expectations about advanced AI, scientific progress and major changes to work. The same reports also recorded warnings about misinformation, displacement, privacy and security. These are expert views presented during the programme; they should not be read as guarantees or as evidence that any particular milestone was achieved.[1][2]

The more durable takeaway is the call to combine technical adoption with human qualities and oversight. For a Malaysian institution, that means naming who checks an AI-assisted decision, how errors are escalated, what data the tool may access and which result will prove the project worthwhile. Without those controls, enthusiasm can create activity without capability.[1][2]