Even though I haven’t done a day’s work outside academia, I’ve been in close contact with those who have. So I’m interested in both the practical side and the more theoretical side of the subjects I work with.
Lasse Lien
Bridging the AI Gap: Lasse Lien on Turning Adaptation into Advantage
Artificial intelligence is evolving faster than most companies can react. Lasse Lien explains what may be Norway’s best path to competitive advantage.
Lasse Lien has spent his entire academic career at NHH, exploring the intersection of theory and practice. He jokes that he’s never really had an honest job, having been at the business school since he was a student.
“Even though I haven’t done a day’s work outside academia, I’ve been in close contact with those who have. So I’m interested in both the practical side and the more theoretical side of the subjects I work with.”
Using AI competitively in Norway
For Lien, the synergy between research and practice is essential. Testing knowledge in real-world settings gives him inspiration for new ideas. One of Lien’s current ideas focuses on understanding how artificial intelligence reshapes competitive advantage. He compares AI to previous “general purpose technologies” (GPTs) like the steam engine or the internet. These innovations have thousands of potential applications across industries.
Historically, Norway has excelled not in developing such core technologies but in adapting them to local strengths: shipbuilding and forestry during the steam era, or energy and maritime industries in the digital age. Lien therefore wonders whether history will repeat itself.
“We’re not going to outcompete OpenAI or Google on core AI technology. Our opportunity lies in tailoring AI where Norway has unique advantages, such as strong data, specialized industries like oil, gas, seafood, or maritime sectors,” he notes.
Lien distinguishes between three levels of AI-based advantage. At the primary level, firms compete on developing the core AI technologies themselves. This, he considers, is “basically hopeless” for a small country like Norway against giants such as OpenAI or Google. The secondary level involves adapting and refining AI by leveraging proprietary data, which can create valuable and customized solutions. The tertiary level, which he considers the most ambitious and riskiest, combines AI with a company’s other unique strengths. While this approach offers the greatest potential for differentiation, it also carries significant organizational complexity and risk.
Closing the gap between technology and practice
Lien warns that technology is advancing faster than most organizations can adapt. The gap between what is technologically possible and what companies are practically able to implement has never been wider. Companies that can narrow it will gain significant advantages, whether through faster innovation cycles, more efficient use of data, or the ability to pivot quickly when markets shift. Doing so, however, isn’t easy.
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Lien’s current projects include building a live database to track how Norwegian firms adopt AI and running experiments, such as testing whether consultants at KPMG improve decision-making with AI tools and who benefits most. This work is urgent and complex.
“New models appear every two weeks. It’s a moving target. But by collecting high-speed, high-quality data, we can start to map the trajectory and help organizations navigate the change.”
Meet the reserach fellows: Karen Modesta Olsen
Since joining NHH in 2007, Professor Karen Modesta Olsen has made her mark as a researcher in human resource management and employment relations.