Together with Esade scholar Xavier Ferràs-Hernández, ENI’s Petra Nylund and Alexander Brem recently published a study in California Management Review on The Emergence of Dominant Designs in Artificial Intelligence. AI is disrupting business across sectors with Amazon, Google, and Microsoft are opening up their source codes to third parties and offering AI services through the cloud, and Netflix and PayPal are deploying their own AI algorithms to recommend content or detect fraud. The theory of dominant designs and industry life cycles partly explain these dynamics, but they appear to be even more complex, with technology, service, and business model innovation interlinked and coevolving. The new study therefore employs the lens of dominant design and industry emergence to understand how AI is contributing to innovation.
The study synthesizes contributions from six research fields: Industrial organization explains the phases that lead to a dominant design of AI, and technology management helps us understand how these phases are fast-tracked in innovation ecosystems. Network economics captures diffusion accelerated by digital platforms, and operations management provide the mechanisms of modularity that combine supply chains from industries with different clockspeed. All this adds complexity and requires new business models that align the ecosystem and extend AI.
The findings mean that a few large digital platforms have the computational power to deliver AI through the cloud, and this business model is increasingly dominating the market. The industry will be verticalized and integrated, and only a few supply chains will have the scale and scope to bring AI to the end user. Then a phenomenon like “Intel Inside” will occur for AI to reach the mass market: Companies might be able to access advanced AI supercomputing facilities by connecting to an AI terminal offered by large digital actors, meaning each single company could have “AI Inside” that would endow any end user with AI power.