Faster Horses: Collaborative AI Innovation between Incumbents and Startups

Amidst the blossoming of technological development of the fourth industrial revolution, so-called ‘Industry 4.0’ (Schwab, 2017), organizations are seeking to integrate the potential benefits of artificial intelligence (AI) into their businesses. The idea is that organizations should become smarter and more efficient (Marr, 2018; Kaplan & Haenlein, 2019). The McKinsey Global Institute suggests that by 2030 70% of all businesses will have adopted at least one form of AI; but also that an “S-curve pattern of adoption and absorption of AI is likely” (Bughin et al., 2018). On the one hand, how incumbent businesses can adopt AI into their core activities is not always clear. On the other hand, the number of AI startups disrupting existing markets is exploding. It is widely acknowledged that incumbents struggle to innovate — at least quickly — and that startups innovate quickly while struggling to scale (Hockerts & Wüstenhagen, 2010; Weissbrod & Bocken, 2017; Slot, in press), but collaboration between incumbents and startups for joint innovation is increasing, especially in Europe. And whereas it is not uncommon to ask how AI disrupts business, there is less known about how collaboration can disrupt AI. This research examines the collaborative innovation between a building industry incumbent, the VELUX Group, and an AI startup, Airboxlab, to ask the following question: How can the collaborative innovation between incumbents and AI startups shape the development of AI?