“I just finished reading the “Competing in the Age of AI” by Marco Iansiti & Karim Lakhani, says Paavo Ritala, associate editor of R&D Management and Professor of Strategy & Innovation at the School of Business and Management, LUT University, Finland. He reviews the book below and we have a short interview with one of the authors here.
I know… I am late to the game! The book was released in 2020 and artificial intelligence stuff develops at the speed light
Thus, if you are reading this, you might be hearing some yesterday’s news.
If you have not read the book yet – now is a good time! In fact, even though I understand quite a bit about AI technologies, the book provided few really strong takeaways that I am going to carry with me to benefit my research, projects and teaching.
AI technologies allow for “boundary-less” growth and organisations
Traditional organisations start to face diseconomies of scale, scope, and learning as they grow. Bureaucracy, corporate culture, matrix organisations. You know the stuff. But AI allows the modern giga-platform companies to grow at unprecedented pace and the it seems that there are very little limits to scalability.
While traditional organisations benefit from specialisation and silos, firms utilising AI benefit rather from horizontal capabilities. Joint data pools, centralised AI capability and AI platform, and the possibility to cross-utilise, collect, and analyse data. Changing an organisation from siloed legacy IT systems & functions into a horizontal model is not easy. In the book there are few stories about companies who have done so.
Why AI is disruptive
The book explains well why AI-driven companies are able to disrupt the old-school companies. While it takes some time to get to speed with collection and analysis of (big) data, the possibility to scale up later can easily bring back what was lost as investments in the beginning.
However, the book reminds us of important differences between companies that can scale globally (e.g. Netflix) vs companies who need to accumulate scale and momentum locally (e.g. Uber). Thus, each competitive setting is unique and there is no universal silver bullet here, even with AI.
Afterthought: In our own research (together with Päivi Aaltonen & Mika Ruokonen), we have studied the use of AI in industrial companies, who use it for process automation, predictive maintenance, and data-driven value added services to industrial customers. Such cases were less visible in the book (B2C was highlighted). Yet, I believe that what happens “behind the scenes” with AI in manufacturing and production automation is something to watch for more closely – some serious productivity improvements are underway!
More info about the book here: https://hbr.org/2020/01/competing-in-the-age-of-ai.
Read a review by Jeremy Klein in R&D Management: https://doi.org/10.1111/radm.12489.
Post adapted from a LinkedIn post written by Paavo Ritala, at his suggestion.