Using open innovation to drive business success

Innovation is frequently discussed in academic and business circles but it is rarely clearly defined. Xavier Ferràs, associate professor at the Department of Operations, Innovation and Data Sciences and associate dean of the executive MBA programme at Esade Business School in Spain, is interested in the concept of open innovation and the best ways to apply it in the era of AI.

“Open innovation means that the process of innovation should be open to the external environment,” Ferràs says. “When this concept emerged, innovation was mostly confined to the internal processes of an organisation. We know now that if you only work with insiders, your innovation capacity will only ever be limited. Your existing employees may offer improvements but improvement is not innovation.”

The rise of globalisation and digital technologies made it easier for companies to embrace collaboration with external partners. The mainstream adoption of AI came later as computational science evolved. By pursuing an open innovation framework alongside AI, organisations can access information across the world and use ideas and insights that were once hidden.

“AI represents a new generation of information systems that are able to learn by themselves,” Ferràs says. “This means they can acquire knowledge that no human has had access to previously by identifying patterns, understanding new frameworks and connecting the dots from any available information. Open innovation and AI represent an explosive combination,” he adds.

“As part of my findings published in The Oxford Handbook of Open Innovation, I identified seven ways AI could influence open innovation,” Ferrás explains. These are identifying new and innovative business models, predicting new marketable technologies and their likely trajectories, analysing strategic directions of competitors, forecasting business results, conducting market research, and predicting health events. “I also developed a model of innovation based on a decision matrix with two axes: risk and reward. Risk is the difference between innovation and improvement. Without risk, there is no innovation.”

Whichever approach to innovation businesses adopt, incorporating AI demands a mindset change. One of the first things organisations should do to accelerate AI adoption is build awareness.

“Many organisations don’t tackle AI in a professional way,” Ferràs says. “They should employ an AI director with the responsibility to understand what is happening in this area. The technology is currently in the fluid phase but this will transition to a dominant design. Businesses should start preparing for this now.” They should also prepare themselves for the regulatory evolution that is likely to occur around innovation and AI, he adds. This is set to be more nuanced than current discussions around AI often suggest.

“I don’t think we can say all AI should be regulated or legalised,” Ferràs says. “It depends on the impact of AI and its level of immediacy. Systems that act immediately, for example, leave no time for human supervision. Should AI recommendations for a fast-food order be regulated in the same way as a self-driving car? The question of regulation depends on how much human oversight you have. The vast majority of AI systems in the future will ultimately be overseen by humans.”

Find out more about research at Esade.