Many companies nowadays face the challenge of drawing the right conclusions and implementing them from a variety of technologies, trends, and innovations which are difficult to comprehend. How can AI support successful innovation management in this process? In this interview Christian Mühlroth, ITONICS CCO, speaks about AI bots, process change, and AI augmentation.
Check the full interview at Digital Innovation Podcast #030, #031 and #032.
The technologies surrounding AI and machine learning are now very advanced so that a wide range of applications is possible: In the front-end of innovation (i.e. the early phases of the innovation process), AI can be used to identify emerging trends or new technologies at an early stage. This brings a clear advantage for companies to be able to deal with new developments at an early stage and thus have more time to find suitable answers to the changes that are about to take place, in order to create new growth opportunities. This can lead to a significant competitive advantage, especially in turbulent markets.
Are there any other Exciting Fields of Application?
Another important application is the strategic observation of competition with the help of machine learning. With this, well-known market companions, but also start-ups and venture capital investments can be observed and classified. The observation can also be applied to geographical areas (such as regions and countries). Typical questions here are, for example, "Who controls the technologies I need?", "Which companies occupy which topic and technology fields and why?" and "Where is the market heading?".
In What Form and at What Point is AI used at ITONICS?
We at ITONICS support our customers in using the potential of AI and machine learning for themselves; among other things, by increasing the share of AI algorithms and features in our digital innovation platform.
What are the Advantages of using AI? Can you give us a few Examples here?
One of the biggest challenges in the field of innovation and technological change is human bias. Deviations from the status quo mean change and major changes in particular are often perceived as a threat. There are countless examples of this, starting with the steam engine, industrialization, the advent of the automobile; today, the topics of renewable energy, digitalization, and AI are just a few of them. AI is not prone to such a bias. And this is its great advantage: the so-called "human experience bias" is avoided because AI acts exclusively on the basis of facts. Once set up, an AI can also be multiplied by any number of "AI bots", which means that any number of AI bots can observe an unlimited number of topics and search fields for companies. An equivalent number of human resources would be much more expensive.
What should Companies using Innovation Management with AI consider?
As with all new technologies, AI in innovation management will have to prove itself individually for each project. The skepticism towards AI in this area is - often justifiably - high. Therefore it is important to achieve first quick successes with simple use cases especially at the beginning and then to expand the integration depth and complexity of the applications step by step. In order to implement AI permanently, it is also important to create trust. The goal should not be to replace people but to support them - a significant difference. Sharing success stories, involving people in the process and the agile, step-by-step approach to implementing and expanding AI are typical success factors - as with all change processes.
What does the Future look like?
The term "AI Augmentation" describes the short-term development to be expected in this area very well. People will continue to be at the center of attention, and around them, AI will expand and deepen their capabilities and increase their speed to an extreme degree. In the short term, this will lead to a multitude of new applications. There are already the first successful applications of AI in innovation management for generating and testing new business ideas, evaluating startups and developing new products.
About the interviewee: Christian Mühlroth is an innovation and machine learning enthusiast, speaker and the CCO of ITONICS. Since joining ITONICS in 2011, he has led a team of innovation experts and international projects across multiple industries helping companies to enable, shape, and grow their corporate foresight and innovation management activities.