Emerging AI Topics In December 2019, I published a short LinkedIn post
about three AI trends for 2020, which was well received. Therefore, I now briefly expand upon it here. Towards the end of 2019, I was asked in several meetings and discussions about the key AI trends for 2020. There are some important lists that try to identify the top trends for AI, especially the Gartner Hype Cycle
analyses.
To some degree, these lists will always be subjective, and my top three trends are strongly driven by my focus on business model innovation and strategic management in the context of AI – rather than focusing on particular technological opportunities and challenges in the different fields of AI. Beyond particular technology topics, I therefore highlight the following three exciting AI trends for 2020:
1. Integrated Intelligence
In light of the limited competitive impact of many corporate AI initiatives so far, executives increasingly focus on the combination of human and artificial intelligence to achieve a sustainable competitive advantage. On this basis, they attempt to develop an integrated intelligence architecture, which goes substantially beyond the isolated application of selected AI tools and which may enable a sustainable competitive advantage. These opportunities are addressed in more detail in my new book ‘
Integrated Intelligence: Combining Human and Artificial Intelligence for Competitive Advantage’.
2. Emotion AnalyticsTechnology experts increasingly address the field of AI-enabled emotion analytics. For example, the startup company
TAWNY.AI
offers customized algorithms based on its underlying core solution for emotion analytics to ease human-machine-interaction. As the functionalities of AI solutions continue to advance, the seamless interaction with the user becomes increasingly important, and it calls for taking into account the emotions of the user. A good example here are the different levels of autonomous driving and the variety of human-machine-interactions, which may need to consider the drivers’ emotions at a particular moment.
3. Data EfficiencySustainable and green AI is a huge topic, and it covers many different aspects. One topic that increasingly becomes a core issue in this regard is data efficiency - as recently pointed out by EU commissioner Margrethe Vestager, who highlighted the energy consumption of streaming and other web-enabled services. The topic of data efficiency is explained in more detail in an excellent
LinkedIn post
by Elmar Schüller. To fully profit from AI in the long run, companies need data strategies that put sufficient emphasis on efficient data management.
The Human Side of AIWhen selecting these three topics, I did not specifically focus on the human side of AI. However, this overarching theme emerged when choosing the three trends. While this result may derive from my personal focus on business models and strategies for AI, there seems to be more to this focus on the human side of AI. For example, the topic of augmented intelligence is still at the beginning of the
Gartner Hype Cycle
for AI, and it describes the role of AI in strengthening human skills, which is a major component of integrated intelligence architectures. Thus, the human side of AI may very well become an overarching key theme for profiting from AI over the next years beyond 2020.