#HBR PROJECT CANVAS HOW TO#
Businesses on the other hand first and foremost need to address the question how to generate value for their customers and stakeholders.
While the performance of narrow artificial intelligence is indeed astonishing in these and other examples, they mainly focus on a specific research question. 2017) or cancer detection (Esteva et al., 2017 Ardila et al. This approach has seen spectacular successes such as playing the game “Go” without human knowledge (Silver et al. Narrow AI systems on the other hand aim to solve a particular problem and specialize in the execution of a specific, singular task. While general AI systems are still elusive, it is expected that they would interact and reason much like we humans do. When referring to artificial intelligence, the distinction between general (or strong) and narrow AI is generally made: General AI systems (Turing 1947) (McCarthy 2007) exhibit intelligent behavior en par or even surpassing human intelligence in a wide range of scenarios. It consists of two parts, where part one focuses on the business view and organizational aspects, whereas part two focuses on the underlying machine learning model and the data it uses.Īrtificial intelligence (AI) and Machine Learning have enormous potential to transform businesses and disrupt entire industry sectors. In addition, the more technical aspects of the underlying machine learning model have to be discussed in terms of how they impact the various units of a business: Where do the relevant data come from, which constraints have to be considered, how is the quality of the data and the prediction evaluated? The Enterprise AI canvas is designed to bring data scientist and business expert together to discuss and define all relevant aspects which need to be clarified in order to integrate AI-based systems into a digital enterprise. Furthermore, the organization will need to be transformed to be able to integrate AI-based systems into their human work-force.
However, companies wishing to integrate algorithmic decisions into their organization face multiple challenges: They have to identify use-cases in which artificial intelligence can create value, as well as decisions that can be supported or executed automatically. Artificial Intelligence (AI) and Machine Learning have enormous potential to transform businesses and disrupt entire industry sectors.
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