Cognitive technologies are increasingly being used to solve business problems; indeed, many executives believe that AI will substantially transform their companies within three years. But many of the most ambitious AI projects encounter setbacks or fail. Broadly speaking, AI can support three important business needs: automating business processes typically back-office administrative and financial activities , gaining insight through data analysis, and engaging with customers and employees. To get the most out of AI, firms must understand which technologies perform what types of tasks, create a prioritized portfolio of projects based on business needs, and develop plans to scale up across the company. Cognitive technologies are increasingly being used to solve business problems, but many of the most ambitious AI projects encounter setbacks or fail.
Aqualisa Quartz is case study of Harvard business school. | Bartleby
Lean start-ups, in contrast, begin by searching for a business model. They test, revise, and discard hypotheses, continually gathering customer feedback and rapidly iterating on and reengineering their products. This strategy greatly reduces the chances that start-ups will spend a lot of time and money launching products that no one actually will pay for. Blank, a consulting associate professor at Stanford, is one of the architects of the lean start-up movement and has seen this approach help businesses get off the ground quickly and successfully. In combination with other trends, such as open source software and the democratization of venture financing, it could ignite a new, more entrepreneurial economy. There are numerous indicators that the approach is catching on: Business schools and universities are incorporating lean start-up principles into their curricula. Even more interesting, large companies like GE are applying them to internal innovation initiatives.