The Covid-19 crisis has significantly exacerbated the corporate digital transition and the need to be the mother of (re)invention. It is important to keep up with fast-moving technological developments as businesses hurry to create fresh new skills in an attempt to construct sustainability and retool for the post-pandemic environment. Bain & Company worked periodically this year with a deliberately curated group of over 100 technology firms and start-ups to track the most relevant developments. Hunting for the most important innovations and technology implementations of today, we have reached some big AI developments that already have an impact on a wide variety of industries. These technological applications are generating great prospects in the age of the modern enterprise, from AI on the edge, to advanced artificial intelligence (AI) powering the banking industry. Edge AI transplants brains into equipment and machines for factories. The "edge AI" or "AI on the edge" is a network infrastructure perceived to be the next generation of artificial intelligence that enables AI algorithms to operate on the edge of a network, meaning near to or even on the data collection machines. The abrupt and drastic shifts in network traffic that have followed Covid-19 lockdowns and the transition from home to work are likely to intensify the move towards edge computing that is already underway. Edge computing advantages include bandwidth preservation and performance enhancement by processing information closer to the consumers and computers that use it, rather than moving the data to central locations in the cloud for processing. Manufacturers can reduce latency problems and speed up insight generation by embedding AI locally, while reducing the use and expense of cloud resources. The cost of communication also decreases, as the processing of part of the data lowers bandwidth and wireless data consumption locally. And since intelligence is run locally, plants with weak contact networks located in rural areas are less vulnerable to link losses that can delay mission-critical and time-critical As Prometheus took fire from the gods and gave it to men, Edge AI "steals" part of the cloud's intellect and gives it to machinery. Octonion, a start-up that incorporates artificial intelligence into low-power microcontrollers, shows how industrial goods can be imbued with intelligence. Using continuous learning frameworks and machine health ratings, the platform enables enterprises to make good decisions in real time, locally. In order to optimize surveillance and improve predictive maintenance capabilities, examples include installing edge AI on industrial motors and pumps. Automated and explainable AI allows more knowledgeable financial organizations. According to The Economist Intelligence Center, banks and insurance firms expect an 86 percent rise in AI assets by 2025. Employees with little to no experience in computer science need to be able to use it to improve their operating efficiency in order for businesses to harness the full value of AI. For this reason, the introduction of AI on a larger scale would be crucial for user-friendly AI systems that help business employees to rapidly create models, easily understand and trust their performance, and make decisions confidently. One example is DreamQuark's Brain, a completely digital AI platform for financial sector sales and customer experience teams. Employees with no experience in data science can build AI models using prebuilt applications that exploit the patented deep-learning technology of the start-up. One tier-1 bank used the tool, according to DreamQuark, to help develop an application that detects more than 40 percent of credit fraudsters. It is used by a top French insurer to determine the expectations of consumers for specific products, such as pensions, retirement products or savings insurance, and to provide insurance analysts with insight into the reasoning behind the ratings.
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