Disruptive technologies: Advances that will transform life, business, and the global economy

By J. Manyika, Michael Chui, J. Bughin, R. Dobbs, Peter Bisson, Alex Marrs. 2013

1,166 citations recorded by the source corpus.

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Citations in the corpus

Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, background): “d to increase in demand for some ML products and the derived demand for the tasks, platforms, and experts needed to produce such products. The economic impact of machine learning in McKinsey’s report [2] is deﬁned under knowledge work automation; “the use of computers to perform tasks that rely on c”
Research Priorities for Robust and Beneficial Artificial Intelligence (2015, background): “Many economists and computer scientists agree that there is valuable research to be done on how to maximize the economic beneﬁts of AI while mitigating adverse eﬀects, which could include increased inequality and unemployment [2–8].”
Internet of Things (IoT): A Review of Its Enabling Technologies in Healthcare Applications, Standards Protocols, Security, and Market Opportunities (2021, background): “4) In the next several decades, the IoT healthcare services transformed into evidence-based policies, and technologies that can be observed to enhance any instances of effective implementations like e-Health policies and strategies [156].”
A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision (2018, background): “Autonomous vehicles and autonomous vehicles on demand are considered to be some of the most attractive technologies of the next few years according to [72].”
The impact of automation on employment: just the usual structural change? (2018, background): “With regard to the effect of automation using robots and AI, there are articles in popular media, consulting reports [4,5], and scientific publications (e.”
Brave new world: service robots in the frontline (2018, background): “It can be assumed that robots in the coming decades will master cognitive and analytical tasks of unprecedented complexity (Manyika et al., 2013, 2017).”
The adoption of digital technologies in supply chains: Drivers, process and impact (2021, background): “The reasons are that IoT, big data and AI are regarded as one of the most important sets of digital technologies in manufacturing sector (The McKinsey Global Institute, 2013).”
The Internet of Things vision: Key features, applications and open issues (2014, background): “Among them, the Internet of Things (IoT), with an estimated value of 36 trillion of dollars, is considered the CPS paradigm with the highest economic impact [14].”
Strategic Implications of Openness in AI Development (2017, unknown): “…by 2025 in the following sectors: Automation of knowledge work: $5.2 – 6.7 trillion; Internet of things: $2.7 – 6.2 trillion; Advanced robotics: $1.7 – 4.5 trillion; Autonomous and near-autono-mous vehicles: $.2 – 1.9 trillion; and 3D printing: $0.2 – 0.6 trillion (Manyika et al., 2013).”
Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. (2017, background): “Although automation in the transportation system has the potential to significantly reduce the number of vehicle crashes and the economic burden associated with them (Fagnant and Kockelman, 2015; Manyika et al., 2013; Maccubbin et al., 2008), this is only true if drivers recognize the usefulness of ”