Recent estimates put the productivity impact of information and communications technology (ICT) and early digital technologies such as broadband at 0.6 percent annually during the 2000s
AI is already relatively applicable to real business problems and can have significant
impact in areas including marketing and sales, supply chain management, and manufacturing
Research has found that the introduction of robots in manufacturing and the introduction of IT accounted for 0.4 percent and 0.6 percent in annual productivity increases, respectively.
The EU has called for $24 billion to be invested in AI research by 2020.
The net effect on GDP and labor markets show that AI could add around 16 percent to global output by 2030, or about $13 trillion, compared with today. This would be incremental value created in addition to current global output.
Virtually all workers will need to adapt to work alongside machines in new ways
In fact, developing economies could potentially leapfrog advanced ones if they were to strengthen core enablers. An absence of legacy, inefficiencies in various parts of the economy, and the role of smart capital in overcoming skills issues may present attractive opportunities for the commercialization of AI use.
Two key questions?
1- How can individuals develop the skills that will be needed to power the AI economy and embrace a culture of lifelong learning
2- How can businesses embrace AI and automation safely, addressing issues including data security,
privacy, malicious use, and potential issues of bias?
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