Artificial intelligence (Al) stands out as a transformational technology of our digital age. Questions about what it is, what it can already do-and what it has the potential to become cut across technology, psychology, politics, economics, science fiction, law, and ethics.
The technologies underpinning Al continue to move forward, enabling applications from facial recognition in smartphones to consumer apps that use Al algorithms to detect diabetes and hypertension with increasing accuracy.
Indeed, while the media hypes science fiction-like Al realization, the number of less-noticed practical applications for Al throughout the economy is growing quickly and permeating our lives.
Techniques that address classification, estimation, and clustering problems are currently the most widely applicable in the use cases we have identified, reflecting the problems whose solutions drive value across the range of sectors.
We see AI adding great value in use cases in which more established analytical techniques such as regression and classification techniques can already be used, but where AI techniques provide higher performance and generate additional insights or applications. This is true for the majority of Al use cases we see. In a minority of use cases do we are also finding “greenfield” Al solutions that are applicable where other analytics methods would not be effective.
Because of the wide applicability of Al across the economy, the types of use cases with the greatest value potential vary by sector. These variations primarily result from the relative importance of different drivers of value within each sector. They are also affected by the availability of data, its suitability for available techniques, and the applicability of various techniques and algorithmic solutions.
In consumer-facing industries such as retail, for example, marketing and sales is the area with the most value. In industries such as advanced manufacturing, in which operational performance drives corporate performance, the greatest potential is in supply chain, logistics, and manufacturing.
McKinsey and Company recently estimated that AI solutions have the potential to enable the creation of between $3.5 trillion and $5.8 trillion in value annually. Within industries, that is the equivalent of 1 to 9 percent of 2016 revenue.
The scale of the potential economic and societal impact creates an imperative for all participants – AI investors, Al innovators, Al-using companies and policy-makers – to ensure that a vibrant Al environment can effectively and safely capture the economic and societal benefits.