Artificial Intelligence and Business Strategy
In collaboration withBCG
After years of hope and promise, 2018 may be the year when artificial intelligence (AI) gains meaningful traction within Fortune 1000 corporations. This is a key finding of NewVantage Partners’ annual executive survey, first published in 2012. The 2018 survey, published on January 8, represented nearly 60 Fortune 1000 or industry-leading companies, with 93.1% of survey respondents identifying themselves as C-level executive decision-makers. Among the 2018 survey participants were corporate bellwether companies, including American Express, Capital One, Ford Motors, Goldman Sachs, MetLife, Morgan Stanley, and Verizon.
The main finding of the 2018 survey is that an overwhelming 97.2% of executives report that their companies are investing in building or launching big data and AI initiatives. Among surveyed executives, a growing consensus is emerging that AI and big data initiatives are becoming closely intertwined, with 76.5% of executives indicating that the proliferation and greater availability of data is empowering AI and cognitive initiatives within their organizations.
The survey results make clear that executives now see a direct correlation between big data capabilities and AI initiatives. For the first time, large corporations report that they have direct access to meaningful volumes and sources of data that can feed AI algorithms to detect patterns and understand behaviors. No longer dependent on subsets of data to conduct analyses, these companies combine big data, AI algorithms, and computing power to produce a range of business benefits from real-time consumer credit approval to new product offers. Companies such as American Express and Morgan Stanley have publicly shared stories of their successes within the past year.
Staving Off Disruption
Survey participants comprised executives representing data-intensive industries, notably financial services companies, which constituted 77.2% of the survey respondents. Financial services companies have long been at the forefront of industry due to the large volumes of transactional and customer data that they maintain, and they have developed robust data management and data governance processes over a period of decades. These organizations have been at the forefront in the use of analytics to manage risk, assess customer profitability, and identify target market segments. Industries such as life sciences, while newer to data management, possess vast repositories of scientific and patient data that have gone largely untapped relative to the potential for insight.
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