A 2019 forecast for data-driven business: from AI to ethics – Tom Davenport

Fellow, MIT Center for Digital Business, Tom Davenport

From Forbes

It should come as no surprise that 2018 continued to mark another year in the progression of data adoption in business.  Companies are pushing forward with efforts to become increasingly data-driven.  Firms are investing in transformation initiatives to establish a “data culture” within their organizations.  Early adopters are focused on data-driven business innovation.

As we look ahead to 2019, we reflect on a year of accomplishments and emerging areas of focus – from AI through Ethics (listed alphabetically)

  • AI/Machine Learning—AI continued to grow in popularity over the past year, becoming well-institutionalized within many large enterprises. We argued in a previous post, however, that too many companies employed AI pilots and prototypes, and not enough firms had implemented production deployments. As with analytics, the use of AI is increasingly being democratized through automated machine learning (AutoML). Several contributors to KD Nuggets’ review of AI and ML trends for 2019 suggested that AutoML would become more popular over the next year. It will make machine learning models easier to create for business analyst types, as well as dramatically increasing the productivity of data scientists—that is, if they can be persuaded to use it. We also predict that deep learning, which has been the fastest-growing and most popular AI technology over the past several years, will continue to advance in power and prevalence for several years. However, we also expect that deep learning will increasingly be augmented by other approaches to AI. NYU professor Gary Marcus has argued, and we agree, that artificial general intelligence—or even generally useful AI—will have to employ various techniques beyond deep learning in order to be successful.

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