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The cognitive effect on automotive


Unleashing exceptional experiences from an abundance of data

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Driving growth through data

Automotive (auto) companies are sitting on a treasure trove of data – data generated by their businesses, products and services, customers and other external sources. The potential uses of this data are tremendous – from greatly improving industry and company practices to personalizing consumers’ in-vehicle experiences to creating new mobility options.

But that potential often remains untapped because the tools to extract the insights residing within the data are either underutilized or unavailable. Cognitive computing can help unleash these insights – and auto executives are beginning to take heed.

To understand the potential impact of cognitive computing on the industry, we analyzed responses of 500 auto industry executives worldwide who participated in a 2016 IBM Institute for Business Value cognitive computing survey (see Methodology section at the end of this report).

We explored what auto executives say about how ready the technology,the industry and their organizations are for cognitive adoption; what their companies are currently doing with cognitive computing; and what they plan to do in the next few years. We also looked at a select group within the industry that is ahead of others in cognitive adoption to learn what they’re doing differently, and at how digital business – business conducted by digital means – and digital intelligence – insights gained using digital technology – are merging to create exceptional enterprise and mobility experiences.

Why cognitive? Why now?

Every day, nine billion gigabytes of personal data is generated and one million new active mobile users are added to social networks.1 For auto companies, this data has significant potential for helping them create exemplary customer experiences and personalizing marketing campaigns.

The Weather Company currently controls three billion weather forecast reference points.2Auto companies could use this reference-point data to enable a vehicle to plan its own route, or a business could use it to avoid weather-related disruptions to supply or distribution channels.

The amount of data is only going to grow. By 2025, one million autonomous vehicles are predicted to generate and consume 4,000 gigabytes of data daily – data that could potentially help personalize customers’ in-vehicle experiences.3 To put this quantity into perspective, currently that’s roughly equal to the amount of data 40 percent of the world’s population generates every day.

However, much of this data is unstructured, complex and volatile – and traditional analytics only makes use of a fraction of it. To access the full spectrum of available data, and to translate that data into the insights that help drive future innovations, new capabilities are needed. And that’s where cognitive computing comes in.

Cognitive systems can understand, reason, learn and interact much like humans do (see sidebar, “What is cognitive computing?”). By augmenting uniquely human strengths – such as imagination or abstraction – with cognitive strengths – such as natural language interaction or pattern identification – cognitive systems can create new partnerships between humans and technology. They do so in part by drawing from other advanced technologies, such as artificial intelligence, natural language processing, deep learning and predictive analytics.


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Meet the authors

Binoy Damodaran

Connect with author:


, Associate Partner, IBM Cognitive and Analytics


Ben Stanley, Automotive Research Leader, IBM Institute for Business Value


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