Artificial Intelligence

Applying Big Data, Machine Learning and Causal Reasoning to Digital Transformation
Data & Artificial Intelligence

It’s been five years since IBM’s artificial intelligence, Watson, beat human contestants on the game show Jeopardy! Still, to this day, many people think of artificial intelligence (AI) as science fiction — a cunning computer run amok or a loyal companion robot.

The reality is much more practical.

“Enhancing the human ability to process” is a strong statement and the stakes are enormous for the early innovators, as well as for the broader economy. Artificial intelligence technologies have the potential to transform entire business models at a clip reminiscent of the industrial revolution. The question is: How can companies take full advantage of such a fundamentally disruptive group of technologies?

For business leaders, it is important to have a basic understanding of how the major technologies that constitute AI can deliver optimal business impact by enabling their companies to provide products and services to meet their customers’ needs when and where they need them.

To provide such products and services requires the ability to collect and analyze vast amounts of structured and unstructured data, and to use the insights gained from that data to inform business decisions and take action in real time.

Although the application of each technology on its own can result in improved business performance, the truly transformative value and future of AI will lie in the ability to seamlessly layer data analytics, machine learning and causal reasoning platforms to deliver insight-driven, personalized products and services.

Smart machines’ rapid impact

Leading predictions show the imminent rise of smart machines and their impact on business investments and applications.

In particular, this combination offers great promise for changing the way that brands approach marketing. By using these technologies in concert with each other, marketers can obtain a better understanding of consumer and behavioral data and enable far more granular personalization of the customer experience.

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