Top 10 AI Trends to Watch in 2017


Few technologies have the transformative potential to reshape how we live, move, and work.  Electricity and the Internet were two technologies that fundamentally transformed life in the 20th century.  Artificial intelligence (AI) is the 21st century equivalent of electricity and the Internet.  AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

AI, in its simplest definition, is an umbrella term for technologies that are inspired by biological systems, giving computers human-like abilities related to seeing, reasoning, hearing, and learning.  The definition of AI is also a moving target; what is considered AI today, once successfully adopted and implemented, will no longer be considered AI.  Today, AI encompasses technologies like machine learning, deep learning, natural language processing (NLP), computer vision, machine reasoning, and strong AI.

Tractica has conducted an analysis of the AI market by assessing approximately 200 use cases in which AI is being used currently, or will be in the near future.  This bottom-up approach provides a comprehensive view of where AI is today, and its future trajectory.  Tractica’s analysis of the AI market indicates that the technology is already deeply embedded in our lives, and its capabilities are growing at an exponential rate.  There is a degree of hype around AI, but at the same time, it is a mistake to brush off the hype as a precursor to another AI winter.

This white paper presents the top 10 AI market trends to watch in 2017 and beyond, backed by data from Tractica’s bottom-up forecast model.  While many of these trends are well-recognized by industry participants, some are surprising and challenge mainstream thinking about the AI market opportunity.  Here is a selection of the top trends examined:

  • AI implementations will be focused on incremental improvements in the short term, but its transformative potential should not be ignored
  • Virtually all AI implementations will be narrow AI
  • Deep learning will be the most important AI technology

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