Artificial intelligence (AI) is already becoming entrenched in many facets of everyday life, and is being tapped for a growing array of core business applications, including predicting market and customer behavior, automating repetitive tasks and providing alerts when things go awry. As technology becomes more sophisticated, the use of AI will continue to grow quickly in the coming years.
In its most widely understood definition, AI involves the ability of machines to emulate human thinking, reasoning and decision-making. A May 2015 survey of USbusiness executives by Narrative Sciencefound that 31% of respondents believed AI was “technology that thinks and acts like humans.” Other conceptions included “technology that can learn to do things better over time,” “technology that can understand language” and “technology that can answer questions for me.”
At a deeper level, however, there is confusion in the marketplace around AI technology and the terminology used to describe it. Similar-sounding terms—such as cognitive computing, machine intelligence, machine learning, deep learning and augmented intelligence—are used interchangeably, though there are subtle differences among them. Many companies that have been involved with AI for years don’t even call it AI, for various reasons. “In essence we call it machine learning, because I think AI sometimes can spook some folks,” said Mahesh Tyagarajan, chief product officer at ecommerce personalization platform RichRelevance.
Many people also don’t realize that AI powers some of today’s most buzzed-about technologies. For example, a June 2016 survey by CompTIA found surprisingly low awareness of AI among US business and IT executives: Just 54% said they were aware of AI, compared with 78% who were aware of 3-D printing and 71% who knew of drones and virtual reality. However, some of the higher-ranking technologies on the list—including virtual reality, self-driving vehicles and robotics—are underpinned by different types of AI, though they were not identified as such.
Narrative Science also found that 58% of US business executives polled were already using AI—particularly in conjunction with big data technologies. Of those, nearly one-third (32%) said voice recognition and voice response solutions were the AI technologies they used most. The study showed that organizations also used AI for machine learning (24%) and as virtual personal assistants (15%). Smaller percentages cited decision support systems, automated written reporting and communications, analytics-focused applications and robotics.
Businesses in all industries are also making choices about how they will acquire AI technologies. For example, a January2016 survey of globalexecutives in the financial industry byEuromoney Institutional Investor Thought Leadershipfound that 42% of respondents said their organization used internal R&D to develop its AI/machine learning capabilities. Other ways included employing consultants and research firms, participating in innovation hubs and incubators, partnering with other businesses and/or academia, crowdsourcing and joint ventures, mergers and acquisitions.