Top Trends on the Gartner Hype Cycle for Artificial Intelligence, 2019

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Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner's 2019 CIO Agenda survey. AI is reaching organizations in many different ways compared with a few years ago, when there was no alternative to building your own solutions with machine learning (ML). AutoML and intelligent applications have the greatest momentum, while other approaches are also popular -- namely, AI platform as a service or AI cloud services. Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant and others. Meanwhile, new technologies continue to emerge such as augmented intelligence, edge AI, data labelling and explainable AI.


Top Trends on the Gartner Hype Cycle for Artificial Intelligence, 2019

#artificialintelligence

Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner's 2019 CIO Agenda survey. AI is reaching organizations in many different ways compared with a few years ago, when there was no alternative to building your own solutions with machine learning (ML). AutoML and intelligent applications have the greatest momentum, while other approaches are also popular -- namely, AI platform as a service or AI cloud services. Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant and others. Meanwhile, new technologies continue to emerge such as augmented intelligence, edge AI, data labeling and explainable AI.


Top Trends on the Gartner Hype Cycle for Artificial Intelligence, 2019

#artificialintelligence

Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner's 2019 CIO Agenda survey. AI is reaching organizations in many different ways compared with a few years ago, when there was no alternative to building your own solutions with machine learning (ML). AutoML and intelligent applications have the greatest momentum, while other approaches are also popular -- namely, AI platform as a service or AI cloud services. Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant and others. Meanwhile, new technologies continue to emerge such as augmented intelligence, edge AI, data labelling and explainable AI.


Why AI will create $2.9T in business value by 2021

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The artificial intelligence (AI) revolution is beginning to pay off: By 2021, AI augmentation will create $2.9 trillion in business value, and 6.2 billion hours of worker productivity globally, according to a Gartner report released Monday. Gartner defined AI augmentation as a partnership model of AI and humans working together to improve cognitive performance, including learning and decision-making. "Augmented intelligence is all about people taking advantage of AI," Svetlana Sicular, research vice president at Gartner, said in a press release. "As AI technology evolves, the combined human and AI capabilities that augmented intelligence allows will deliver the greatest benefits to enterprises." By 2020, Gartner predicts that decision support/augmentation will be the largest type of AI in terms of the greatest business value add and the fewest barriers to adoption, followed by agents, smart products, and decision automation.


AI, Machine Learning, Data Science: What Enterprises Are Doing - InformationWeek

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IT organizations are adjusting their plans about how and when to implement artificial intelligence and machine learning initiatives. Moving into production is taking longer than IT leaders may have expected. CIOs have identified artificial intelligence and machine learning as the number one way to achieve "game-changing transformation." That's according to Gartner research VP Svetlana Sicular, who provided a perspective on where the industry is right now in terms of implementation, where we are going, and how soon we might be getting there. Sicular offered her take during a session, The Future of Data Science, Machine Learning, and AI, during the recent Gartner Data and Analytics Summit in Orlando, Florida.