ABI Research forecasts almost one million businesses worldwide will adopt AI technologies by 2022
Jun 20, 2017
Oyster Bay, New York - 20 Jun 2017
ABI Research predicts the number of businesses adopting artificial intelligence (AI) technologies worldwide will grow considerably, up from 7,000 this year to nearly 900,000 in 2022, a CAGR of 162%. AI is no longer limited to science fiction and movies, with significant strides being made in cloud processing, storage capacity, and machine learning algorithms to enable computer systems to surpass humans in winning strategy games and television shows. Increasingly, businesses are applying these technological advancements to deliver automation and innovation that equal or exceed human capabilities.
“Even though nearly one million businesses will adopt AI by 2022, it will not be a great fit for every company,” says Jeff Orr, Research Director at ABI Research. “Many businesses will have to adapt their corporate governance policies to deal with the lack of a guaranteed outcome when implementing machine learning. While most enterprises start using machine learning to analyze their existing business for insights, the technologies have far-reaching application in specific industries, ranging from reduction of false positives in fraud detection to powering conversational interfaces for chatbots and virtual assistants.”
While some of the world’s largest and innovative enterprises, such as Amazon, American Express, Citrix, Coca Cola, Facebook, Google, Netflix, PayPal, and Uber, already deploy projects powered by machine learning, ABI Research finds that not all will benefit. Organizations that are comfortable with uncertainty in outcomes and measuring changes in key performance indicators (KPIs) will find the most to gain from enacting machine learning projects. On the other hand, companies that focus only on ROI timetables will find emerging technologies, including machine learning, cybersecurity, and IoT, to be frustrating to implement and difficult to measure.
Several SaaS solutions are available for machine learning and businesses looking to experiment will have many vendors to choose from. Best practices include starting off with a pilot project and requesting case studies about enterprises that have already gone through their first operational deployment.
“It is the companies that choose to ignore AI entirely that will quickly find themselves at a competitive disadvantage,” concludes Orr.
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