Businesses may not be ready to jump all in to AI just yet, so starting with individual projects can be a good place to start. What should CIOs look for in early-stage AI projects?
"Google was one of the pioneers in using AI, and the investments paid off with the company doubling its net income year over year after only a short period of time. Today, many companies seek to join the AI revolution. Genesys predicted that 60% of U.S. companies will be using AI by 2022, and the reason for this is simple: Not only have they seen the results, but the fear of losing the market to AI-driven competitors is a powerful source..."
Artificial intelligence has been baked into enterprise applications in recent years and often given special names, such as Einstein, Leonardo and Coleman. But has the hype delivered?
"While adoption of machine learning (ML) technology has yet to hit the mainstream, the most common means of implementing it today is to purchase enterprise applications in which such functionality is embedded.
According to a study by 451 Research, only one in five organisations have to date implemented some form of ML software in one or more parts of the business, while a further 20% are at the proof-of-concept stage. Another 13% plan to introduce the technology in the next 12 months, a further 15% within the next three years and just under a third have no such plans at all..."
Headlines proclaiming the next great application of artificial intelligence appear with a great degree of frequency
"As much that is true generally, healthcare seems to receive potentially an even greater amount of such announcements.
Determining the validity behind the assertions about artificial intelligence can be difficult. There will be truthful claims and others that do not live up to the hype. The arguably more interesting question is what artificial intelligence, including both the development and use, is doing to privacy..."
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