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AI at Long Last?

We're still far from anything like general-purpose artificial intelligence, but we're witnessing an explosion in the availability of function-specific AI.

Artificial intelligence (AI) has arrived. Sort of. We're still a far piece from anything like the general-purpose AI that's grist for sci-fi classics such as 2001: A Space Odyssey or Ex Machina, but we're witnessing an explosion in demand for another, more limited kind of AI: function-specific AI.

International Data Corp. (IDC) projects that enterprise spending on AI and cognitive computing technologies will increase by nearly 60 percent this year, reaching $12.5 billion.

So what if artificial general intelligence (AGI), the holy grail of AI research, isn't yet close to being a reality? IT organizations are spending beaucoup bucks on function-specific AI. In all likelihood, they'll continue to do so; IDC forecasts that IT-related spending on AI and cognitive technologies will top out at more than $46 billion by 2020.

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That's a compound annual growth rate (CAGR) of 54.4 percent. "[Intelligent] applications are being developed and implemented on cognitive/AI software platforms that offer the tools and capabilities to provide predictions, recommendations, and intelligent assistance through the use of cognitive systems, machine learning, and artificial intelligence," said IDC's David Schubmehl, research director for cognitive systems and content analytics, in a statement.

Going Gaga Over AI

The AI-ification of the enterprise will occur at a rapid rate, Schubmehl says. "Cognitive/AI systems are quickly becoming a key part of IT infrastructure, and all enterprises need to understand and plan for the adoption and use of these technologies in their organizations."

For 2017, enterprises will spend $4.5 billion on cognitive applications, which IDC defines as "a set of technologies that use deep natural language processing and understanding to answer questions and provide recommendations and direction." Elsewhere, IDC says cognitive/AI software platforms -- integrated offerings that provide tools for accessing, organizing, and analyzing structured and unstructured data, along with related advisory services -- will account for $2.5 billion in IT spending in 2017.

Spending on cognitive IT and business services will come to about $3.5 billion this year.

What are organizations doing with AI/cognitive technologies? The most popular use cases include quality management investigation and recommendation systems, diagnosis and treatment systems, automated customer service agents, automated threat intelligence and prevention systems, and fraud analysis, according to IDC. Vertical-specific use cases are coming on strong, too -- spending on cognitive technologies for public safety and emergency response will grow at an 85.5 percent CAGR between 2015 and 2020.

"Double-digit spending growth is expected for cognitive and artificial intelligence systems across all industries, but growth varies depending on how well particular use cases solve existing and future business priorities," said IDC research manager Marianne Daquila in a statement. "Heavily regulated markets such as banking and securities investment services are among the early growth drivers. Collectively, these two financial industries will represent a quarter of worldwide spending on cognitive/AI solutions. Stringent compliance requirements are key drivers for these industries as they seek new innovations in fraud and risk detection."

Waiting on AGI

AI and cognitive products, services, and APIs are designed to do one thing, or a few things, very well. They're a far cry from AGI, a posited higher kind of AI that theorists say would be able to perform any human intellectual task and have some degree of self-awareness.

On the other hand, what Amazon, Apple, Facebook, IBM, Microsoft, Oracle, and other companies are doing with all of this function-specific AI technology suggests how something like AGI might come to pass. Take Amazon, for example, which recently released a trio of new AI offerings -- Lex, Rekognition, and Polly -- for its Amazon Web Services (AWS) platform. These services provide natural language conversation, image recognition, and text-to-speech capabilities, respectively. Individually, they're instances of function-specific AI.

Because they're exposed as microservices, however, developers can call and embed them into their own apps. As a result, a single app can exploit multiple function-specific AI services. Combine enough AI services and you get closer to an approximation of human intelligence. That's still a far cry from self-aware machine intelligence -- but it bears watching.

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