More than a third of companies use artificial intelligence (AI), while another 42% are exploring their AI options, according to IBM's recent Global AI Adoption Index. AI adoption looks easy, thanks to rapid advancements in AI technology and the availability of off-the-shelf AI tools.
But in reality, as other recent research makes clear, some companies are struggling with AI. Accenture reports that only 12% of AI adopters are currently using AI "to outpace their competitors," while nearly two-thirds (63%) are still in the experimentation phase—"barely scratching the surface of AI’s potential." Multiple reports show that it is common for AI models to never make it into production.
So where are companies going wrong? There are four common possibilities.
The Problem of Unrealistic Expectations
A reality sometimes lost in between the fear of AI and the hype of AI (such as with Watson, GPT-3, and AlphaGo) is that AI has its limitations. Business leaders often overlook this. They fail to understand what AI can and can’t do for their business and have unrealistic expectations.
Sure, AI is a powerful new technology. It makes sense of unstructured data and gives insights that humans miss. But it isn’t magic. AI relies on mathematical modeling, and its solutions are often probabilistic. Today, enterprises use narrow AI that does specific tasks—not general AI, the kind in sci-fi movies.
Even IBM, which claimed Watson would be the intelligent digital assistant for everyone everywhere, settled for a humbler version of the tech. The company set out to make sense of all medical data to improve cancer treatment—but in the end, it failed. Ultimately, the division was discontinued. Former IBM executives noted that their unrealistic AI goals set Watson up for failure because the tech was not advanced enough to meet those goals. This brings us to the first lesson.
Continue reading: https://techbeacon.com/enterprise-it/why-isnt-ai-working-your-business
But in reality, as other recent research makes clear, some companies are struggling with AI. Accenture reports that only 12% of AI adopters are currently using AI "to outpace their competitors," while nearly two-thirds (63%) are still in the experimentation phase—"barely scratching the surface of AI’s potential." Multiple reports show that it is common for AI models to never make it into production.
So where are companies going wrong? There are four common possibilities.
The Problem of Unrealistic Expectations
A reality sometimes lost in between the fear of AI and the hype of AI (such as with Watson, GPT-3, and AlphaGo) is that AI has its limitations. Business leaders often overlook this. They fail to understand what AI can and can’t do for their business and have unrealistic expectations.
Sure, AI is a powerful new technology. It makes sense of unstructured data and gives insights that humans miss. But it isn’t magic. AI relies on mathematical modeling, and its solutions are often probabilistic. Today, enterprises use narrow AI that does specific tasks—not general AI, the kind in sci-fi movies.
Even IBM, which claimed Watson would be the intelligent digital assistant for everyone everywhere, settled for a humbler version of the tech. The company set out to make sense of all medical data to improve cancer treatment—but in the end, it failed. Ultimately, the division was discontinued. Former IBM executives noted that their unrealistic AI goals set Watson up for failure because the tech was not advanced enough to meet those goals. This brings us to the first lesson.
Continue reading: https://techbeacon.com/enterprise-it/why-isnt-ai-working-your-business
