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Around 91% of organisations rely on Artificial Intelligence (AI) in their workplace but only 26% realize using it. More than 65% of organizations use AI without even realizing it, says the National Business Research Institute report.
In their latest research, ‘Outlook on Artificial Intelligence in the Enterprise 2016’, it was found that only 26% organisations agreed to be using AI in their workplace, up from 15% in 2015. Paradoxically, 88% of those who said that their organizations do not use AI technologies also use solutions that actually rely on AI techniques, as per the report.
This makes roughly 65% organisations, using AI unaware of the fact that they are using it. This, as per the report is mainly because of lack of a proper definition of AI. Also, 20% of organizations cited in the report that it is lack of clarity on value proposition as primary reason for not deploying the technology.
But, the direct adoption of AI to automate the workplaces will boost in the coming two years. As per the report, 56% of organisations will be deploying AI directly in the coming two years, which will make a total of 62% of organizations using AI in their workplaces by 2018.
Big data deriving AI
The report also shared that it is the big data initiative that will make the organizations adopt AI. More than half (58%) of businesses said in the survey that, predictive analytics — using data mining, statistics, modeling, and machine learning to analyze current data to make predictions about the future — is the most commonly used solution.
However, businesses are planning to turn one of their biggest challenges - lack of data scientists (cited by 59% in the survey) into their biggest strength by deploying AI in their place.
Though half of the organisations felt confident using big data to solve problems, almost all of the respondents (95%) who showed confidence in using big data to solve business problems (or generate insights) used AI technologies. Clear indicating that many companies are turning to intelligent systems (95% from 59% last year) to help augment their data science capabilities in the face of a talent shortage.
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