Skills gap hitting full-scale roll out of machine learning

DataIQ News

Nearly 9 in 10 (87%) companies in Europe have already invested in machine learning but over half (51%) remain hesitant to fully implement the technology due to a gap in their skills and knowledge.

So says a new study, Finding the Business Potential in Machine Learning by Cloudera, which quizzed IT decision-makers from more than 15 different industries and four countries (UK, France, Germany, Spain) to gain an understanding of the usage, drivers and challenges within organisations.

The results were broadly positive, with machine learning second only to analytics as the key investment priority for businesses and ahead of other disciplines like IoT, artificial intelligence and data science.

A third of companies are already seeing a return on investment from the adoption of machine learning, with most stating that the technology provides a competitive advantage. The biggest benefit is an improvement of operational efficiency (52%), followed by deeper insights (43%) and the reduction of tedious tasks (39%).

Despite this, a lack of skills and resources are among the biggest barriers to full-scale adoption. Over half of those surveyed admitted they are hesitant to implement because they do not have enough skills and knowledge, while 74% of this group view it as a cost that reduces the bottom line.

While 89% of respondents claim to have a basic understanding of the benefits, 60% agree they lack the correct skills to implement fully, and only half of IT decision-makers understand what machine learning can do to help their businesses.

Commenting on the findings, Stephen Line, VP EMEA at Cloudera, said: “Although most IT buyers understand the benefits of machine learning, with 33% of respondents saying they have already seen tangible ROI from its use, many are still unsure about how to implement and how it will impact their businesses.

"These are barriers that can be overcome, through upskilling staff, recruiting new data talent, and through leveraging external technology. In what is still the early stages for many businesses in actually implementing machine learning, it’s unsurprising to learn that the skills gap and investment are key factors in preventing many companies from using it to improve efficiency and drive growth. That said, with the benefits of the technology quite clear, the race is now on for businesses to overcome their barriers to deliver a better experience for their customers.”

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Technology