Nearly 9 in 10 (87%) companies in Europe have implemented machine learning (ML) technology or plan to do so by 2020, a new study has revealed. The conclusions reached in Finding the Business Potential in Machine Learning show that ML is second only to analytics as the key investment priority for businesses and ahead of other disciplines like IoT, artificial intelligence and data science.
Despite this, a lack of skills and resources are among the biggest barriers to adoption. Over half of those surveyed admitted they are hesitant to implement because they don’t have enough skills and knowledge, while 74% view it as a cost that reduces the bottom line.
The new report by Cloudera, the modern platform for ML and analytics, explores the benefits and barriers of ML implementation. IT decision-makers from more than 15 different industries and four countries (UK, France, Germany, Spain) were interviewed to gain an understanding of the usage, drivers and challenges within organisations.
The results were broadly positive, with a third of companies already seeing a return on investment from the adoption of ML and 84% of companies stating that ML provides a competitive advantage. Most consider the biggest benefit of ML to be the improvement of operational efficiency (52%), followed by deeper insights (43%) and the reduction of tedious tasks (39%).
Barriers to adoption
While the results of the survey are encouraging, there are still several barriers to achieving more widespread acceptance and implementation. Chief among them is a lack of skills and knowledge of the competitive advantages ML can provide. 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 ML can do and its range of use cases.
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, working with the right partners who can complement existing teams and through leveraging external technology."
Making the case
In the boardroom, senior leaders are still struggling to make a case for it, with 59% stating that it’s hard to convince the board of the benefits, and just 31% seeing it as transformational. External factors like GDPR have also swayed opinions, as 67% fear the use of ML could conflict with new regulations.
The survey also revealed that many IT decision-makers struggle to identify exactly where ML will have an impact on a business, with 65% finding it hard to prioritise where ML will have the greatest effect. When coupled with the top three answers for barriers to adoption – ‘lack of skills and resources’ (34%), ‘lack of leadership knowledge’ (25%) and ‘too expensive’ (24%) – it is clear that external expertise and upskilling is required.
Stephen Line added: “In what is still the early stages for many businesses in actually implementing ML, 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 ML quite clear, the race is now on for businesses to overcome their barriers to deliver a better experience for their customers.”
The reality is that ML gives businesses a competitive advantage, which is why 47% are already investing in the technology, with 40% looking to do so over the coming two years.