In a new report, business leaders share their machine-learning successes and struggles.
What’s new: Many businesses plan to increase their use of machine learning, but their efforts so far don’t always yield the results they seek, according to a study performed by the market analyst Forrester and commissioned by the bank Capital One.
Machine learning on the rise: The authors surveyed 150 “data-management decision-makers” who work for North American companies in banking, information technology, manufacturing, and retail about how their organizations have used — and hope to use — machine learning.
- The respondents used machine learning primarily to analyze data. A high priority for this group in the next one to three years was detecting anomalies such as fraudulent bank transactions. Further priorities included improving customer experiences and growing revenue.
- Two-thirds planned to increase the use of machine learning across their organizations.
- 77 percent began using machine learning in the past two years, and 24 percent started more than two years ago.
Room for improvement: The respondents also outlined several worries.
- Around half of respondents said their teams lacked sufficient machine learning expertise. Two-thirds said their organizations were partnering with proven leaders to overcome machine learning challenges.
- 57 percent said that organizational barriers between data scientists and other departments inhibited deployment of machine learning projects, and 41 percent stated that their primary challenge is breaking down those barriers.
- 47 percent said their organizations struggled to use machine learning to inform strategic decisions, and 73 percent struggled to explain the business value of their machine learning applications to executives.
Behind the news: The talent shortage in machine learning and data science is well documented. A 2020 Deloitte survey found that companies across all industries struggled to find the machine learning engineers that would help them meet their business goals. Some companies offer incentives to attract people skilled in AI, such as offering remote work at Silicon Valley pay rates and providing time off to pursue personal projects.
Why it matters: Machine learning continues to expand in mainstream businesses, and with it opportunities for machine learning engineers and data scientists. An earlier Forrester study found that business leaders who see clear value in AI are (a) using or expanding their use of the technology and (b) effectively using the resulting insights to drive their business strategies. The new report shows that they believe the potential is greater still — and that bringing more machine learning engineers onboard could make the difference.
We’re thinking: Many industries are still figuring out how to get the most out of AI. If you can make its value clear to executives in your organization — one of the top issues in this study — you can play a big role in moving things forward.