Home Machine Learning is a Definite Leader Among Other AI Subsets According to the Global CTO Survey Report

Machine Learning is a Definite Leader Among Other AI Subsets According to the Global CTO Survey Report

by sol-admin

Based in Poland, STX Next is a software company offering end-to-end development, team extension, and consulting services in both web and mobile development. Their comprehensive range of services includes Python, JavaScript, React Native, Machine Learning, Data Engineering, DevOps, Product Design, Software Testing, Quality Assurance, Product Strategy, and Discovery Workshops.

STX Next recently polled 500 CTOs from 4 continents. They have shared insights on technology, current trends, security, management, and more. One of the report’s noteworthy findings is that Machine Learning is the most popular AI subset to be implemented. 68,3% of all CTOs in the survey said that machine learning had been applied in their company or organization. Thus ML is more than 2.5 times ahead of the second most common AI area, Natural Language Processing, which has been implemented by 24,5% of the respondents. Pattern recognition, AI Chatbots, Deep Learning, and Computer Vision are used roughly by 20-21% of the surveyed companies. In addition, 72% of the respondents see ML as the most likely technology to come to prominence in the next two years.

Despite the growth, AI implementation is still in its infancy, with skills gaps still hindering adoption to some extent. Most businesses have a team of five people working exclusively on AI, machine learning, or data science, but just 15% currently have a dedicated AI department.

It’s unsurprising to see machine learning as a definite leader when it comes to future technologies as its applications are becoming more widespread every day. What’s less obvious is the skills that people will need to take full advantage of its growth and face the challenges that will arise alongside it. It’s important that CTOs and other leaders are wise to these challenges and are willing to take steps to increase their AI expertise to maintain their innovative edge.”

Łukasz Grzybowski, Head of Machine Learning & Data Engineering, STX Next

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