Companies are Investing in Machine Learning in 2021. Why?

An Algorithmia survey reveals the increasing investments in machine learning

According to reports, machine learning is one of the most sought-after jobs in 2021. Companies have been in high demand for machine learning engineers to build algorithms that can enable business growth and efficiency. Disruptive technology is not a stranger anymore. Companies are pouring money into the development and deployment of cutting-edge technologies and automation. Companies are adopting business intelligence and automation to boost their services and get a deeper insight into the business.

A recent survey by Algorithmia on the key trends driving enterprises in 2021 found an increased priority level for artificial intelligence/machine learning initiatives and companies are backing them up with investments and hiring.

Machine learning is one of the most significant disruptive technologies that has immense capabilities to transform and digitize businesses. AI and machine learning together can automate most of the operational processes and enable to derive business insights through data analytics. Machine learning applications range from computer vision, data analytics, and deep learning to speech recognition, natural language processing, predictive analytics, and sentiment analysis.

The Algorithmia report revealed that 64% of its respondents stated that they have increased their priority on AI/ML initiatives rather than any other IT initiatives in the past 12 months. Further, the report revealed that 83% of organizations have increased their AI/ML budgets compared to 71% last year.

Investing in AI and ML has many perks to the companies. Machine learning clubbed with artificial intelligence can automate most of the mundane tasks and unburden the employees. Data analytics is considered the fuel for businesses these days and machine learning enables this analysis in a hassle-free manner. The report states one method in which companies are investing in machine learning is by increasing data scientists hiring. Year-on-year, the average number of data scientists has increased to 76%, reveals the report. The more the strength of data science teams, the easier it becomes to develop and deploy ML algorithms and models. This hiring process also indicates the focus of companies on revenue growth and reducing operational costs by adopting ML and AI.

Automating business processes and enhancing customer experience are the two major industrial use cases of AI and ML in the current scenario. The digital shift and penetration of smart devices have given birth to customer-centric business systems, where companies are focused on providing a personalized and customized experience to their users. According to a Capgemini report, AI and ML are being extensively used in cybersecurity practices. The report says that the role of machine learning and deep learning in detecting anomalies using behavioral analysis and provides several examples of companies using ML to detect attacks and mitigate risks.

Companies pouring money into developing machine learning strategies are anticipating redefining their business by embracing automation. Still, many enterprises are lagging and living out of legacy systems. The rising need for data science and analytics will urge businesses to accept and adopt disruptive techs like ML and artificial intelligence.