The popularity of AI and ML have wide-reaching effects on your enterprise. Here are three important trends driven by AI to look out for next year.
The Rise of AutoML 2.0 Platforms
As the need for additional AI applications grows, businesses will need to invest in technologies that help them accelerate the data science process. However, implementing and optimizing machine learning models is only part of the data science challenge. In fact, the vast majority of the work that data scientists must perform is often associated with the tasks that preceded the selection and optimization of ML models such as feature engineering — the heart of data science.
The Shift to Automation Will Intensify Focus on Privacy and Regulations
As AI and ML models become easier to create using advanced “AutoML 2.0” platforms, data scientists and citizen data scientists will begin to scale ML and AI model production in record numbers. This means organizations will need to pay special attention to data collection, maintenance, and privacy oversight to ensure that the creation of new, sophisticated models does not violate privacy laws or cause privacy concerns for consumers.
More Citizen Data Scientists Doing Data Science
Big data will continue to be on the upsurge in 2020 with a growing demand for skilled data scientists and a continued shortage of data science talent — creating ongoing challenges for businesses implementing AI and ML initiatives. Although AutoML platforms have alleviated some of the pressure on data science teams, they have not resulted in the productivity gains organizations are seeking from their AI and ML initiatives. As such, companies need better solutions to help them leverage their data for business insights.
To support for AI technology and development for social impact, Michael Dukakis Institute for Leadership and Innovation (MDI) has established AI World Society (AIWS) to invite participation and collaboration with think tanks, universities, non-profits, firms, as well as start-up companies that share its commitment to the constructive and development of AI.
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