Productive uses for AI are closer at hand than ever due to the rise of AutoML.

Beginning in 2019, advancements in AI have replaced obstacles with tools to benefit from its power. Foremost among them is Automated Machine Learning (AutoML), which does not require programming or scripting of any kind. Here are some examples.

Business Analysts
“AI is the new BI” is a theme repeated for years by journalists and product marketers. AI is now simple enough that business analysts can make reliable predictions without being data scientists or programmers. Moving from visualizing trends with BI to predicting the future—record-by-record—with AI is transforming the way businesses run. AutoML is what makes that possible.

Citizen Data Scientists
Researchers and designers who need to understand patterns know their problems and data very well, but not necessarily the AI algorithms that can extract information they need. AutoML abstracts algorithm selection and use to produce results quickly.

Data Science Professionals
AutoML does not replace the need for true data scientists, whose expertise in solving complicated AI problems cannot be replicated. Nevertheless, AI pros use AutoML to glean insights on problems to make custom work more efficient. In addition, offloading simpler BI problems to AutoML keeps them focused where they are most needed.

Conclusion: AutoML makes achieving the benefits of AI simpler for everyone.

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