In-Demand Skills for AI Professionals: Plainsight CEO Shares Insights

The workforce is growing rapidly as organizations continue to embark on digital transformations in hopes of outpacing competitors and adapting to thrive in a changing world. Professionals versed in tech topics like artificial intelligence and machine learning are in especially high demand. A recent Gartner report found that total AI-generated revenue increased by more than 14% between 2020 and 2021. Experts predict even more revenue growth (over 21%) in the year ahead.

In-Demand Skills: AI and ML Professionals

How can professionals set themselves apart in a crowded talent marketplace? How can businesses recognize truly world-class applicants? The professional development experts at Great Learning asked AI executives to answer these questions in their latest roundup article. 

Among the experts surveyed is Carlos Anchia, CEO and Co-Founder of Plainsight. He suggests that subject matter expertise is as important as ever, but that those “soft skills” that make us uniquely human are becoming more and more crucial. Even in a high-tech, high-complexity field, there’s often no substitute for a quality like persistence.

While technical skills will always prove important, intangibles like these can often make the difference between two equally-skilled candidates.

      – Carlos Anchia

Check out the full list of skills from Anchia and more than a dozen additional AI and machine learning thought leaders. From technical skills like programming languages to intangibles like creativity and emotional intelligence, they discuss the full range of attributes that make for success in AI. Whether you’re looking to stand apart as an applicant or recognize a top-notch candidate, the guide should help you better understand what excellence in AI looks like.

More AI Insights from Plainsight

Anchia recently sat down with Alldus for the latest episode of their ‘AI in Action’ podcast. Check out the episode below to learn more about hiring top-notch AI professionals and how Plainsight works to democratize vision AI. 

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What Is Synthetic Data?

What Is Synthetic Data?

By leveraging synthetic data, organizations can easily train their models to address uncommon scenarios that might be tough to capture in the real world. Deep learning algorithms can concoct every conceivable event and image, dramatically increasing the number of use cases a model can help to address. If they’re supplementing an existing dataset, enterprises can make a point to include objects and scenarios that are missing.