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How to build a highly effective AI team

Bruce Harpham | June 15, 2017
Four organisations share real-world insights into staffing a successful AI effort from the ground up.

Recruiting AI talent in a hot hiring market often requires going directly to academic institutions.

“Being active in the community – especially presenting at conferences and publishing papers – has supported our recruiting efforts. We have also presented at Columbia, MIT, and other leading organizations,” explains Thomson Reuters’ Al-Kofahi.

But bringing a new hire in the door is not enough. You also need them to stick around.

“When it comes to retention of AI professionals, a few factors make an important difference. First, it has helped us to think through the career path and show what other opportunities are available. Second, we encourage our staff to actively participate in the professional community, including presenting at conferences, attending Meetups and other activities,” LogRhythm’s Brazdziunas says.

Professional development is not the only way to grow: Autonomy is also important.

“In addition to external activities, we support giving our AI talent time at the office to carry out their investigations and generate new ideas,” Brazdziunas adds. For professionals interested in research, such support will go a long way.

 

How to organize your AI efforts

In the technology industry, Bell Labs and Xerox’s PARC loom large as examples of corporate support for research. In addition to broad research units such as Google X, several organizations are creating AI-focused organizations. In Canada, Royal Bank has invested heavily in AI by establishing an AI research lab in Edmonton. Pure research is not the only way to structure your AI organization. Consider the approach that Thomson Reuters has followed.

“Our organization has three major groups: traditional research, application development, and user experience,” explains Al-Kofahi. “My philosophy for the group combines two themes: following the business and leading the business. That means that we deliver incremental improvements for the business and create entirely new ideas and products.”

When it comes to moving AI concepts and products from the world of computer science to business use, paying attention to user experience is key.

“In my view, AI is the new UI,” explains Elliott Yama, assistant vice president of machine learning at software provider Apttus. “Max, our AI assistant, is designed to be used conversationally and ask to follow up questions,” Yama adds.

User experience design is a focus at Thomson Reuters as well.

“If you want to build applications that will change how professionals get their job done, the user experience is a big part of this story,” Al-Kofahi says.

 

Alternative AI staffing solution: Freelance marketplaces

What if your organization is just not ready to recruit a computer science Ph.D.? There are other ways to get started in AI.

Anand Kulkarni, founder and CEO of Crowdbotics, has hired three machine learning specialists from Upwork, a large talent marketplace. Crowdbotics is far from alone. According to Upwork’s Q1 2017 Skills Index report, demand for AI skills is the second fastest growing skill set. With multiple opportunities available, contractors may be a good addition.

 

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