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AI is becoming strategic for many companies across the world. The technology can be transformative for just about any part of a business.
But AI is not easy to implement. Even top-notch companies have challenges and failures.
So what can be done? Well, one strategy is to provide AI education to the workforce.
“If more people are AI literate and can start to participate and contribute to the process, more problems–both big and small–across the organization can be tackled,” said David Sweenor, who is the Senior Director of Product Marketing at Alteryx. “We call this the ‘Democratization of AI and Analytics.’ A team of 100, 1,000, or 5,000 working on different problems in their areas of expertise certainly will have a bigger impact than if left in the hands of a few.”
Just look at Levi Strauss & Co. Last year the company implemented a full portfolio of enterprise training programs—for all employees at all levels—focused on data and AI for business applications. For example, there is the Machine Learning Bootcamp, which is an eight-week program for learning Python coding, neural networks and machine learning—with an emphasis on real-world scenarios.
“Our goal is to democratize this skill set and embed data scientists and machine learning practitioners throughout the organization,” said Louis DeCesari, who is the Global Head of Data, Analytics, and AI at Levi Strauss & Co. “In order to achieve our vision of becoming the world’s best digital apparel company, we need to integrate digital into all areas of the enterprise.”
Granted, corporate training programs can easily become a waste. This is especially the case when there is not enough buy-in at the senior levels of management.
It is also important to have a training program that is more than just a bunch of lectures. “You need to have outcomes-based training,” said Kathleen Featheringham, who is the Director of Artificial Intelligence Strategy at Booz Allen. “Focus on how AI can be used to push forward the mission of the organization, not just training for the sake of learning about AI. Also, there should be roles-based training. There is no one-size-fits-all approach to training, and different personas within an organization will have different training needs.”
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AI training can definitely be daunting because of the many topics and the complex concepts. In fact, it might be better to start with basic topics.
“A statistics course can be very helpful,” said Wilson Pang, who is the Chief Technology Officer at Appen. “This will help employees understand how to interpret data and how to make sense of data. It will equip the company to make data driven decisions.”
There also should be coverage of how AI can go off the rails. “There needs to be training on ethics,” said Aswini Thota, who is a Principal Data Scientist at Bose Corporation. “Bad and biased data only exacerbate the issues with AI systems.”
For the most part, effective AI is a team sport. So it should really involve everyone in an organization.
“The acceleration of AI adoption is inescapable—most of us experience AI on a daily basis whether we realize it or not,” said Alex Spinelli, who is the Chief Technology Officer at LivePerson. “The more companies educate employees about AI, the more opportunities they’ll provide to help them stay up-to-date as the economy increasingly depends on AI-inflected roles. At the same time, nurturing a workforce that’s ahead of the curve when it comes to understanding and managing AI will be invaluable to driving the company’s overall efficiency and productivity.”
Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction, The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems and Implementing AI Systems: Transform Your Business in 6 Steps. He also has developed various online courses, such as for the COBOL.
