AI is becoming strategic for many companies around the world. Technology can be transformative for just about any part of a business.
But AI is not easy to implement. Even the top companies have challenges and failures.
So what can we do? Well, one strategy is to provide AI training to the workforce.
âIf more people are proficient in AI and can begin to participate and contribute to the process, more problems large and small can be solved across the organization,â said David Sweenor, Senior Director of Marketing produced at Alteryx. âWe call this the ‘democratization of AI and analytics’. A team of 100, 1000 or 5000 people working on different issues in their areas of expertise will certainly have a greater impact than if it were left in the hands of a few.
Just look Levi Strauss & Co. Last year, the company implemented a comprehensive portfolio of corporate training programs, for all employees at all levels, focused on data and AI for business applications. For example, there’s 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 to integrate data scientists and machine learning practitioners across the organization,” said Louis DeCesari, global head of data, analytics and research. ‘AI at Levi Strauss & Co. “In order to achieve our vision of becoming the best digital clothing company in the world, we must integrate digital into all areas of the business.
Certainly, corporate training programs can easily become a waste. This is especially the case when there is not enough buy-in at the upper levels of management.
It is also important to have a training program that is more than just a set of lectures. âYou need to take results-oriented training,â said Kathleen Featheringham, director of artificial intelligence strategy at Booz Allen. âFocus on how AI can be used to advance the mission of the organization, not just training to learn more about AI. In addition, there should be role-based training. There is no single approach to training, and different people within an organization will have different training needs.
AI training can certainly be intimidating due to the many complex topics and concepts. In fact, it might be better to start with basic topics.
âA statistics course can be very helpful,â said Wilson Pang, chief technology officer at Appen. âIt will help employees understand how to interpret the data and how to make sense of the data. This will allow the business to make data-driven decisions.
There should also be some coverage of how the AI ââcan derail. âThere has to be training on ethics,â said Aswini Thota, who is senior data scientist at Bose Company. “Bad and biased data only exacerbates the problems with AI systems.”
For the most part, effective AI is a team sport. So it should really involve everyone in an organization.
“Accelerating adoption of AI is inevitable – most of us experience AI every day, whether we realize it or not,” said Alex Spinelli, CTO at Live person. âThe more companies educate their employees about AI, the more opportunities they will provide to help them stay up to date, as the economy increasingly relies on AI-shaped roles. At the same time, training a workforce that is ahead of its time when it comes to understanding and managing AI will be invaluable in improving overall business efficiency and productivity.
To M (@ttaulli) is an advisor / member of the board of directors of startups and 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. Hhas also developed various online courses, such as for the COBOL.