Artificial intelligence (AI) is poised to have a major impact on global business—expected to drive $1.2 trillion in value by 2022. While there is plenty of discussion around the efficiencies and new capabilities that AI will bring, talent remains the Achilles heel of AI implementation.
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A majority of senior AI professionals believe that the lack of talent and qualified workers is the greatest single barrier to AI implementation across businesses. Neither traditional corporate training methods nor one-size-fits-all eLearning programs, like AWS’s Machine Learning University, will be enough to effectively close this skills gap and create the adaptable workforce that AI advancement requires.
Without essential components like virtual coaching, peer-to-peer social interaction, and personalization—powered by AI itself—most training programs simply won’t stick. Companies can close their own AI skills gaps and see value from AI implementation by taking a modern approach to training and prioritizing adaptability above all.
Blocking Out the Noise
Companies are competing with external content distribution platforms like YouTube, LinkedIn, Facebook, and Amazon for their own employees’ attention. But in order to manage and measure employee learning and development, companies must be able to hold their own as the primary learning provider for their workforce.
AI implementations must be customized for an organization—and constantly refined—to provide maximum value. To build and retain a workforce with the specific skills a company needs, companies must be able to ensure continuous, flexible learning that can be updated and measured.
In AI fields in particular, which are in a constant state of change and progressing at a very fast pace, AI can work “in the background” to keep your training material up to date and deliver to trainees’ timely updates on the latest approaches and breakthroughs that DO happen globally basically every week. This is something that a traditional training program cannot do.
Companies can no longer expect employees to come to them for training; companies must meet employees with personalized tools, when and where they want to learn.
Letting AI Close the Gap
AI itself can be an important secret weapon for closing the AI skills gap. Particularly at a global scale, companies simply won’t have the resources and hours within learning and development (L&D) teams to power the quality of learning experiences that AI can now deliver.
AI today is already enabling businesses to provide a personalized, adaptive learning experience, arming workers with the skills needed to succeed in their job and development and coaching tools to make the most of their careers.
Attracting and retaining a modern workforce means cutting down on outdated training processes like instructor-led classes or in-person onboarding. With AI-powered personalized training programs, L&D teams can not only provide the very best training experience for each employee but also measure training in real time and ensure that employees have all of the skills that managers think they have.
Prioritizing Adaptability
While teaching specific AI skills is important, an increased focus on what specific courses or skills companies should teach—and the tactics to do so—is leading companies down the path to failure.
The rapid pace of change is really the only constant that companies can be sure of in the years to come.
So instead of a particular set of technical skills, adaptability itself should be the ultimate goal. In the end, creativity will be a more important skill than knowing how to code because technology will continue evolving faster and faster.
Organizations should be mapping out more strategic programs that are not focused on training specific skills and capabilities but the creative skills to ensure a culture of adaptability.
AI Is Not the Silver Bullet
AI-driven learning will be able to provide vast benefits, from time saving to more sophisticated, engaging, and personalized learning experiences, but it is not going to be a sort of “silver bullet” to solve all training woes.
For example, it is very difficult to teach machine learning (ML) in a void. Practical, effective training depends on the availability of data sets on which trainees can spend prolonged time and get their hands dirty in order to learn how to resolve tasks and problems. The opportunity for interactive learning is not something that is fully supported by eLearning as we know it but instead can be included supplementary through social learning functionality in a more advanced learning platform.
The shortage of capable IT-leaning people whose skills can be redirected toward AI skills is not going away; in fact, it is going to worsen as businesses of all kinds begin to refocus their hiring to data scientists, ML specialists, and others for their own AI needs. To meet this even higher demand, there will be a need to “convert” people who already work in a business in other capacities to the field.
With AI-powered eLearning, the retraining of a workforce and development of comprehensive and effective training will be increasingly possible and accessible.
 Giuseppe “Peppo” Valetto, Product Owner, Artificial Intelligence Business at Docebo, is an experienced researcher with a demonstrated history of working in the learning industry. He leads Docebo’s AI team in developing the first AI-powered learning platform. Follow Docebo on Twitter, @docebo. |