It’s no secret that artificial intelligence (AI) has changed how many industries function, and workforce education is no exception. Businesses today are increasingly using AI technologies to upskill workers. Concurrently, more than one-half of employees want their organizations to train them to use AI.
The rapid emergence of AI has created a more level playing field for degreed and non-degreed employees, who across industries now share a need for AI learning options. This has put pressure on companies to provide relevant upskilling opportunities for employees at all levels, and human resources (HR) teams are becoming increasingly creative to fill AI skills gaps.
The Need for AI Skills
As many as 57% of C-suite executives acknowledge that their company lacks the necessary AI skills and knowledge to grasp the risks and opportunities presented by the technology. This gap can present a significant challenge for HR and learning and development (L&D) teams. They are tasked with developing training programs that not only bridge these technological skills gaps but also deliver a clear and quick return on investment (ROI) for the company.
Some organizations are making plans to address this training gap. For example, in a SHRM article, “Rising Demand for Workforce AI Skills Leads to Calls for Upskilling,” IBM requires employees to perform at least 40 hours of learning annually, with a focus on AI, and provides career pathways that align with skill attainment. The company provides learning tools for their workers to proactively reskill and upskill as their jobs are transformed by AI. Meanwhile, Intel recently expanded its “AI for Workforce Program” to 18 additional colleges, offering essential skill training in computer vision, AI and data collection. Even with these types of programs growing in frequency, there is a lot more work to be done to bring the entire workforce up to speed with AI.
Training for AI Expertise
Many company and HR leaders are becoming aware that they need to focus on training workers for emerging technologies to close AI skills gaps. These organizations want to equip their senior leaders with the strategic insights needed to deploy AI effectively across organizations and provide technical professionals, such as engineers, with the skills needed to develop, scale and implement AI solutions.
However, to ensure strong outcomes, companies must not overlook the development of soft skills among their employees. While AI is transformative in many respects, it doesn’t possess the capability to fully comprehend or manage human emotions, an element that is vital for leadership, teamwork, negotiation and customer service. If companies prioritize AI-related upskilling at the expense of continuous training in soft skills, the overall health of the business could be at risk.
That’s why the first step to building the right training program is to develop curricula that emphasize a blend of soft skills like creative problem-solving and communication and technical skills, including programming, machine learning, big data, neural networks and deep learning. For example, a coding workshop can include activities that require teamwork and collaboration with metrics to assess both technical and soft skill development. Use feedback, performance reviews and self-assessment tools to track employee progress and identify areas for improvement.
Second, consider that not everyone is comfortable with or has the technical background to immediately jump into advanced AI topics. One thing that can help prepare workers is to relate AI to everyday tasks your team already does. For instance, if your team handles customer service, show them how AI chatbots can help handle common inquiries. This can make AI feel less abstract and more relevant. Another way to increase comfort with AI learning is to share examples of how AI has already benefited your company or other companies in your industry. Success stories can be very motivating and make the benefits tangible.
Third, be flexible. AI technologies are constantly changing and advancing, and you may have to consistently update your curriculum to reflect that. To deliver this type of more dynamic content, L&D leaders are incorporating tools such as adaptive learning platforms and virtual reality. For instance, Microsoft leverages VR technologies to provide immersive and interactive training environments. These approaches cater to individual learning needs and drive engagement and training outcomes.
Fourth, let employees use AI on a daily basis. People learn best by doing. Set up workshops where employees can play around with AI tools and start with simple exercises, like using AI to sort data or predict trends. It’s like learning to ride a bike — start with training wheels.
Training employees on how to use AI technologies with these approaches underscores the importance of continuous learning and the need for programs that can rapidly adapt to evolving technological landscapes. By integrating hands-on, practical projects into learning programs, employees can learn how to apply AI concepts in real-world scenarios. This reinforces theoretical knowledge and can help identify gaps in skills that can be addressed in future training sessions.
A Final Caution
AI is evolving rapidly, offering substantial advantages for companies that strategically deliver AI training and development to their workforce. However, as AI assumes greater responsibility for repetitive or routine cognitive tasks, fostering a deep connection with, and understanding of, people also becomes increasingly indispensable. By enhancing these strengths within your teams as you incorporate AI into your upskilling initiatives, you can position your employees for success in the present and in an AI-driven future.
