In the rapidly evolving landscape of artificial intelligence (AI), the skills gap remains a significant challenge for employers hoping to take advantage of these new technology resources. As the demand for AI skills surges, many companies struggle to find qualified professionals who have the desired technical knowledge. Addressing this gap is crucial, not only for maintaining a competitive advantage but also for driving innovation and growth.
By investing in upskilling existing employees, companies can cultivate a workforce adept in AI, ensuring they stay ahead in the tech-driven future. Dahl Consulting offers key insights and tips to help companies navigate employment trends, including AI developments. In this article, discover what the AI tech skills gap is, how you can identify areas for training, and how to implement training programs. Plus, discover ten learning resources to help your organization get a head start on upskilling your key team members for AI utilization.
Understanding the AI Tech Skills Gap
The AI tech skills gap refers to the shortage of professionals with the necessary skills and knowledge in artificial intelligence technology. As the demand for AI continues to grow, employers are finding it increasingly difficult to find qualified individuals who know how to use these tools in their daily work.
Many companies are adopting a “buy vs. build” approach, planning to hire talent with existing AI skills instead of upskilling existing workers. This tactic is problematic, however, as there is a shortage of talent available in the market with these skills, hence the skills gap. Even within the technology sector, 95% of leaders at tech companies are struggling to find skilled talent with top-notch AI skills, and 51% anticipate hiring issues due to this skills gap.
There is also a disconnect between companies that want to hire candidates with AI skills versus the number of companies willing to offer training on these skills. A global survey by the Boston Consulting Group revealed that 86 percent of employees anticipated needing AI training, yet only 14 percent of front-line staff had actually received any upskilling.
Another one of the main reasons for the AI tech skills gap is the rapid advancement of technology. As AI continues to evolve, new skills and knowledge are constantly required to keep up with the latest developments. This creates a challenge for employers who need employees with up-to-date AI skills. Similarly, the AI tech skills gap can also be attributed to the lack of educational programs and training opportunities in AI. Many traditional educational institutions have not yet fully incorporated AI into their curriculum, leaving a gap in the market for specialized AI training programs that both educational institutions and professional workplaces have yet to fill.
Understanding the AI tech skills gap is the first step for employers to address this issue and develop effective training solutions.
Identifying Key Training Needs
To bridge the AI tech skills gap, employers will first need to identify the key training needs of their workforce. This involves assessing the current skills and knowledge of employees and determining the specific areas where training is required. Managers and employees should work together to identify key tasks where training could be the most helpful before moving forward with creating learning and training opportunities.
One way to identify key training needs is through skills assessments and evaluations. Employers can conduct assessments to understand the proficiency levels of employees in various AI technologies and identify any skill gaps that need to be addressed.
Another approach is to gather feedback from employees themselves. Surveys and interviews can be conducted to understand their training needs and preferences. This can help employers tailor the training programs to meet the specific needs of their workforce.
It is important to note that as this technology continues to develop and evolve rapidly, these assessments and conversations should be ongoing. New learning and development needs may arise after initial assessments, so remaining dynamic is the best way to continually work toward closing the AI technology skills gap. Adopting a culture of experimentation with new tools and AI developments is a great way to stay ahead of the curve.
By identifying the key training needs, employers can ensure that the training programs are relevant and targeted, maximizing the impact on closing the AI tech skills gap.
Implementing Tailored Training Programs
Once the key training needs have been identified, employers can implement tailored training programs to address the AI tech skills gap. These programs can be designed to provide employees with the specific skills and knowledge required for their roles. While some trainings, such as how to tailor good prompts for generative AI tools may be helpful organization-wide, the kind of learning should be customized for each department or role to achieve maximum effectiveness.
There are various approaches to implementing tailored training programs. Employers can offer in-house training programs, where employees receive training from internal experts or external trainers. This allows for a customized learning experience that is tailored to the organization’s specific needs.
Another option is to provide employees with access to external training resources, such as online courses or workshops. These resources can offer a wide range of AI training topics and allow employees to learn at their own pace.
Additionally, employers can consider partnering with educational institutions or AI training providers to develop specialized training programs. This can ensure that employees receive industry-recognized certifications and qualifications.
Our employment experts have identified a few resources and courses below, categorized by price point. These resources can be used as a starting point for leaders to begin educating themselves and employees on AI skills. As previously stated, it is important that leadership identifies and customizes key areas of development in order to implement the most worthwhile learning opportunities for their organization.
AI Training Resources & Courses
Low-Cost Resources (Free to $)
- Introduction to Generative AI Learning Path (Google Cloud): This course provides an overview of AI concepts, including language models, ethical AI usage, and more.
- 8-hour course
- Free
- Building a Generative AI-Ready Organization (AWS via Coursera): In this course, learn the practical applications for generative AI for businesses and how to use these tools to drive organizational success.
- 1-hour course
- Free
- Introduction to AI (Udacity): Offered by Udacity, this course introduces AI concepts, techniques, and tools, and explores how businesses can leverage AI to drive innovation and growth.
- Free course, or $$$ monthly fee for full Udacity access
- AI for Business Leaders (edX): This course from edX explores the fundamentals of AI, its potential impact on businesses, and how organizations can develop an AI strategy.
- 2-week program, 1-2 hours per week
- Free, with optional upgrade available
Moderate Cost Resources ($$ to $$$)
- AI for Everyone (Coursera): Offered by Deeplearning.ai, this course is designed for non-technical professionals and aims to provide a basic understanding of AI concepts, applications, and implications for various industries.
- 6-hour program
- Free to enroll, $$$ for course
- Professional Certificate in Artificial Intelligence for Business (Wharton, University of Pennsylvania): This comprehensive program from Wharton covers AI technologies, applications, and strategies for integrating AI into business processes.
- 4-6 week course, 2 hours per week
- $$$
- Artificial Intelligence & Machine Learning for Business (Udemy): This course from Udemy is geared toward managers, leaders, and entrepreneurs. Learn practical applications, AI disruptions in specific industries, and how you can apply AI and Machine Learning for business success.
- 6-hour course
- $$
High-Cost Resources ($$$ to $$$$)
- AI Foundations for Business (Microsoft): This course from Microsoft Azure is tailored for business professionals and covers topics such as AI principles, ethical considerations, and how AI can be applied to different business functions like customer service, marketing, and operations.
- 16-week program
- $$$$ program
- AI Certification Programs from Professional Organizations: Some organizations like the Association for Intelligent Information Management (AIIM) and the Institute for Robotic Process Automation & Artificial Intelligence (IRPA AI) offer AI certifications tailored for business professionals and non-technical roles.
- AIIM courses:
- Depends on course, 4 to 26 hours
- $$$$
- IRPA AI Courses
- 6-week on-demand program, 2-3 hours per week
- $$$$
- Artificial Intelligence Courses (Simplilearn): Simplilearn provides a variety of courses covering AI, machine learning, and deep learning. Their courses include use cases and practical applications of AI in various industries.
- 4-11 month courses
- $$$$
- AIIM courses:
These introductory courses, programs, and certifications can help non-technical office employees and business leaders understand the basics of AI, its potential applications in the workplace, and how to effectively collaborate with technical teams implementing AI solutions.
Measuring Training Success
Measuring the success of training programs is essential to ensure that the AI tech skills gap is effectively bridged. Employers need to have a mechanism in place to evaluate the impact of the training and determine its effectiveness.
One way to measure training success is through assessments and evaluations. Employers can conduct post-training assessments to gauge the improvement in employees’ AI skills and knowledge. This can help identify any gaps that still need to be addressed and make necessary adjustments to the training programs.
Another approach is to gather feedback from employees about their learning experiences using surveys or interviews. These can be conducted to understand employees’ satisfaction with the training programs and whether they feel more confident in applying their AI skills in their work.
Additionally, employers can track the performance of employees after the training to assess the impact on job performance and productivity. This can provide valuable insights into the effectiveness of the training programs and the overall bridging of the AI tech skills gap. Booz Allen Hamilton consulting firm, the largest provider of AI to the federal government, had great success. Jim Hemgen, Director of Talent Development, shared that “Using GenAI has reduced our content production time by hundreds of hours as well as brought down production costs.”
Overall, by measuring training success, employers can continuously improve their training programs and ensure that the AI tech skills gap is effectively addressed.
Empower Your Workforce with Dahl Consulting
Bridging the AI skills gap is imperative for organizations aiming to thrive in today’s technology-driven world. Through targeted training solutions, employers can empower their workforce with the necessary AI skills, fostering innovation and efficiency.
Dahl Consulting stands as a trusted staffing partner for driving business success, providing not only expert insights but also the skilled employees you need to support your business. Get connected with our employment experts today!