IIC Journal of Innovation 11th Edition | Page 30

Bridging the Artificial Intelligence Skills Gap in the Machine Manufacturing Industry biggest skill gap in AI and ML spans across the organization. help improve existing employee skills efficiently. The Finnish Artificial Intelligence Programme end report pointed out that based on their survey, Finland has high quality education for those who aim to be AI professionals (e.g. information technology, mathematics), but there is a gap in the AI applier field. In these fields, the effects of AI would be seen fastest. The working group stated that in order to achieve the ambitious AI targets, the most important things are to ensure that versatile education will be available, investments are made in new education methods and programs are created to attract talent to Finland. Much of the employee competencies are based on the on-the-job learning, and thus companies have more responsibility for competence development. Companies are actively seeking for ways to re-educate their employees either internally or in co- operation with other companies. Continuous education of current employees is a challenge, and different operations and mechanisms are needed to address these concerns. A critical factor is to increase management awareness and knowledge regarding the opportunities AI will bring. This is how enough input can be secured for new flexible education methods. Employee competence requirements are affected by the changes in the work demand in the job markets. The need for new talent is increasing at a rapid pace in tasks where AI will be developed and applied. This demand cannot be addressed by the usual education path. Rather, new operations and mechanisms are needed to Today, numerous approaches exist to carry out education, but suitable combinations for workplace learning in Industry 4.0 contexts do not yet really exist. But without an adequate performance appraisal strategy and adequate training of the workforce with suitable educational approaches (e.g. self-regulated, reflective, collaborative, blended learning), there is a risk that workers are excluded from being employed in Industry 4.0 environments and that the expected impact on task performance decreases (i.e. efficiency of production, product diversity and quality). 4 To succeed, companies need to equip their existing professionals with the AI skills to apply their knowledge in the AI-driven world. This is supported by a recent study of Future Workplace and The Learning House (2018) 5 highlighting that training the workforce for AI and ML skills could be the efficient way to fill the skills gap. Letmathe & Schinner (2017) 6 state that the success of workers will depend on their 4 E.Ras et. al (2018): Bridging the Skills Gap of Workers in Industry 4.0 by Human Performance Augmentation Tools – Challenges and Roadmap. Luxemburg Institute of Science and Technology. Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments. Pages 428-432 5 https://www.learninghouse.com/closing-skills-gap-report/ 6 Lemathe P. & Schinner, M. RWTH Aachen University. Competence Management in the Age of Cyber Physical Systems. In book: Industrial Internet of Things. Oct 2017. IIC Journal of Innovation - 26 -