The fast pace of AI/ML evolution and other domains has created a new revolution across industries, which has never been seen before. The shift is not only showing up in how we work, but it is also forcing employees and companies to ask deep, profound questions. As the future of work becomes increasingly uncertain, individuals are confronted with a pivotal quandary: “Will the relevance of my job be compromised by automation? What steps can I take to be ready for the challenges that will be posed in the future?”
Skill Assessment: Moving Beyond Traditional Methods
We need to rethink how we assess skills in the workforce. The conventional approach is limited since it depicts the skills required for tomorrow in the competencies of today. AI has an enormous potential to create skill baselines, identify gaps and determine meaningful results, but the challenge lies in appropriately interpreting that data. In the context of today’s workforce transformation, traditional methods of evaluating employee skills will struggle to keep pace with the pace of technology and the need to reskill. Traditional assessment and performance evaluation are based on the existing abilities of an employee and will not forecast future needs or reveal potential skill gaps. This is where the chance for AI-driven solutions to add significant value comes forth.
Identifying Emerging Trends
AI can use data analysis available from industry trends, job market data and new technologies to predict future skills that will be in demand.
For example, if AI identifies that a sector needs a particular programming language or data analysis skills to grow, it can alert organizations to make training in those areas their priority to stay in the lead.
Redefining Skill Development: A Shift in Perspective
Normally, organizations have tended to pay little attention to the issue of developing the necessary skills, considering it as an issue secondary to solving immediate problems. Conversely, the growing automation of tasks is a matter of the moment and necessitates the development of workers’ skills. This transformation of the perspectives implies the reexamination of the notion of what the skills are and how they should be cultivated in the corporate environment.
Businesses that intend to be digital-first should be applying AI to do a comprehensive diagnostic evaluation and, in addition, find areas that can be improved on. The evaluation of large databases that contain information about previous successes, new industry tendencies and individual learning styles allows these projects to offer inspiring perspectives of the evolving talent space. As an example, data science may highlight the demand for upskilling in subjects such as data analysis or programming languages so that workers can keep up with the data-driven economy. Similarly, it can provide ways to learn new skills in growing fields like cybersecurity to change careers when industries need different types of jobs.
The Complexity of Skill Evaluation: Exploring New Approaches
The complexity of evaluating skills is even more visible in areas like interpersonal and leadership competencies. It provokes doubts regarding the most efficient evaluation method and puts into question the traditional view of knowledge gaps. Understanding these nuances requires a blend of impartial data science and practical observation to capture the full spectrum of an individual’s capabilities:
- Data-driven ideas used in conjunction with practical observation will provide a more holistic view of how employees use their skills.
- Data science methods are good for observing patterns and trends, while practice observation provides a real-world context.
Therefore, technology can drive data-driven assessment and decision-making on an individual’s strengths and weaknesses, providing the basis for formulating better talent assessment and training methods.
Toward a Future-Ready Workforce
With industries undergoing continuous changes due to digital transformation, meeting the demand for a flexible and adaptable workforce — a workforce that can adjust to various changes becomes a necessity. Holistic skills development needs a broader approach that goes beyond the usual methods of evaluation. The use of innovation and the exploration of new assessment methods will not only help companies to better prepare their employees for the challenges of tomorrow, but it will also help to maintain a competitive edge in a rapidly changing world.
To be successful in the growingly sophisticated and ever-changing workforce, it is imperative to learn how to recognize and develop the required skills quickly and efficiently. Through creating a culture of continuous learning and readiness to adapt, organizations can take the lead in the process of industry transformation, therefore putting workers in the limelight of the changing world.
Founder and CEO, Julia Grace Samoylenko launched Asteri from Palo Alto to tackle corporate challenges like inefficient talent use and high turnover. With more than a decade of Fortune 500 experience, Samoylenko leads Asteri in using AI to turn chaotic employee work data into strategic skill insights. This innovation helps organizations adapt, innovate and thrive, driving global economic growth.
Did You Know: Despite 57% of C-suite executives wanting their companies to provide necessary AI training, only 6% of companies have trained more than a quarter of their employees on AI tools, leaving 48% of U.S. professionals fearing being left behind in their careers due to inadequate AI training opportunities.
