Who Needs to Upskill and Reskill In The AI Era?

More than 90% of leading businesses are already investing significantly in artificial intelligence and it’s predicted to transform almost every industry in the coming years. This is driving a rapidly evolving job landscape where the skills required to succeed are as dynamic as the technologies themselves.

The AI revolution presents opportunities, but also comes with hurdles due to the absence of standardized terminology and insufficient data. Without these ingredients, it’s difficult to conduct a thorough skills gap analysis for your organization’s workforce.

In this blog post, we will explore the most in-demand skills in today's job market, the challenges faced by organizations, and how digital credentials can help learning and development professionals analyze skill data to identify gaps and create targeted upskilling strategies in the era of AI.

Beyond coding: Essential skills for success

As AI-driven technology evolves, the employee skills that experts predict will be most in demand may surprise you. It’s not necessarily coding or other technical skills that will be most needed.

Zahra Bahrolouloumi, CEO of Salesforce UKI believes not everyone needs to learn how to code in the generative AI era. “It’s about showing people where exactly, and often how easily, they can fit into the digital-first workplace.”

While workers need to be digitally savvy to take advantage of AI-powered tools, it’s the things that AI can’t do — such as incorporating critical thinking, collaboration and social intelligence into work — that will be the in-demand job skills of the future. This is supported by recent data from Deloitte, which reports that soft skill-intensive work will account for almost two-thirds of all jobs by 2030.

According to Pearson research, while technical skills and expertise remain highly valued, the top five most sought-after skills (now and in the short-term future) are all human skills.

1. Collaboration
2. Customer focus
3. Personal learning & mastery
4. Achievement focus
5. Cultural and social intelligence

The Challenge of Standardization and Skills Verification

How could organizations determine who needs to develop the latest AI-related skills and who should focus more on their soft skills development?

To ensure their workforce is equipped with the relevant skills, organizations must first have standardized terminology and frameworks for assessing and verifying AI skills. In fact, many individuals already possess relevant skills and knowledge that can be applied to AI. In a global survey of 11,000 workers conducted by Salesforce, only one in 10 employees said their day-to-day role currently involves artificial intelligence, but as AI applications spread, this portion will grow quickly. 

Secondly, developing a big-picture view of what constitutes expertise can be murky when organizations heavily depend on skills inferred by their employees. According to a recent survey of 1,000 working professionals from graphic design company Canva, 26% admit to sometimes exaggerating their knowledge of AI or generative AI to keep up with superiors or colleagues. While 72% of professionals said they were familiar with the term "artificial intelligence," the number dropped to 51% when asked about familiarity with "generative AI."

It also highlights the prevalence of inflated skill claims within the workforce. The lack of skills verification mechanisms, including human skills, can lead to a skewed understanding of the actual expertise within the organization.  

Without clear and consistent terminology and framework to evaluate an organization’s skill inventory, L&D leaders will find it challenging to:

• Identify skill gaps across the organization
• Track skills possessed by employees
• Create consistent job descriptions
• Identify employee opportunities for growth and match these with the right training, at the right level for each individual.
• Effectively allocate training resources to develop needed skill sets

Understanding Where to Invest Efforts

Introducing digital credentials can help organizations develop a data-driven strategy, with credentials and digital badges serving as both an analytic tool and a motivational factor for employees.

With digital credentialing, organizations can

• Develop a common language for describing expertise, making it easier for employers and employees to communicate effectively about skill sets.
• Provide official skill recognition, validate employees’ AI proficiencies, and provide concrete evidence of competency.
• Sustain employee engagement for continuous learning initiatives with personalized learning paths aligned with employee career aspirations.
• Enables features like recommendations, which show employees recommended courses, allowing employees to continue to work on the skills they lack based on data.

Specifically, organizations can develop credentialing frameworks with well-designed taxonomies to create standardized certifications for your organization.

Standardizing the language behind AI training certifications enables data-driven analysis to measure what skills your workforce may already possess and what’s needed for the future. This eliminates guesswork and wasted resources on unneeded training.

Building on this, organizations can use skill data analytics to identify gaps in individual skill sets and design customized learning paths.

The ability of a workforce to effectively use AI as a “co-pilot” to increase productivity gives an organization a significant competitive advantage. Keeping humans in the loop helps companies develop uniquely defensible business models and adapt to unpredictable business environments.

Learn more about adopting a strategic stance toward upskilling with verified skills data with Credly Acclaim.