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Upskilling and Reskilling in the Age of AI

What Organizations Need to Know

Christina Catenacci, Human Writer

Jan 20, 2025

Key Points:


  • Upskilling is the process of improving employee skill sets through AI training and development programs

 

  • Reskilling is learning an entire set of new skills to do a new job

 

  • It is not possible to have a one-time upskilling and reskilling session—rather, upskilling and reskilling is a continuous learning process


IBM’s Institute for Business Value states that more than 60 percent of executives predict that Gen AI will disrupt how their organization designs experiences; even more striking, 75 percent say that competitive advantage depends on Gen AI. In a study by Boston Consulting Group where 13,000 people were surveyed, 89 percent of respondents said that their workforce needed improved AI skills—but only six percent said that they had begun upskilling in “a meaningful way”.


Clearly, organizations that are not beginning the process of upskilling and reskilling can be at a disadvantage in this competitive game and risk being left behind. This may be why the AI Age is commonly referred to as an era of upskilling.


What is upskilling and reskilling?


IBM notes that upskilling and reskilling are two different things. In particular, upskilling is the process of improving employee skill sets through AI training and development programs. The goal is to minimize skill gaps and prepare employees for changes in their job roles or functions. For example, it could include asking customer care representatives to learn how to use Gen AI and chatbots to answer customer questions in real time with prompt engineering.


On the other hand, reskilling is learning an entire set of new skills to do a new job. For example, someone who works in data processing might need to embrace reskilling to learn web development or advanced data analytics.


Organizations Need to Prioritize Upskilling and Reskilling


According to a report by KPMG, organizations are increasingly prioritizing upskilling and reskilling their workers to harness the power AI and realize true business value. The authors point out that the impact of AI transformation is often underestimated—AI is expected to surpass human intelligence, and organizations cannot be complacent.


Only 41 percent of organizations are increasing their AI investments. This is concerning since Gen AI is not like past disruptive technology; there can be no one-time upskilling and reskilling session, but rather a continuous learning process that takes place.


Leaders in organizations need to get past employee resistance and help to drive AI adoption. How can this be accomplished? The authors note that leaders need to be equipped with the right mindset, knowledge, and skills to guide their AI transformation. By actively using AI in their own work and sharing their experiences with their teams, leaders can create a safe environment for exploration and experimentation, and this in turn helps to create a culture of innovation and continuous learning.


Most importantly, the authors state that leaders need to communicate the benefits of AI clearly and transparently: they need to share how the technology can augment and enhance human capabilities rather than replace them.


An In-depth Study on Reskilling and Upskilling


In an instructive report by World Economic Forum (in collaboration with Boston Consulting Group), the authors introduced an approach to mapping out job transition pathways and reskilling opportunities using the power of digital data to help guide workers, companies, and governments to prioritize their actions, time, and investments on focusing reskilling efforts efficiently and effectively.

To prepare the workforce for the Fourth Industrial Revolution, the authors stated that it was necessary to identify and systematically map out realistic job transition opportunities for workers facing declining job prospects. When mapping job transition opportunities, the authors asked whether the job transition was viable and desirable.


They broke down jobs into a series of relevant, measurable component parts in order to systematically compare them and identify any gaps in knowledge, skills, and experience. Then, they calculated “job-fit”’ of any one individual on the basis of objective criteria.


They asked whether the job was viable and desirable. Viable future employees were those who were equipped to perform those tasks (individuals who possessed the necessary knowledge, skills, and experience). When it came to whether the job was desirable, some jobs were simply undesirable because the number of people projected to be employed in this job category was set to decline. Using the United States Bureau of Labor Statistics, the authors aimed to find job transition pathways for all.


Let us take an example: the authors discovered several pathways for secretaries and administrative assistants. Some provided opportunities with a pay rise, such as insurance claim clerks, and some provided opportunities with a pay cut, such as library assistants or clerical workers.


The authors emphasized that employers could no longer rely solely on new workers to fill their skills shortages. One of the main issues was the willingness to make reasonable investments in upskilling and reskilling that could bridge workers onto new jobs. Similarly, they stressed that it was not possible to begin the transformation unless there was a focus on individuals’ mindsets and efforts. For instance, they reasoned that some employees would need time off of work to gain additional qualifications, and some would require other supports and incentives to engage them in continuous learning. This transformation could involve a shift in the societal mindset such that individuals aspired to be more creative, curious, and comfortable with continuous change.


Moreover, the authors noted that no single actor could solve the upskilling and reskilling puzzle alone; in fact, they suggested that a wide range of stakeholders (governments, employers, individuals, educational institutions and labour unions etc.) needed to collaborate and pool resources to achieve this goal. Further, data-driven approaches were anticipated to bring speed and additional value to upskilling and reskilling. For example, it may be worth exploring the amount of time required to make job the various transitions, or nuanced evaluations of economic benefits from these job transitions.


How do Organizations Begin Upskilling and Reskilling?


When it comes to upskilling, BCG recommends that organizations:

  • assess their needs and measure outcomes

  • prepare people for change


  • unlock employees’ willingness to learn

  • make adopting AI a C-Suite priority

  • use AI for AI upskilling

Moreover, IBM recommends creating a lasting strategy, communicating clearly, and investing in learning and development. Some AI tools that are critical to upskilling include computer vision, Gen AI, machine learning, natural language processing, and robotic process automation.


Upskilling use cases include customer service, financial services, healthcare, HR, and web development. Organizations can use AI technologies to enhance the AI learning experience itself via online learning and development, on-the-job training, skill-gap analysis, and mentorship. AI can provide added value for organizations because it combines institutional knowledge with advanced capabilities, fills important gaps, improves employee retention, and embraces the democratization of web development.


Furthermore, McKinsey & Company recommends that organizations use a cross-collaborative, scaled approach to upskilling and reskilling workforces. More specifically, to realize the opportunity of Gen AI, a new approach is required to address employee attraction, engagement, and retention.


That is, before rushing in and starting the process, it is important to clarify business outcomes and how Gen AI investments can enable or accelerate them. This involves defining the skills that are required to deliver these outcomes and identify groups within the organization that need to build those skills.


In addition, it is necessary to use a human-centred approach—from the outset, organizations are recommended to acknowledge that many employees experience upskilling and reskilling as a threat to their well-established professional identities. To address this issue, organizations need to lead using an empathetic, human-centered approach—foster learning and development and transform fears into curiosity—cultivating mindsets of opportunity and continuous learning.


And of course, it is necessary to make personalized learning possible at scale. This involves having tighter collaboration across the HR function, stronger business integration to embed learning experiences into working environments, and a refreshed approach to the learning and development technology ecosystem.  


Benefits of Upskilling and Reskilling in an AI-Driven Environment


There are several benefits of upskilling and reskilling:

  • Organizations can remain competitive

  • Employees can increase engagement and job satisfaction

  • Workers with enhanced skills can improve their creativity, productivity, and efficiency

  • Organizations can help employees reduce the risk of job displacement

  • Employees can increase wages and enjoy better job opportunities

  • Organizations can increase their retention numbers

 

Indeed, according to an MIT study, evidence suggests that Gen AI, specifically ChatGPT, substantially raised average productivity. Moreover, exposure to ChatGPT increased job satisfaction and self-efficacy, as well as concern and excitement about automation technologies.


We know that employee development programs, including upskilling and reskilling, are highly valued by workers. More precisely, employees appreciate the following:


  • Skill assessment and analytics


  • Personalized learning paths


  • Adaptive learning platforms


  • AI-powered content curation


  • Virtual assistants and chatbots


  • Simulation and gamification


  • Predictive analytics for training ROI


  • Natural language processing for feedback and coaching


  • Augmented reality (AR) and virtual reality (VR) for leaning, mentoring, and training


  • Continuous learning and adaptation


What We Can Take From all This


Given the above, itt may be in organizations’ interests to start the process of upskilling and reskilling, as recommended above. No one wants to find and hire new people: turnover costs organizations a great deal of money. And no one wants to stand by and watch an employer replace them with a robot or other form of Gen AI. The solution is to take the time to create a solid plan, beginning with outlining goals and aligning them with what the business needs.


It is true: HR professionals who have an upskilling and reskilling plan look a lot more enlightened than those who view AI as a threat.


As seen in the 2024 Work Trend Index Annual Report by Microsoft and LinkedIn, it appears that many employees want, and even expect, this type of training and development at work. Employers need to catch up to the employees, given that 75 percent of employees are already bringing AI into the workplace.

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