AI Skills Gap: The Critical Challenge in Workplace Transformation

Why workers must upskill as AI accelerates workplace changes

Governments must act now on AI upskilling and invest in talent programmes, so that every member of the workforce can reach their potential. This year's World Economic Forum Future of Jobs report shows that business leaders and their employees are navigating unprecedented macroeconomic forces - chiefly the technological progress driven by artificial intelligence (AI) and Generative AI (GenAI) - and these are set to transform the labour market over the next five years. Business leaders and professionals are feeling the impact of these rapid workplace shifts. LinkedIn's Work Change report found that worldwide, seven out of every 10 executives say the pace of change at work is accelerating. Almost two-thirds of professionals report feeling overwhelmed by how quickly their jobs are changing. This is hardly surprising. As LinkedIn data shows, the jobs we do and the skills we need to do them are being transformed. We know that for every 10 professionals, at least one has a job title that didn't exist in 2000. They might be a data scientist or an AI engineer; 25 years ago, that wouldn't have been an option. The skills needed for work are expected to change by 70% by 2030 too. That massive shift is being accelerated by AI. The Future of Jobs report found that six out of every 10 business leaders expect AI and GenAI to transform their organizations. The technology holds so much potential and businesses that aren't embracing it risk being left behind. Individuals and businesses are beginning to upskill on AI as they race to keep up - the question is whether this is happening fast and broadly enough to meet this moment of transformation. Globally, the proportion of workers with AI skills has increased by at least 100% across all sectors since 2016, which shows a whole range of professionals are preparing themselves for the new future of work. But, the concentration of AI talent is still comparatively low and not enough attention is being paid to the broader upskilling that would allow workers to make the most of the AI transition. Business leaders must think carefully about designing effective strategies to equip workers to unlock the potential of AI. This requires a detailed understanding of the skills professionals have, the skills they want and the skills they need. LinkedIn has identified three core groups of skills that will be impacted by AI, and most prominently by GenAI. GenAI technologies require AI literacy skills that enable professionals to use tools such as ChatGPT and Microsoft 365 Copilot, which are already changing how we work. Data shows that AI literacy is a major focus for upskilling. In the EU, for example, the number of professionals adding these skills to their profiles was 80 times greater in 2023 than in 2022. But, while GenAI is capable of learning hundreds of skills - like writing, editing and data analysis - there are hundreds more skills that GenAI doesn't have. Crucially, these are people skills, like leadership, teamwork, negotiation and relationship building. These skills are critical for the implementation of AI technologies and for successful business operations more broadly. Effective skills policies will be those that train workers to use AI and GenAI technologies, while also helping them to future-proof their role and position in the workforce by supporting the development of strong people skills. Success in AI isn't just about investing in new technologies. There's no point in having the best AI technology if no one knows how to use it. That's why it's time to strategically design skills policies that prioritize continuous learning and are designed to factor in AI skills alongside rich people skills. And, central to effective skills policies is accurate, real-time data, which shows how talent is developing and where it's being deployed across the economy. Effective skills policies are key to a fast and fair AI transition. Governments across the world must act now on AI upskilling and invest in talent programmes, so that every member of the workforce can reach their potential. This is the only way to ensure we are leveraging the full potential of AI to boost economic growth.

63% of employers say skill gaps are the biggest hurdles to AI adoption

As organizations everywhere race to integrate AI into their ways of working, a significant barrier persists: skill gaps. According to a recent Accenture report, 63% of employers identify these gaps as the primary obstacle to adopting AI technologies. And this doesn't just apply to worker bees. While 97% of executives believe AI will fundamentally reshape their industries, 65% also admit they lack the technological expertise to lead these transformations effectively. 5 jobs hiring across the U.S. Trust gap At the same time, there's a clear disconnect between employers and workers. Though most employees (82%) feel confident in their ability to grasp AI technology, and an overwhelming 94% express confidence in their ability to develop the necessary AI skills, employers remain skeptical about their readiness. A "trust gap" is brewing between leadership and their workforce, says Accenture. Its research outlines that successfully leveraging AI requires more than simply deploying new tools as "digital coworkers', though that is a "compelling start". Moreover, it recommends that organizations fundamentally reimagine how traditional workflows, functions, and even jobs are defined. And this means holistically integrating technology, talent, and processes. Bridging the gap Unlike traditional upskilling, Accenture says that the half-life of skills (the time period in which skills are relevant to an organization) will plummet. Continuous and tandem human and AI agent learning will be important. As people and intelligent agents co-learn, the report says they will begin to innovate together. It's up to leadership to create structure and incentives for this new way of continuous upskilling, and this means breaking innovation out of tightly-managed centers of excellence (CoE). It asks: "What if innovation were not prescribed to a place and time, but rather bubbled up from the edges of the organization, where individuals and teams have direct insights into customer needs?" Individual and team innovation sounds positively utopian, but what practical steps can be taken to get there? It doesn't really explain how "connective intelligence tissue" will be set up -- perhaps that's a selling point for their consultancy services -- but does say when it's combined with AI agents, employees will need to develop new skills inline with these capabilities, integrating them into their everyday working practices. Organizations must enable employees to acquire and apply skills, quickly and continuously. Dynamic skills With the rise of AI, it's predicted that job advertisements will become more focused on skills, and HR departments will need more focus on predictive workforce planning as the nature of work, tasks, and skills continually evolve. Ethan Mollick of Wharton School, University of Pennsylvania is cited in the report as saying "In the AI future, HR becomes your R&D department." However, this is already the case in many forward-thinking organizations who have deployed advanced-AI recruiting tools, like Robin, and Dash. Both feature easy integration with existing Applicant Tracking Systems (ATS), Teams, and Slack. And it's this kind of easy integration that needs to become the standard to help overcome hurdles to AI implementation. In the coming years, across sectors, curious and inquisitive individuals who demonstrate strong learning agility, and an ability to fuse human and machine skills will become top talent. Organizations will require a "high degree of ambidexterity", so Accenture believes that both generalists and specialists will remain essential. Workers seeking to AI-proof their careers should focus cultivating uniquely human expertise, and fusing human and machine skills. When it comes to upskilling, Accenture comes down hard on on-demand, self-service learning as lacking in personalized guidance, tailored to an individual's role, context, and learning preferences. Instead it favours AI learning agents. "Aware of an employee's changing role, experience and ambition, the agent could proactively suggest upskilling / reskilling paths that are highly tailored to the individual's professional goals, needs and unique learning preferences." It also outlines that L&D functions will be responsible for nurturing continuous learning by embedding it into job roles, which requires collaboration between business and HR leaders. Ultimately, the future of AI adoption lies in its ability to create seamless, intuitive experiences that enhance human capabilities, rather than replace them. By integrating these solutions with existing workflows and systems, organizations can overcome the skill gaps that currently impede AI transformation, but there needs to be a plan. With 57% of employees seeking clarity on what gen AI means for their careers, it's essential for leaders to prioritize transparency. And if this is lacking in your organization, it could be time to look elsewhere.