The rapid emergence, excitement and adoption of AI among organizations is changing how we work at an unparalleled pace. But while AI promises to deliver a slew of productivity and innovation gains, the biggest concern is how it will affect jobs in the future, with an estimated 400 million jobs to be eliminated by 2030.
To combat this, over 85% of employers plan to prioritize reskilling their workforce, according to a recent World Economic Forum report. Reskilling offers irrefutable benefits to employees, providing them with new skills to advance in their roles and careers. For employers, reskilling also ensures that workers can develop the skills necessary for the fast-changing workplace, while boosting employee productivity, morale and retention.
However, traditional reskilling was not built for this moment. The labor market transformation is already happening as organizations – including Meta, Workday and DBS – are diverting resources to AI and slashing jobs. The trend is expected to continue, with 41% of employers planning to downsize their workforce as AI increasingly takes over certain tasks. Additionally, a recent survey of CHROs found that a mere 7% are implementing reskilling strategies for jobs that will be replaced by AI.
Traditional Reskilling Does Not Meet Today’s Needs
Historically, one of the biggest challenges in reskilling is the time required to develop the learning & development (L&D) programs to effectively boost workers’ existing skills. For HR and L&D professionals, simply identifying skill gaps and anticipating future needs is just the start of the process. HR leaders require C-level buy-in to design and develop reskilling coursework, which then requires precious time to be taken away from other business activities for the training to be rolled out. For L&D professionals, many hours are also needed to schedule the training, create learner to-dos, set up event reminders, provide adequate learning support, track progress, and assess employee performance and results.
This extensive time and cost investment in reskilling means that it’s no wonder that companies are seemingly sidelining such efforts to focus on immediate gains. It can take an organization 18 to 24 months to develop a new upskilling program—-and in that time, the needs of the organization, and potentially even the skills themselves have changed.
Rapid Reskilling, Now Made Possible
While perceptions exist even among L&D and HR leaders that reskilling is too time-consuming and expensive, the irony is that AI is now able to address these core issues. For example, the most time-consuming aspects of reskilling initiatives lie in administrative tasks, including scheduling, sending announcements to employees, nudging them to complete any activities or coursework, tracking participation and progress (often through some kind of learning management system), and collecting post-training feedback to help refine future programs. Today, AI can greatly decrease or eliminate these tasks, giving L&D professionals time to concentrate on the reskilling program itself, and expanding it throughout the organization.
For example, at one organization we work with – a multinational food company – using AI-powered automation, improved the number of learners in a “high-touch” program by over 9x while slashing the workload by over 50%. This allowed the L&D team to focus on higher-impact initiatives rather than tasks such as scheduling, attendance tracking, and follow-ups. Another customer, Procore, has developed technology courses for their engineering organization in a matter of days, not months—allowing them to be agile and responsive to the shifting needs of the organization.
Additionally, AI is addressing one of the long-held challenges that companies have faced when it comes to reskilling: does it actually work?
In his famous Two Sigma Problem paper, Benjamin Bloom discovered that students who receive one-on-one tutoring perform significantly better than those in traditional classrooms—with a gap so large it seemed impossible to bridge on a large scale. But today, with AI-powered personalized learning, we are on the brink of realizing this long-elusive promise. AI can deliver adaptive, real-time feedback, tailor educational content to individual needs, and simulate the benefits of expert tutoring for millions. This revolution in reskilling means that workers can rapidly and efficiently acquire new competencies, ensuring that they remain competitive in an era of relentless technological change. AI can now role play scenarios, practice tough leadership situations, give personalized feedback on coding assignments, and keep employees motivated with the right support. What once seemed like a utopia for education is now a reality, opening up unprecedented opportunities for lifelong learning.
Embracing Meaningful Learning
While deprioritizing reskilling may not have overt ramifications initially, if it’s not a consistent priority it will have compounding issues for both individuals and employers. For employees, a lack of reskilling opportunities can foster greater job dissatisfaction, reduced job security, and career stagnation.
Meanwhile, companies that are perceived to disregard or deprioritize skills programs could face challenges in hiring and retaining staff, and a backlash against their brands. When Meta recently announced job cuts while simultaneously investing in more AI projects, criticism from laid off workers was swift, outspoken and severe. And when nearly half (48%) of American workers say that they’d switch jobs if it provided skills training opportunities, reskilling is a simple yet effective strategy to drive positive attitudes and morale. Moreover, it’s ultimately a waste of resources—-finding talent that fits a company’s bar and culture is expensive. It is far cheaper to reskill people in the future job needs–organizations can save around $20,000 per employee by building skills from within, rather than hiring externally
AI is undeniably transforming the skills and jobs landscape, making upskilling and reskilling more critical than ever. But tackling this challenge with outdated methods is a losing battle. To keep pace with change, organizations must embrace AI-native tools that accelerate reskilling, streamline learning, and deliver highly personalized experiences. The future of work belongs to those who can adapt—and the key to adaptation is not just learning new skills, but doing so with the speed and precision that only AI can enable.
