The skills gap isn’t just widening. It’s accelerating at a pace that traditional training simply cannot match. The World Economic Forum says nearly half of workers’ core skills will be disrupted by 2027, and this is largely due in part to AI, automation, and other technological advancements.
While artificial intelligence is behind this disruption, it can also offer a powerful solution by transforming how organizations identify, develop, and measure critical capabilities across their workforce. As AI adoption accelerates across industries, learning leaders are rethinking how to close skills gaps at scale.
When your teams struggle to keep pace with technological change, AI becomes more than just another tool. It becomes the bridge between your current workforce capabilities and the skills your organization needs to thrive in an increasingly complex business landscape.
What is an AI skills gap and why is it happening?
A skills gap happens when your employees’ abilities don’t match what your organization needs to succeed. AI skills gaps are growing wider because technology evolves faster than traditional training methods can keep up.
While the majority of companies (75%) are quickly incorporating AI into their systems and functions, only 35% of workers have been receiving AI training or upskilling.
This AI skills gap results also means job requirements are changing rapidly as AI technologies, automation, and digital transformation reshape entire industries. The skills that were valuable yesterday might be obsolete tomorrow, leaving your teams struggling to adapt.
Traditional training programs or learning approaches make this problem worse because they can’t scale effectively or personalize development for each employee. One-size-fits-all training simply doesn’t work anymore.
Without intentional AI adoption, many organizations risk falling further behind as job roles evolve faster than their learning strategies.
What are high-demand AI skills?
According to research by Deloitte, the most on-demand AI skills are those that need to be used to build and deploy AI—skills typically executed by AI researchers, software developers, and data scientists. Think of those as AI roles.
The skills from these roles include knowledge and application of gen AI, large language models (LLMs), natural language processing (NLP), machine learning (ML), and deep learning.
But high-demand roles are not necessarily completely zeroed in on AI expertise. They still include project managers, change management experts, user-experience designers, and subject matter experts, whose critical thinking and decision-making skills are fundamental to bridging the gap between AI adoption and AI use.
According to the World Economic Forum, other high-demand skills include creative thinking, analytical thinking, curiosity and lifelong learning, and resilience, flexibility, and agility.
How do we close the AI skills gap?
The first step in closing the AI skills gap is identifying where the gaps actually are. The good news? Youdon’t have to guess. Your learning platform’s analytics can give you a clear view of high-demand skills by comparing workforce capabilities with business needs—making your upskilling strategy more targeted and data-driven.
But that’s just the starting point. According to the MIT Sloan School of Management, Johnson & Johnson tackled this challenge by using a process called skills inference. They began by defining future-ready roles and building a taxonomy of the skills those roles would require—not just today, but five to ten years down the road.
Then, they analyzed employee data from HR systems, project tools, and learning platforms to map existing competencies and identify skill gaps. An AI model was used to assess proficiency, which employees validated through self-assessments. Importantly, all of this was done for development purposes—not performance reviews—helping build trust and boost participation.
The result? J&J saw a 20% increase in learning platform engagement, and 90% of technologists actively used the system for career development.
This kind of approach isn’t just about identifying the gaps—it’s about building a scalable infrastructure for growth. That means going beyond course catalogs. To close the AI skills gap, you need to embed AI into your learning systems as well.
Establishing an AI literacy program across the organization is a powerful next step. But this shouldn’t just be a one-time initiative. It should reflect a culture of continuous learning—one that adapts to evolving skills and new technologies.
Address the AI skills gap with an AI learning platform
By implementing AI-powered learning platforms that offer hyper-personalized, adaptive pathways, you give every employee the opportunity to learn at their own pace, on their own terms. Whether it’s an entry-level hire or a senior engineer, AI can recommend the right content, surface relevant skills, and even coach people in real-time.
That’s how you close the gap—not just by identifying what’s missing, but by creating the conditions to grow what’s next.
AI-powered learning platforms are fundamentally changing how organizations develop talent, moving from periodic training events to continuous capability building integrated into everyday work.
Organizations that embrace AI for skills development gain a significant competitive advantage through greater adaptability and innovation capacity. Their workforces become more resilient to technological disruption and market changes.
Explore why more than 3,800 companies across the world leverage Docebo’s enterprise AI learning platform. Book a demo today.
