How AI is driving personalized learning at scale
By Mark Onisk (pictured), Senior Managing Director, Talent Strategy & Transformation at Skillsoft
We’re living in an unprecedented time of opportunity and unpredictability. Artificial intelligence (AI) is enabling scalability and productivity like never seen before – but is also a catalyst out of necessity.
Corporations must keep evolving or risk falling behind, given the rapid rate of change and advantages gained by proactive companies. According to research from Amazon Web Services (AWS), 95% of Australian businesses adopting AI report an average revenue increase of 34%. Productivity improvements were noted by 86% of adopters, with 94% anticipating average cost savings of 38%.
Training deficit leading to workforce incapability
A fundamental aspect of successful AI implementation is workforce capability. According to McKinsey, nearly half of employees in the U.S. say they want more formal training, as they believe it’s the most effective way to boost AI adoption, however, as many as a fifth report that they have received minimal to no support.
Closer to home, employees also want more training – but the numbers aren’t as stark. Employees in markets including Australia, Singapore, and the UK report receiving far more support than U.S. employees, with 84 percent saying they receive significant or full organizational support to learn AI skills (versus just over half of U.S. employees).
International employees also have more opportunities to participate in developing gen AI tools at work than their US counterparts, with differences of at least ten percentage points in activities such as providing feedback, beta testing, and requesting specific features.
Skills gaps prohibit growth and AI preparedness
Shortfalls in training are unsurprisingly leading to shortfalls in skills. Skillsoft’s 2025 Global Skills Intelligence Survey, which studied over 1,000 HR and L&D professionals across Australia, the U.S., UK, and Germany, revealed that global organizations face significant growth risks as skills gaps widen, particularly in the face of AI innovation.
The research found that only 10% are fully confident their workforce can deliver on business goals in the next 12–24 months, over one in four (28%) say skill gaps restrict their ability to pursue new markets or opportunities, and a quarter (24%) worry AI is advancing faster than workforce upskilling. Regarding AI adoption, 41% say their workforce is resistant to change and 28% point to the need for greater technical expertise.
AI could, however, provide a new set of analytic capabilities to help make sense of this.
AI-native skills intelligence could be the answer
The organizations winning today and successfully combating some of these challenges are investing in an intelligent workforce, putting skills development center stage, and fostering an environment where people and AI agents unite around projects and break free from the outdated constraints of job titles and traditional employment.
Most talent systems weren’t built for this shift. They were designed to train individuals for set roles as employees, not to develop agile, skill-based teams where humans and AI learn, adapt, and perform together in flexible models.
Now, skills, not roles, are the currency of performance. In the new economy of people-AI collaboration, leaders need real-time visibility into available workforce capabilities – understanding not just what skills exist, but how effectively people and agents can work together. Building this type of workforce isn’t a side task, it’s a core growth strategy – the key to unlocking potential, accelerating performance, and staying ready for whatever comes next.
Personalization and real time tracking
Personalization and scalability can often sound like an oxymoron, but with modern technology – having both is absolutely a possibility, and should be the benchmark.
Having one centralized platform that connects AI-native skills insights, personalized learning paths, and hands-on practice at scale means every team gets exactly what they need, when they need it – to the most granular, contextual detail. This means learning and executing in the flow of work, not against it.
Tools are now available that are easy to integrate and scale, that are built with AI from the ground up, so every part of the system works smarter and faster.
These systems connect learning, talent, and skills tools without costly integrations, and scale with global teams and support learning right in the workflow. They also allow you to assemble best-fit teams of people and AI agents based on real-time skills data, and have direct ROI connection, where skills intelligence drives project outcomes, not just completion rates.
A clear path forward
In the end, the path forward is clear: organizations that embrace AI-powered, skills-focused learning strategies will be the ones best positioned to thrive in a rapidly shifting landscape. By combining personalized development, real-time skills intelligence, and seamless human–AI collaboration, businesses can close capability gaps, unlock innovation, and future-proof their workforce. The challenge is no longer whether AI can scale personalized learning (it already does) but whether leaders will seize the opportunity to make it a cornerstone of growth and transformation.
