New Economy Skills 2025

Digital skills learning curves BOX 3 Research from Coursera reveals clear contrasts in the time needed to build digital skills. A basic level can often be achieved within a few days of study, but advancing to higher proficiency demands a far greater commitment, stretching to 108–155 hours, or several weeks of part-time learning (Figure 9). Programming is the most demanding digital skill at the beginner and intermediate stages, requiring comparatively higher investment from the outset. Networks and cybersecurity escalates most sharply, becoming the most time-intensive at advanced levels (around 155 hours), reflecting the growing complexity of securing systems and managing evolving cyber threats. Technological literacy shows a similar steep progression, nearly matching programming in effort throughout. By contrast, AI and big data, along with design and user experience, provide more accessible entry points. Beginners can often start AI with as little as 30 hours of study, as many beginner courses focus on AI literacy fundamentals. Advancing to higher levels, however, demands a significant leap into complex areas such as ML models and data science, with the average time to reach an advanced level estimated at 137 hours. Design and UX maintains the smoothest and least time- intensive learning curve across all stages, reflecting its emphasis on design thinking and user-centred practice rather than deep technical specialization.However, learners seldom acquire skills in isolation. As new skills are taught, they often intersect with complementary abilities. Figure 10 illustrates the interconnectedness of digital skills, showing that they are built on a foundation of human-centric and business skills. Technological literacy emerges as a core competency commonly taught alongside other digital skills, underscoring its role as a base for more specialized expertise. Programming is also frequently co-taught with AI and big data (26% of programming courses also include AI and big data) and with networks and cybersecurity (17%). Likewise, the strong links between UX and AI (26% of UX courses also teach AI) or programming (15%) highlight the growing emphasis on designing technology solutions around user needs. Among human-centric skills, analytical and systems thinking are key complements to digital skills. Mathematical and statistical thinking, leadership and social influence, creative thinking, and dependability also appear frequently alongside digital skills learning. Business-related areas such as resource management, operations, marketing, media, and quality control further highlight the use of digital skills for applied real-world challenges. The urgent need to scale digital talent For businesses to effectively align sought-after talent and skills with their strategic objectives, and for governments to unlock both latent and future opportunities for prosperity, a coordinated effort toward expanding digital skill development is essential. Yet, according to Coursera data on the time required to reach proficiency in digital competencies, significantly increasing the talent pipeline remains a complex and gradual process (Box 3).The journey to mastering digital skills varies greatly depending on the area of focus. While the fundamentals can often be grasped relatively quickly, progressing to higher levels of expertise calls for far greater time commitment. Equally significant are the intricate relationships that exist among various skills. Digital competencies are often interdependent, with these connections enhancing the development of each skill and amplifying their overall impact. The data underscores a central point: digital skills are most powerful when combined with human-centric and business capabilities that allow technology to be applied effectively to real-world challenges. New Economy Skills: Building AI, Data and Digital Capabilities for Growth 16