Global ICT Talent Demand in the Age of AI: Trends, Gaps, and Solutions

The explosive growth of AI is reshaping global labor markets, driving an unprecedented transformation in talent demand for information and communications technology (ICT) — the backbone of the digital economy. According to the ICT Job Roles and Skills in the Intelligent World white paper jointly released by International Data Corporation (IDC) and Huawei, the number of ICT jobs worldwide is expected to increase by 36 million by 2030, bringing the total to over 97 million. However, this opportunity is accompanied by skill gaps and supply-demand mismatches, which are emerging as critical bottlenecks constraining digital transformation. From job restructuring to skill evolution, and from regional disparities to collaborative solutions, the global ecosystem of ICT talent supply is undergoing a profound shift in the intelligent era.

Job ecosystem restructuring: AI-driven creation and evolution

In the era of the intelligent economy, AI is more than just a tool for transforming production — It is also reshaping job functions and skills within enterprises. On one hand, AI has created many new positions, such as prompt engineers, AI training engineers, and model reviewers. On the other hand, AI has made the iterative upgrade of skills a must for traditional ICT positions. For example, today's software professionals must not only be able to collaborate with AI tools to write code but also possess the ability to deeply embed AI capabilities into a wide range of products and build the next generation of intelligent, adaptive solutions.

Of particular note is the growing adoption of AI agents, which is accelerating the transformation of job skills and reshaping employee lifecycle development (see Figure 1). According to IDC's research, 66% of professional services firms and 47% of financial institutions have already heavily invested in the development and application of agents. "Digital employees" are increasingly taking over repetitive tasks, allowing human workers to transition to higher-value roles such as strategic planning and complex problem-solving. This model of human-machine collaboration has become the new normal in the ICT industry.

Figure 1: How agentic applications reshape the employee lifecycle

Given that employee skills are critical in determining the success or failure of enterprises' digital transformation, IDC's data offers cautionary insights: Skill gaps will hinder digital transformation efforts at more than 65% of companies worldwide, resulting in issues such as product development delays and revenue loss. Therefore, enterprises should prioritize investment in the cultivation and recruitment of digital talent.

Widening talent gaps: A global phenomenon with regional disparities

Major economies around the world have made AI-driven growth a strategic priority, and the shortage of ICT talent has evolved from a localized issue into a global, systemic challenge. It is estimated that there are currently around 61 million ICT jobs worldwide, and this number is projected to reach 97 million by 2030 — meaning an additional 36 million new positions over the next five years.

As a major digital economy, China faces particularly strong demand for ICT talent. By 2030, the country is expected to have 10 million new ICT jobs. Although there were 1.1 million computer science graduates in China in 2024, the gap in talent — particularly in areas such as AI development and deployment, cybersecurity, and AI hardware infrastructure — continues to widen, constrained by the disconnect between education and practice amid accelerating innovation. Demand is concentrated in technology hubs like Beijing, Shanghai, Shenzhen, and Hangzhou, where university-based hands-on projects, online training, and vendor micro-certifications are all emerging as popular approaches to cultivating innovative talent.

ICT talent markets in other regions around the world exhibit distinct characteristics (see Figure 2):

Figure 2: Global ICT talent demand

• The North American market is facing a scarcity of high-end talent. The United States is expected to have 6 million new ICT jobs by 2030, with critical shortages in roles such as AI-native architects and large language model (LLM) security researchers. North American companies place a strong emphasis on interdisciplinary collaboration skills, with 51% of enterprises developing talent through a combination of internal training and individual self-directed learning.
• Europe faces an ICT talent gap of 10 million, concentrated in major economies such as Germany and the United Kingdom, where specialists in AI, cybersecurity, and cloud computing are among the most in-demand roles. Overall, limited labor mobility within the European Union (EU), and Europe as a whole, hinders efforts to fill talent gaps across member states. Additionally, while university graduates in Europe generally have strong job-role alignment, there is a notable shortage of mid-level talent.
• In regions like the Middle East and Africa, ICT talent gaps are widening rapidly. By 2030, Africa and the Middle East are expected to have 2 million new ICT jobs each. In these regions, low digital literacy and weak infrastructure are the main factors preventing the rapid closure of ICT talent gaps.

Figure 3: How AI applications reshape job skill requirements

Evolving skills demand: Hybrid competencies and lifelong learning become the norm

We have entered an era of rapid skill evolution. For professionals, traditional expertise in a single technical domain is no longer sufficient to meet business needs. For students, rigid theoretical learning and conventional training are also inadequate to address the innovation demands of an intelligent future. Talent with a hybrid skill set — combining technical expertise, AI literacy, and soft skills — will undoubtedly be the focus of future talent development ecosystems.

At the technical level, the deep integration of AI with business is requiring professionals to surpass traditional skill boundaries and possess both domain-specific technical expertise and AI literacy. For example, cybersecurity specialists need to master the application of AI-driven threat detection tools, cloud computing specialists need to possess the ability to optimize AI resources, and data professionals are expected to be proficient in automated analysis and model validation. What these skills share in common is the deep integration of the "AI + vertical domain".

Furthermore, as intelligent tools mature, the importance of soft skills — such as communication, collaboration, critical thinking, and ethical judgment — will become increasingly pronounced. In fields like AI ethics governance, for instance, competencies in data privacy protection and algorithmic bias mitigation will become differentiating advantages for future ICT talent.

Additionally, the accelerating rate of skill obsolescence will make lifelong learning the norm. The renewal cycle for technical knowledge is now just 18 to 24 months, requiring professionals to continuously upskill through diverse channels — including, but not limited to, participating in corporate training programs, enhancing skills via online platforms or self-study, and contributing to open-source ecosystem projects.

Collaborative solutions: Building a multi-stakeholder talent ecosystem

Given the severity of the talent challenge, the efforts of a single entity are unlikely to succeed. Therefore, collaboration among enterprises, academic institutions, and governments is essential to building a sustainable talent ecosystem (see Figure 4).

Figure 4: An ICT talent cultivation ecosystem driven by industry-education collaboration

Enterprises need to shift from passive hiring to active talent development. On one hand, enterprises should establish dynamic talent strategies, create dedicated roles like Chief Artificial Intelligence Officer (CAIO) to oversee AI talent development, and leverage intelligent tools to analyze skill gaps and design personalized training programs. On the other, they should deepen university-industry collaboration by developing joint curricula, building hands-on labs, and integrating real-world business projects into the talent development process. Collaborative cases between Huawei and Shanghai Jiao Tong University, and Huawei and Shenzhen Polytechnic University, demonstrate that such partnerships can strengthen the technology ecosystem, improve job-role alignment for graduates, and shorten talent training cycles.

Universities need to accelerate curriculum innovation. Universities should break down traditional disciplinary silos and establish flexible, innovation-oriented training models that combine theory with practice. For example, Shanghai Jiao Tong University's Student Innovation Center has significantly enhanced students' hands-on capabilities by providing an AI-focused practice environment. At the same time, universities should strengthen their faculty's industry relevance through industry-education collaboration, joint projects, and lectures delivered by industry experts, ensuring that teaching content stays aligned with the cutting edge of industry development.

Governments should play the role of ecosystem architects and enablers. At the individual level, government departments should recognize short-term skills certifications and open-source project experience. At the university level, they should increase investment in AI labs, cloud sandboxes, and other infrastructure, while promoting pilots for industry-education collaboration. At the systemic level, they should establish unified skill certification standards and use real-time employment data to guide talent development. Initiatives such as the Digital China strategy and the EU's Digital Europe Programme have emerged as key pillars supporting regional ICT talent development.

The global transformation of ICT talent in the age of AI represents both a challenge and an opportunity. Behind the expected 36 million new ICT jobs lies an urgent demand for high-quality talent in the digital economy. Meanwhile, the existence of skill gaps offers clear directions for individual career development, higher education reform, and corporate strategic planning. Moving forward, only by building a collaborative multi-stakeholder ecosystem — one that is led by the industry, supported by universities, enabled by governments, and empowered through open source — can we solve the challenge of misalignment between talent supply and demand.