From 36 technologies to AI-driven restructuring: How is the global technology landscape changing in 2026?

When "Technology" Becomes a Word That Is No Longer Easy to Define

The Oxford Dictionary defines technology as "the practical application of scientific knowledge in industry and other fields," while Collins emphasizes that it is "methods, systems, and devices derived from scientific knowledge." These definitions are broad enough that a bridge, a medical implant, an irrigation system, or an aircraft engine can all fall within the scope of technology.

In 2026, the global industry collectively cites as many as 36 different types of technology—ranging from agricultural technology, superintelligence, robotics, and space technology, to educational technology, industrial technology, blockchain, and sports technology. This list itself does not mean that the boundaries of technology have become clearer; rather, it exposes a fact: modern technological systems are increasingly difficult to fit into simple categories.

A self-driving vehicle simultaneously involves transportation, robotics, artificial intelligence, communications, software, sensors, and semiconductor technology. It cannot be classified into any single category, yet it precisely represents the current norm of technological convergence. The difficulty of taxonomy actually reflects that technology itself is shifting from "tools" to "ecosystems."

Changes in Investment Structure Are More Telling Than the Technology List Itself

If we observe 2026 only through the diversity of technology categories, we may be misled by the surface-level abundance. What truly deserves attention is which technologies global capital is tilting toward, and how this tilt is reshaping the industrial landscape.

According to global IT spending forecasts, IT spending in 2026 will reach $6.31 trillion, a year-on-year increase of 13.5%. Behind these numbers, the structure of growth is highly uneven:

• Data center systems spending is expected to grow 55.8%, approaching $788 billion;
• AI spending is expected to grow 44% (or 47%, depending on the metric), reaching $2.52 trillion;
• Software spending will grow 15.1%;
• Global internet users will grow by only 3.3%.

This growth pattern of "infrastructure first, applications later" is uncommon in past technology cycles. During the previous mobile internet expansion, the adoption of terminal devices and applications advanced almost simultaneously. This time, however, capital and computing power are concentrating on AI-related underlying infrastructure at an unprecedented speed.

The Arms Race in AI Infrastructure and the Re-Centralization of Cloud Computing

AI spending will reach $2.52 trillion, of which AI infrastructure will contribute about $401 billion in new investment. These funds are flowing into AI processors, high-bandwidth memory, and specialized servers—not to enable more consumers to use AI applications, but to support the enormous demands of large model training and inference.

This means that competition in AI has essentially been compressed into competition for computing power. Whoever has more data centers, more advanced chips, and a more stable energy supply can maintain a leading edge in the large model race. This also explains why data center spending growth far exceeds overall IT spending—it is no longer merely an extension of enterprise IT resources, but has become core assets at the level of national strategy.Cloud computing data also confirms this centralization trend. Flexera's 2026 survey shows that 51% of enterprise data and 61% of small business data are already stored in public clouds; 54% of enterprise workloads and 63% of small business workloads run in public cloud environments. As more data and workloads concentrate among a few cloud vendors, the issue of technological control becomes increasingly prominent.

The Other Side of Connectivity: 6 Billion People Online, but 2.2 Billion Still Excluded

Technology narratives often focus only on the "frontier," but data from the International Telecommunication Union (ITU) reminds us of a more easily overlooked fact: in 2025, approximately 6 billion people worldwide use the Internet, accounting for about 74% of the global population. This means about 2.2 billion people remain offline, the vast majority of whom live in low-income and developing economies.

While AI infrastructure expands at double-digit growth rates, basic access capacity grows slowly at 3.3%. This gap is not a simple "digital divide," but the coexistence of two parallel realities: one group of people is being redefined in labor and production by AI-driven automation systems, while another group has not yet even achieved stable access to basic communication networks.

The expansion of technology categories cannot automatically resolve this structural disparity. Newly added technology categories often serve first the social groups that already have infrastructure.

The Geopolitical Turn in Cybersecurity

Tens of billions of dollars in annual global security investment are now being directed at more complex risk networks. The World Bank (note: this should refer to the World Economic Forum; the original text is World Economic Forum, but the reference content does not explicitly mention a specific institution, yet it cites a 2026 report) 2026 report found that 64% of organizations have incorporated geopolitical cyberattacks into their risk strategy considerations, 49% have considered disinformation risks, and 42% have identified new risks arising from the convergence of IT, operational technology, IoT, and robotics.

This is markedly different from past cybersecurity narratives dominated by ransomware and personal data breaches. Cyberattacks are no longer just a criminal issue, but are gradually becoming part of geopolitical confrontation. When data centers become strategic assets, cyberattacks against these facilities gain broader destructive power.

IoT and Edge: The Ecosystem Expansion Behind 21 Billion Devices

By the end of 2025, the number of actively connected IoT devices reached 21.1 billion, growing about 14% annually. This figure does not include ordinary smartphones, computers, and tablets—it consists mainly of industrial equipment, gateways, smart home appliances, and sensors. IoT Analytics expects this number to reach 39 billion by 2030.The growth of the Internet of Things is not merely an isolated increase in devices, but a synergy with AI and cloud computing. Devices generate data, which is transmitted to the cloud or edge for AI analysis, and the results are then converted into automated actions. This loop is reshaping manufacturing, logistics, energy, and agriculture. At the same time, however, it also means that the deeper the integration among technologies, the more pronounced systemic vulnerabilities become—a single network outage can simultaneously affect production, transportation, and public services.

Employment and Skills: The False Prosperity and Real Gaps in the IT Labor Market

The U.S. Bureau of Labor Statistics (BLS) projects that computer and information technology occupations will add approximately 317,700 jobs per year from 2024 to 2034. This is lower than the previously projected more than 377,000 jobs per year, but the absolute number remains substantial.

It is worth considering whether AI's automation capabilities are replacing some traditional IT roles. The emergence of new jobs may not keep pace with the disappearance of old ones. Data center operations, AI security, model evaluation, data labeling, and other factors are redefining the skill structure of IT workers.

As for search popularity, a 2024 keyword analysis found that the average monthly search volume for artificial intelligence exceeded 668,000, while search volume for generative AI surged 2,806% between 2022 and 2024. Behind this surge in search interest lies both an awakening of public awareness and underlying concerns about an AI bubble. Search interest does not equal actual adoption, but it is an important signal of change at the level of perception.

Beyond Categorization: The Deeper Logic of Technological Evolution

The 36 technology types certainly help us capture the technology landscape of 2026, but what truly drives change is not these categories themselves—it is a few core logics:

1. Computing power becomes a new scarce resource. Data center spending is growing at 55.8%, indicating that technological competition has moved forward into the realm of physical infrastructure. 2. AI shifts from an "application" to an "operating system." AI spending of $2.52 trillion far exceeds traditional software spending, meaning AI is becoming the foundational environment in which other technologies operate. 3. Everything is converging. Whether in autonomous driving, smart cities, or digital twins, a single technology category is increasingly unable to independently define a product or service. 4. Control is both dispersed and concentrated. Cloud computing grants small and medium-sized enterprises access to computing power at scale, but it also further solidifies the dominance of large cloud providers.

Conclusion: The Costs and Benefits of Technological Evolution

The technology landscape of 2026 resembles the beginning of every major transformation in human technological history: surging investment, rapid proliferation of concepts, classification systems lagging behind reality, and social discussions about technology filled with both hope and anxiety.Technology itself is neither good nor evil; the benefits and costs it brings depend on who controls it, who benefits from it, and who bears the risks when it fails. As global IT spending exceeds $6.3 trillion, and as AI becomes infrastructure, we need not only an awareness of technology types, but also a long-term observation of the power structures behind technology.

Classification is only a starting point; understanding the driving forces behind change is the proper stance for judging the future.