The global IT market is currently experiencing a major transformation, driven by rapid advancements in Artificial Intelligence and evolving technological capabilities. In a September 2026 outlook, McKinsey identified 14 key global IT trends that are set to redefine business operations and technological deployment worldwide.

Key Identified Trends:

• Agentic Software Development: This trend involves the deployment of Large Language Model (LLM)-based systems capable of autonomously performing complex engineering tasks, including planning, coding, testing, and debugging. This shifts the role of developers toward quality control and workflow coordination.
• AI in Science: Neural networks are accelerating research in fields such as materials science, chemistry, physics, and climatology. These models are being used to formulate hypotheses, simulate complex scenarios, and automate routine experimental tasks.
• AI Infrastructure: Continued development is anticipated for the underlying infrastructure supporting LLMs, specifically focusing on large-scale data centers and advanced cloud platforms.
• Agentic AI: Systems are being developed to plan and execute multi-step workflows with minimal direct human intervention. These agents analyze context, interact with enterprise platforms, and autonomously adjust actions based on changing conditions.
• Specialized Semiconductor Solutions: The focus is on co-designing chips tailored for specific computing needs within the AI space, optimizing for performance and energy efficiency.
• Cybersecurity and Trusted Systems: Deployment of solutions built on zero-trust architecture, blockchain registries, tokenization, and quantum-resistant cryptography to secure distributed computing environments.
• Advanced Communication Technologies: Growth in technologies such as 5G and future 6G networks, alongside energy-efficient Internet of Things (IoT) networks and low Earth orbit satellites, is expanding connectivity.
• Immersive Reality Technologies: The focus is shifting toward context-aware wearable devices utilizing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), integrating digital experiences with physical environments.
• Quantum Technologies: Progress in quantum computing is noted for solving specialized computational problems, alongside the development of quantum encryption to address future security challenges.
• The Future of Robotics: There is a projected shift toward physical AI, where robots powered by neural networks and advanced control systems navigate complex environments and operate alongside humans.
• The Future of Mobility: Transformation in transportation is being driven by electric and autonomous vehicles, software-defined platforms, drones, and air taxis.
• Future of Space Technology: Significant development is occurring in launch systems for orbital cargo delivery, satellite servicing, and on-orbit computing services.
• Future of Life Sciences and Bioengineering: The convergence of AI with biology and chemistry is accelerating the design, testing, and scaling of new biological products.

International Context and Significance:

These trends underscore how Artificial Intelligence is not merely an incremental technological upgrade but a fundamental restructuring force across global IT. For the global economy, the efficiency gains promised by agentic software and AI in science are expected to impact productivity across manufacturing, finance, and research.

In terms of international business, the shift toward specialized semiconductor solutions and advanced communication technologies will influence global supply chains and trade in high-tech components. The emphasis on quantum computing and advanced cybersecurity reflects a growing international focus on securing digital infrastructure against evolving threats.

Verified Analysis:

Experts suggest that the adoption of agentic AI in software development represents a significant change in the labor market for technology professionals. The immediate implication is a need for workforce retraining focused on AI coordination and system management rather than pure coding.

Economically, the investment pipeline is expected to concentrate heavily on AI infrastructure, cloud platforms, and specialized hardware. This concentration risks exacerbating existing disparities between technologically advanced economies and those lagging in infrastructure investment.

Future Developments (2-5 Years):

Over the next few years, policy implementation will likely focus on regulating the deployment of agentic AI systems and establishing international standards for quantum-resistant cryptography. Business responses will center on integrating AI agent frameworks into core enterprise systems, particularly in supply chain management and digital transformation initiatives. Infrastructure investment will be heavily directed towards building out the necessary data center capacity and specialized semiconductor fabrication capabilities to support these advanced models.

Global competitiveness will be increasingly tied to the speed and efficacy of adopting these AI-driven workflows. Regional cooperation will be crucial for establishing shared standards in areas like digital infrastructure and data governance to mitigate risks associated with rapid technological change. The long-term outlook suggests a deep integration of AI into scientific research and operational planning, fundamentally altering the pace of innovation across all major global industries.