The global technology landscape is undergoing significant shifts, propelled by fast-moving innovations in technologies. These are exponentially increasing demand for computing power, capturing the attention of management teams and the public, and accelerating experimentation. These developments are occurring against a backdrop of rising global competition as countries and corporations race to secure leadership in producing and applying these strategic technologies.
New and notable
In addition to the growing reach of AI, another new trend we have chosen to highlight in this year’s report is agentic AI, which has rapidly emerged as a major focus of interest and experimentation in enterprise and consumer technology. Agentic AI combines the flexibility and generality of AI foundation models with the ability to act in the world by creating “virtual coworkers” that can autonomously plan and execute multistep workflows. Although quantitative measures of interest and equity investment levels are as yet relatively low compared with more established trends, agentic AI is among the fastest growing of this year’s trends, signaling its potentially revolutionary possibilities.
AI is also the primary catalyst for another trend we highlight this year: application-specific semiconductors. While Moore’s Law and the semiconductor layer of the technology stack have long been key enablers of other tech trends, innovations in semiconductors have spiked as reflected in quantitative metrics such as number of patents. These innovations have come in response to exponentially higher demands for computing capacity, memory, and networking for AI training and inference, as well as a need to manage cost, heat, and electric power consumption. This has given rise to a slew of new products, new competitors, and new ecosystems.
Technology trends also have a variety of profiles along the dimensions we analyzed. AI is a widely applicable, general-purpose technology with use cases in every industry and business function—and thus lots of innovation and interest—and it is scaling rapidly across the business landscape. Quantum technologies have a different profile. Quantum computing has the potential for transformative impact in certain critical domains, such as cryptography and material science, and the basic technology continues to be developed. Recent announcements, particularly by technology giants, have sparked increased interest, but real-world business impact will require even more technology advancements to make quantum computing practical. Other trends and subtrends vary across the multiple dimensions we analyzed, offering different approaches—from watchful waiting to aggressive deployment—to business leaders depending on their industries and competitive positions.
From the rise of robotics and autonomous systems to the imperative for responsible AI innovations, this year’s technology developments underscore a future where technology is more adaptive, collaborative, and integral to solving global problems. This is illuminated by themes that cut across trends this year:
- The rise of autonomous systems. Autonomous systems, including physical robots and digital agents, are moving from pilot projects to practical applications. These systems aren’t just executing tasks; they’re starting to learn, adapt, and collaborate. Autonomy is moving toward broad deployment, whether through coordinating last-mile logistics, navigating dynamic environments, or acting as virtual coworkers, among other skills.
- New human–machine collaboration models. Human–machine interaction is entering a new phase defined by more natural interfaces, multimodal inputs, and adaptive intelligence. From immersive training environments and haptic robotics to voice-driven copilots and sensor-enabled wearables, technology is becoming more responsive to human intent and behavior. This evolution is shifting the narrative from human replacement to augmentation—enabling more natural, productive collaboration between people and intelligent systems. As machines get better at interpreting context, the boundary between operator and cocreator continues to dissolve.
- Scaling challenges. The surging demand for compute-intensive workloads, especially from gen AI, robotics, and immersive environments, is creating new demands on global infrastructure. Data center power constraints, physical network vulnerabilities, and rising compute demands have exposed cracks in global infrastructure. But the challenge isn’t just technical: Supply chain delays, labor shortages, and regulatory friction around grid access and permitting are slowing deployments. As a result, scaling now means solving not only for technical architecture and efficient design but also for the messy, real-world challenges in talent, policy, and execution.
- Regional and national competition. Global competition over critical technologies has intensified. Countries and corporations have doubled down on sovereign infrastructure, localized chip fabrication, and funding technology initiatives such as quantum labs. This push for self-sufficiency isn’t just about security; it’s about reducing exposure to geopolitical risk and owning the next wave of value creation. The result is a new era of tech-driven competition where nations have a stake in critical industries.
- Scale and specialization are growing simultaneously. Growth on these vectors is enabled by innovation in cloud services and advanced connectivity. On one hand, we see rapid growth in general-purpose model training infrastructure in vast, power-hungry data centers, while on the other, we observe accelerating innovation “at the edge,” with lower-power technology embedded in phones, cars, home controls, and industrial devices. This is creating ecosystems that deliver massive large language models with staggering parameter counts, as well as a growing range of domain-specific AI tools that can run almost anywhere. Leaders will balance centralized scale with localized control: Think modular microgrids for clean energy or bespoke robotics for niche manufacturing.
- Responsible innovation imperatives. As technologies become more powerful and more personal, trust is increasingly the gatekeeper to adoption. Companies face growing pressure to demonstrate transparency, fairness, and accountability, whether in AI models, gene editing pipelines, or immersive platforms. Ethics are no longer just the right thing to do but rather strategic levers in deployment that can accelerate—or stall—scaling, investment, and long-term impact.
Read the full report originally published by McKinsey here.
