Executive Summary
The McKinsey Technology Trends Outlook 2025, published in July 2025, represents a comprehensive assessment of the frontier technologies poised to transform global business over the next decade. The fifth edition of this annual report analyzes 13 trends—a 'baker's dozen'—across six quantitative measures: innovation, interest, investment, and talent. Notably, the report consolidates four previous AI-related trends into an overarching artificial intelligence category, introduces agentic AI and application-specific semiconductors as new trends, and merges energy-related trends into a single broader category.
The central finding is that AI is no longer a standalone trend but rather a foundational amplifier of every other technology domain. From robotics to bioengineering, from quantum computing to energy systems, AI's impact increasingly emerges through combination with other trends. For enterprise leaders and investors, the report provides a critical framework for prioritizing technology investments, understanding adoption maturity, and navigating the rising complexity of the global innovation landscape.
Introduction
For technology executives, venture capitalists, and enterprise strategists, the challenge is not identifying which technologies matter—it is understanding how they interact, mature, and translate into competitive advantage. The McKinsey Technology Trends Outlook 2025 addresses this challenge directly, offering a data-driven analysis of the technology trends that will shape the next decade. Based on patent filings, research publications, news coverage, search behavior, equity investment, and talent demand, the report goes beyond hype to identify where real momentum exists and where enterprise adoption is still nascent.
The report arrives at a moment when global competition for technology leadership is intensifying. Countries and corporations are racing to secure positions in AI, semiconductors, and advanced computing. Meanwhile, the lines between digital and physical, and centralized and decentralized, continue to blur. For decision-makers, understanding the relative maturity and trajectory of these trends is essential for strategic planning, capital allocation, and workforce development.
Technology Context
McKinsey's analysis identifies 13 trends, each assessed in terms of innovation (patents and research) and interest (news and searches). The report also assigns enterprise adoption scores on a 1-to-5 scale, from frontier innovation to fully scaled.
The most significant structural change in this edition is the consolidation of applied AI, generative AI, industrializing machine learning, and next-generation software development into a single, overarching artificial intelligence trend. This reflects a marketplace reality: AI solutions increasingly combine generative and applied capabilities, and the boundaries between them are dissolving. The report emphasizes that AI's true value lies in its role as a cross-cutting amplifier, accelerating progress in robot training, scientific discovery, energy optimization, and more.
Two new trends debut in the 2025 outlook: agentic AI and application-specific semiconductors. Agentic AI refers to systems capable of autonomous goal-directed behavior, representing a shift from AI that generates content to AI that takes action. Application-specific semiconductors, meanwhile, are custom chips designed for particular workloads—most notably AI inference and training—and have become critical infrastructure for the AI economy. The report also combines 'electrification and renewables' and 'climate technologies beyond electrification' into a single trend: future of energy and sustainability technologies. This reflects a recognition that energy transition is not merely a climate imperative but a fundamental enabler of the digital economy, particularly for AI data centers.
Main Analysis
The McKinsey report's methodology is notable for its breadth. By analyzing multiple vectors—patents, research, news, searches, equity investment, and talent demand—it provides a multi-dimensional view of technology maturity. For enterprise leaders, this approach is valuable because it distinguishes between technologies with genuine commercial traction and those still confined to research labs.
The central narrative of the 2025 outlook is the foundational role of AI. The report argues that AI's impact increasingly occurs through combinations with other trends. For example, agentic AI requires advanced semiconductors; AI-powered robotics depends on both AI algorithms and physical hardware; and AI is now essential for optimizing energy systems in data centers. This interconnectedness suggests that enterprises should not evaluate AI in isolation but rather as part of a broader technology portfolio.
Another key insight is the rise of agentic AI. While generative AI captured the spotlight in 2024, agentic AI represents the next evolutionary step: systems that not only generate content but also plan, execute, and adapt to achieve goals. The report's inclusion of this trend as a distinct category indicates that it has crossed a threshold of interest and investment. For enterprises, the implications are profound. Agentic AI could fundamentally reshape business processes, from customer service to supply chain management, and introduce new governance challenges.
Application-specific semiconductors also emerge as a trend of strategic importance. The demand for AI accelerators, and the concentration of their supply, has made chip design and manufacturing a matter of geopolitical significance. The report highlights how investments in this area are driven by AI's insatiable need for compute. This aligns with broader concerns about semiconductor supply chain resilience and the push for domestic manufacturing capacity.
Industry Impact
Enterprise Technology
The consolidation of AI trends underscores a shift in enterprise software. Companies are moving from point solutions for specific tasks to integrated AI platforms that combine analytics, generation, and automation. This is driving consolidation in the software industry and leading to the emergence of new AI-native entrants. For CIOs, the challenge is not just adopting AI but building the data and infrastructure foundation to support it at scale.
Semiconductors and Computing
The report's inclusion of application-specific semiconductors reflects the growing strategic value of compute infrastructure. AI accelerators, such as GPUs and custom ASICs, have become the bottleneck for AI adoption. Enterprises must now factor chip availability and cost into their AI strategies, while semiconductor makers face pressure to innovate across advanced packaging, memory, and power efficiency.
Cloud and Infrastructure
AI-intensive workloads are reshaping cloud architecture and data center design. The demand for high-performance compute has accelerated the edge-to-cloud continuum, with enterprises increasingly distributing AI workloads across centralized and decentralized infrastructure. The report's focus on energy sustainability further emphasizes that data center power consumption is a critical constraint on AI growth.
Investment and Startups
For venture capitalists and institutional investors, the report provides a roadmap for capital deployment. The emergence of agentic AI and application-specific semiconductors as distinct trends signals where new opportunities are forming. At the same time, the consolidation of AI trends suggests that AI investments are maturing, with a shift from experimentation to scaling. Startups must demonstrate not just innovative technology but a clear path to enterprise adoption.
Global Competitiveness
The report places these trends in the context of rising global competition. Countries are competing to attract AI talent, secure semiconductor supply chains, and build digital infrastructure. The report's talent dimension—job postings across English-speaking countries—highlights the acute shortage of AI and deep tech professionals. For policymakers, this implies that technology policy is increasingly integral to national economic strategy.
Strategic Insights
Technology Maturity and Adoption
The report's adoption scores (1-5) reveal a wide spectrum of maturity. While AI is moving rapidly toward widespread deployment, other trends such as quantum technology and space technologies remain in earlier stages. For enterprises, this means adopting a portfolio approach: invest in foundational AI now while monitoring emerging trends for future opportunities.
Commercial Adoption and Enterprise Strategy
The report emphasizes that AI's full potential will require continued innovations in computing intensity, deployment costs, and infrastructure investment. This is a strategic signal for enterprises: AI is not a one-time investment but an ongoing commitment. Enterprises must build the organizational capacity to absorb AI-driven change, including workforce training and process redesign.
Investment Trends
The report's investment data, drawn from PitchBook and corporate M&A, show that capital continues to flow into AI and related technologies. However, investment is becoming more selective. The report's trend consolidation suggests that investors are prioritizing integrated AI platforms over isolated point solutions.
Engineering Challenges
The intersection of AI with energy and semiconductors highlights significant engineering challenges. Power consumption, heat dissipation, and network bandwidth are all becoming constraints on AI deployment. Enterprises and technology providers must work together to develop more efficient compute architectures and energy management systems.
The report also raises questions about technology policy. As agentic AI becomes more capable, governance and safety become paramount. The report's inclusion of digital policy and data governance considerations reflects a broader societal concern. Enterprises must navigate a complex regulatory landscape while maintaining innovation momentum.
Long-Term Technology Leadership
McKinsey's outlook is not merely a snapshot but a guide to long-term technology leadership. The report emphasizes that the most significant opportunities lie at the intersections of trends—AI and robotics, AI and energy, AI and biology. For enterprises, the ability to recognize and exploit these intersections will be a key differentiator in the coming decade.
Future Outlook
The next 5-10 years will see a deepening of the trends identified in the 2025 outlook. Agentic AI is likely to evolve from early pilots to mainstream deployment, creating new opportunities for enterprise automation and raising questions about accountability and control. Application-specific semiconductors will continue to drive the AI infrastructure stack, with fierce innovation in advanced packaging and chiplet architectures.
AI's role as a foundational amplifier will become even more pronounced. In robotics, AI will enable robots that can learn from demonstration and generalize across tasks. In science, AI-driven discovery will accelerate the development of new materials, drugs, and energy solutions. In quantum computing, AI will be used to optimize quantum circuits and decoherence mitigation.
The energy transition will become increasingly intertwined with AI. As data center demand grows, renewable energy and grid management will be critical. The report's combination of energy and sustainability into a single trend acknowledges that zero-carbon energy is a prerequisite for AI's continued expansion.
Enterprises that successfully navigate this landscape will share several attributes: a clear AI strategy, a modular data architecture, a culture of continuous learning, and a willingness to invest in long-term infrastructure. The report's framework helps leaders benchmark their progress against their peers and identify gaps in their technology portfolios.
Conclusion
The McKinsey Technology Trends Outlook 2025 provides an essential roadmap for technology strategy in an era of accelerating innovation and geopolitical competition. By consolidating AI trends, introducing agentic AI and application-specific semiconductors, and highlighting the interdependencies across domains, the report offers a clear-eyed view of where value will be created. For enterprise leaders, investors, and policymakers, the message is clear: technology leadership is no longer optional—it is a strategic imperative. The organizations that thrive will be those that treat technology as a portfolio, invest in foundational AI, and build the capabilities to integrate emerging innovations into real-world operations.
The article is based on the findings of the McKinsey Technology Trends Outlook 2025, published July 22, 2025, and authored by Lareina Yee, Michael Chui, Roger Roberts, and Sven Smit.