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Technology M&A AI enters its industrial phase AI investment isn’t just fueling innovation; it’s reshaping competitive dynamics and catalyzing a new wave of strategic M&A across the global tech landscape. February 2026 -- 1 of 3 -- AI has transcended years of experimentation to become the defining growth engine of the technology sector. Investment in AI and AI-enabling technologies has scaled rapidly, not only fueling innovation but also reshaping competitive dynamics, driving sector convergence, and launching a new wave of strategic M&A across the global tech landscape. We witnessed similar dynamics during the rise of the internet, cloud build-outs, and other recent tech revolutions—where consolidation and capability-driven M&A differentiated the top performers from everyone else. The lesson from those past advances is clear: Today’s investment and deal strategies will determine who leads in the next decade of AI-enabled growth. Scaling the foundations of AI Our research and experience in the field suggest that AI investment is entering a new phase of maturity. The sharp increase in infrastructure and platform M&A, particularly targeting data center assets, chip design, and model-training capabilities, reflects a strategic repositioning across the tech ecosystem. The following are among the dynamics we’ve observed: — Computing and data consolidation: Companies are acquiring computing capacity and energy-secure infrastructure to mitigate bottlenecks in graphics-processing-unit supply and power availability. — Platform integration: Cloud providers, hyperscalers, and AI start-ups are engaging in selective mergers, joint ventures, and minority investments to enable greater vertical integration among infrastructure, models, and applications. — Cross-sector convergence: Traditional IT service firms are acquiring or partnering with AI-native start-ups to embed generative and predictive capabilities into their core offerings. The most active acquirers are focusing on deals that deliver strategic control of data, access to AI models, and computing efficiency. Their activity echoes that of the internet era of the early 2000s, when companies often used M&A to build full-stack digital ecosystems. Lessons from the past: Creating sustainable advantages As we’ve noted, today’s tech boom is following a pattern we’ve seen before: hyperinvestment followed by consolidation and sustainable scale. There are three relevant history lessons, then, for AI investors and corporate acquirers: — Emphasize infrastructure readiness and efficiency. The internet companies that survived the dot-com collapse had robust infrastructures and scalable economics. Today’s acquirers should seek targets with differentiated computing efficiency, proprietary data pipelines, or model optimization capabilities that can scale sustainably—for instance, energy-efficient data centers and AI-optimized hardware, both of which are attracting premium valuations. — Cultivate agility and market responsiveness. The AI market is evolving faster than traditional deal cycles can accommodate. Open-source models (such as Llama 3, Mistral, and Falcon) and new monetization frameworks are shifting value pools toward flexible, modular architectures. Leaders should cultivate agile M&A strategies, ones that emphasize optionality through minority stakes, ecosystem partnerships, or “acqui-hires.” In this way, they can innovate while still managing valuation risk. 2 Technology M&A -- 2 of 3 -- — Be strategic about value chain investment. Past tech cycles show that the high performers succeeded not by owning every layer of the value chain but by gaining strategic access to those parts of it that shaped performance, cost, and the customer experience. Selective investment in these critical areas rather than in broad ecosystem expansion allowed companies to influence the economics of the entire stack without overextending their capital or increasing the complexity of their operations. Looking ahead: The strategic implications of AI-related M&A Again, based on our research and experience, we believe AI-related M&A will shape global competitiveness in three fundamental ways. First, we expect to see continued convergence of hardware, cloud, and model layers as companies seek end-to-end control of performance, cost, and intellectual property (IP). Semiconductor consolidation and roll ups among computing platforms are likely to remain active through 2026. Second, we expect to see more capability-driven acquisitions in enterprise software and services. IT and professional-service firms are acquiring specialized AI start-ups to accelerate their integration of gen AI into workflows, customer service, and knowledge management. Such transactions tend to be smaller than others but will still be strategically critical. And finally, uncertainty about regulation and geopolitics will continue. Divergent regional frameworks, such as the EU AI Act, US executive actions, and China’s rules on AI model governance, are influencing where and how deals can be executed. Cross-border M&A involving AI will continue to be scrutinized on data security and algorithmic control, pushing firms toward joint ventures and localized build-outs instead of full acquisitions. Investors’ deal rationales are shifting from primarily focusing on synergies to focusing on capability acquisition, infrastructure security, and other secondary objectives. The new playbook for AI M&A must emphasize access to talent, proprietary data, and model IP rather than traditional scale economics. In short, companies’ success with AI and AI-enabling tools will depend on not just building the technology but also buying and integrating it wisely—and M&A will remain a critical accelerator of that integration. The companies that use inorganic growth to strengthen their position in computing, data, and model layers while maintaining flexibility amid regulatory uncertainty will define the next generation of AI leaders. Indeed, they will shape the competitive landscape of tomorrow’s intelligent economy. Read the full report on which this article is based, 2026 M&A trends: Navigating a rapidly rebounding market. Anthony Luu is a partner in McKinsey’s Austin office, Jeremy Schneider is a senior partner in the New York office, and Naveen Sastry is a senior partner in the Bay Area office. Download the full report in which this article appears, 2026 M&A Trends: Navigating a rapidly rebounding market. Scan • Download • Personalize Find more content like this on the McKinsey Insights App Designed by McKinsey Global Publishing Copyright © 2026 McKinsey & Company. All rights reserved. 3 Technology M&A -- 3 of 3 --