跟踪亚太地区人工智能风险投资活动：第二部分

INDUSTRY RESEARCH Institutional Research Group Tracking AI VentureActivity in APAC: Part II Melanie Tng APAC Private Capitalmelanie.tng@pitchbook.com pbinstitutionalresearch@pitchbook.com Where capital is concentrating across the AI value chain Published on February 6, 2026 PitchBook is a Morningstar company providing the most comprehensive, mostaccurate, and hard-to-find data for professionals doing business in the private markets. Contents Key takeaways Introduction Key takeaways The enabling stack: APAC’s AI backbone Applied industry verticals: Where AIis commercialized •AI investment in APAC is increasingly organized along the value chain ratherthan dispersed across themes. Capital continues to concentrate in enablinginfrastructure and in applied use cases with clear paths to deployment, Emerging and downstream themes: Where Conclusion •The enabling stack remains the largest recipient of AI venture capital in the region,but funding dynamics have shifted. Larger median deal sizes and a growingshare of later-stage rounds point to a more selective environment, where capital •Commercialization within applied industry verticals is uneven and increasinglyshaped by enterprise demand. Sectors such as industrials, healthcare, and financialservices are advancing at different speeds depending on regulatory readiness and •In contrast, emerging and downstream AI themes remain largely exploratory.Consumer and climate-related AI activity is concentrated at the early stage, withlimited progression into later rounds, underscoring ongoing uncertainty around Introduction AI & machine learning (AI & ML) remain the defining theme of venture capital in theAsia-Pacific (APAC) region. As covered in ourQ4 2025 Analyst Note: Tracking AIVenture Activity in APAC, the sector has proven unusually resilient amid the broaderventure slowdown. Even as overall deal activity moderated, AI’s share of total VC deal The key question, then, is where this capital is flowing. While US dealmaking hasbeen dominated by large funding rounds for a small number of foundation-modeldevelopers, AI investment in APAC is far more dispersed, spanning infrastructure, To address this, we take a value-chain approach where we group AI deal activi tybased on where companies sit in the AI value chain and then examine how capital i sdistributed across those layers. This framework, what we call the “AI cap ital stack,” We break the AI capital stack into three parts: •The enabling stack:The software and hardware infrastructure that powers AImodel development and deployment, including software as a service (Sa aS), data •Applied industry verticals:The core commercialization layer where AI is embedded •Emerging and downstream themes:Consumer- and policy-facing applications,such as media, marketing, and climate-related AI, where adoption rem ains earlier Within each layer, we focus on verticals that are the most material to aggreg ate dealactivity and capital deployment. Using this framework, we compare dea l activity, dealvalue, stage mix, investor composition, and geographic concentration across each The enabling stack: APAC’s AI backbone The enabling stack continues to anchor APAC’s AI venture ecosystem, encompassingthe software and hardware infrastructure required for model development,deployment, and enterprise integration. In 2025, this layer accounted for more than Although activity peaked alongside the broader venture cycle in 2021 and declinedin the subsequent correction, deal value rebounded in 2025 even as deal countsremained below prior highs. This points to a targeted recovery, driven less by renewedrisk appetite and more by investors selectively funding infrastructure assets perceived The composition of these deals by stage further supports this trend. Later-stageVC rounds now account for a growing share of activity, while Series A and B fundinghas declined. Capital is concentrating around a narrower set of scaled platforms, Core AI software & data infrastructure Within the enabling stack, core AI software and data infrastructure, including SaaS,Big Data, cloudtech, development operations, and cybersecurity, remain the dominantcategories. In 2025 alone, this segment recorded approximately 680 deals and $5.2billion in deal value, making it the largest contributor by deal count and a major driver By country, India and Japan lead by deal count, reflecting the depth of their enterprisesoftware and data-infrastructure ecosystems, where AI is increasingly embeddedinto productivity, analytics, and security platforms. In India, this is underpinned by thecountry’s mature SaaS export model: a wide base of AI-enabled enterprise platformsfocused on analytics, workflow automation, and security continues to attract steadyearly- and later-stage funding from both domestic and cross-border investors. Recent Meanwhile, Japan’s high deal count reflects a different dynamic. Activity is largelydriven by corporate-led digitization, where c