July 30, 2026, Beijing — As the hype around generative AI fades, the investment logic for artificial intelligence is undergoing a profound paradigm shift. No longer simply chasing concepts and expectations, the focus is turning to rigorous validation of commercial value after technological breakthroughs. According to the latest reports from multiple investment banks and research institutions, the core keywords for AI investment in the second half of 2026 are "deployment" and "returns."
Large Model Cost Reduction: Commercial Inflection Point Has Arrived
In mid-July, OpenAI announced a 30% price cut for the GPT-5 series API, followed by Google, Anthropic, and others. The inference cost of large models has dropped over 60% in a year, directly driving large-scale deployment of AI applications. According to the latest IDC data, the global AI software market reached $24 billion in Q2 2026, up 55% year-over-year, with enterprise AI application revenue exceeding 50% for the first time. "When model call costs drop from a few cents per 1,000 tokens to sub-millicent levels, many scenarios previously unviable due to cost become feasible," said Li Hua, TMT Chief Analyst at CITIC Securities. "We observe AI penetration accelerating in verticals such as education, customer service, and data analytics."
For investors, this means the investment target is shifting from initial infrastructure like computing chips and model training to downstream AI application layers. Companies that can leverage low-cost models to build differentiated products and quickly acquire customers are likely to become the focus of the next growth wave.
Industry Deployment Cases Surge: Finance and Healthcare Lead
On July 28, Industrial and Commercial Bank of China (ICBC) announced the launch of version 3.0 of its "ICBC Smart Brain" based on the Ascend AI platform, deployed in over 30 business scenarios including intelligent risk control, credit approval, and wealth management, saving more than 1.5 billion yuan in labor costs. In healthcare, the U.S. FDA approved the 100th AI-based medical device in July, with imaging-assisted diagnostics accounting for the largest share. A digital pathology AI model developed by NVIDIA in collaboration with Mayo Clinic improved cancer diagnostic accuracy to 96% while reducing slide reading time by 80%.
"AI is no longer a lab toy but a real productivity tool," noted Wang Ming, researcher at Yueya Finance. "Investors now focus on ROI indicators, and a large number of real cases show that AI deployment can bring enterprises an average efficiency improvement of 20%-40%, with a payback period of 12-18 months."
Policy Acceleration: Global AI Competition Enters New Phase
In July 2026, China's Ministry of Industry and Information Technology (MIIT) and other departments jointly issued the "Three-Year Action Plan for AI Empowering New Industrialization," proposing to build 50 national-level AI industry innovation platforms by 2028 and push AI penetration in the industrial sector to 70%. The European Parliament also passed amendments to the AI Act implementation rules on July 25, strengthening regulation while providing regulatory sandboxes and other conveniences for innovative enterprises. The White House announced an additional $30 billion in AI R&D funding, focusing on future AI safety and reliability research.
Sustained policy efforts provide long-term certainty for AI investment. Zhang Lei, strategy analyst at Huatai Securities, believes: "Major economies are competing for AI influence, ensuring sustained policy and financial support for related industrial chains. Investors should focus on sub-sectors that align with national strategic directions and possess core technologies."
Capital Trends: From 'Broadcasting' to 'Precision'
According to Crunchbase, global AI financing totaled $89 billion in the first half of 2026, up 35% year-over-year, but the number of projects decreased by 20%, with the median single-round financing rising to $50 million. This indicates capital is concentrating on top-tier projects, with more cautious decision-making. Notably, financing activity in cross-disciplinary fields such as AI robotics, autonomous driving, and quantum AI has increased significantly. For example, Silicon Valley startup Figure AI completed a $1.5 billion Series D round in July, reaching a valuation of over $15 billion, with its general-purpose humanoid robot already deployed at a BMW factory.
"In the past, simply adding an AI label could secure funding. Now investors ask: What is your moat? What is your customer retention rate? When can you become profitable?" said Fei-Fei Li, renowned angel investor and former Google AI researcher, at a forum. This change precisely indicates the AI industry is maturing, which is positive for long-term fundamental-focused investors.
Investment Strategy: Focus on Four Major Tracks
Synthesizing views from multiple institutions, AI investment in the second half of 2026 can focus on the following directions:
- AI Application Software: Including enterprise SaaS, industry-specific AI tools, and AI-native applications, benefiting from model cost decline and user penetration increase.
- Vertical Industry Solutions: Such as AI+Healthcare (imaging diagnosis, drug discovery), AI+Finance (risk control, robo-advisory), AI+Manufacturing (quality inspection, scheduling), with high barriers and high added value.
- Data and Security: Infrastructure like data annotation, privacy computing, and AI security testing, benefiting long-term from AI compliance needs.
- Smart Hardware: AI PCs, AI phones, AI robots, etc. The rise of on-device AI will drive a new replacement cycle.
"AI investment has moved from 'story-playing' to 'performance-watching,'" said Chen Hao, Chief Strategy Analyst at Yueya Finance. "AI companies with real customers, sustainable revenue, and positive business models will outperform the market in the next 2-3 years. Investors should abandon short-term speculation and allocate to high-quality targets from an industry perspective."
As technology matures, costs continue to fall, and applications accelerate, artificial intelligence is evolving from a supporting tool into a core force reshaping industry landscapes. For investors aiming to capture the next wave of tech dividends, the second half of 2026 may well be a window for building positions at lower levels. But remember, the core of AI investing is not chasing hot topics but understanding how technology creates value and which companies can deliver on that value.
