Global Asset Giants Mid-Year Outlook: AI Pricing Logic Reshapes, A-Share Tech Faces Value Revaluation Window

Keywords: Artificial Intelligence, Global Asset Managers, China Stock Market, A-Share AI, Valuation Revaluation, Commercialization, Emerging Markets, Robots

Recently, BlackRock, Fidelity International, and Invesco, among other global asset management giants, held their 2026 mid-year investment outlook conferences, setting out their judgments on global asset allocation for the second half of the year. Unlike before, artificial intelligence is no longer just a hot theme within the tech sector but has been elevated by many institutions to a "fundamental variable" affecting global economic growth, capital expenditure, and industrial structure. At the same time, "China" became a high-frequency keyword at the conferences, with A-share AI-related sectors in particular, combining valuation advantages and industrial implementation potential, widely seen as an important allocation direction in the global tech competition.

AI Is No Longer Just Thematic Investing, But a New Engine for Economic Operation

In the past tech stock rally, market focus was mainly on traditional logic such as earnings delivery, valuation expansion, and capital inflows. However, in the current wave of AI, the role of AI has clearly exceeded a single industry category, gradually evolving into a core force driving productivity improvement, corporate organizational restructuring, and even changes in economic growth patterns.

BlackRock believes that AI has evolved from a simple tech track into a structural force affecting the underlying logic of the global economy, and short-term interest rate fluctuations are not enough to change its long-term trend. Its core judgment is that AI-related companies are achieving revenue growth at an unprecedented pace, and AI tool application scenarios have penetrated most existing GDP components. The breadth and depth of this technology diffusion are rare in history.

This judgment is significant. It means that the market's valuation of AI should not be confined to the level of "concept hype" or "hardware cycles," but should consider its long-term reshaping of corporate profit margins, industry competition landscape, and return on capital. In other words, AI is no longer just a hot sector in capital markets but is gradually becoming an important factor affecting global asset pricing systems.

Different from the Internet Bubble: Current AI Rally Has Profit Support

As the AI frenzy continues to heat up, market concerns about a bubble have also risen. Some investors have begun to compare the current market with the 2000 internet bubble, worrying that "high growth expectations" may ultimately not materialize. However, from the perspective of multiple international asset management institutions, the current AI sector fundamentally differs from the internet wave back then.

Fidelity International believes that the first phase of AI development is primarily driven by infrastructure investment, covering semiconductors, computing power, data centers, etc. Supported by sustained capital expenditure from hyperscale cloud vendors and large enterprises, this phase remains an important source of earnings growth for the global tech sector. That is, the market is not simply driven by sentiment but has a relatively clear chain of orders, revenue, and profits as support.

Invesco further points out that the current AI sector cannot simply apply the historical template of the internet bubble. Internet companies around 2000 had valuations extremely dependent on highly elastic metrics like price-to-sales ratios, and many lacked actual profitability. In contrast, many leading AI companies today already have strong cash flows and profit growth, with valuations built more on the matching of P/E or P/S ratios with earnings delivery. In other words, although the current AI rally is considerable, it is not a complete "castle in the sky" detached from fundamentals.

However, this does not mean the AI sector is risk-free. What is truly worth watching is not the overall AI trend but the excessive pre-pricing of some sub-sectors, slower-than-expected commercialization progress, and earnings fluctuations after capital expenditure growth marginally slows. Therefore, AI investing needs to distinguish among "infrastructure dividends," "application layer implementation," and "concept narratives" to avoid across-the-board chasing of gains.

Why Chinese AI Assets Become a Focus for Global Capital

In the global asset managers' outlooks, "China" is repeatedly mentioned because AI is becoming an important catalyst for the revaluation of Chinese tech assets, and A-share related sectors still have significant valuation discounts and growth flexibility compared to global peers.

BlackRock explicitly stated that it holds a positive view on Chinese stocks, especially A-share AI-related sectors, because their valuations are more attractive compared to global peers. For global capital, this "low valuation + high growth expectations" combination is highly attractive for allocation. Especially against the backdrop of generally rising global tech stocks and some high-quality targets nearing historical valuation highs, the relative cost-effectiveness of Chinese AI assets is further highlighted.

More importantly, China's AI industry is not just a "follower" but has formed its own advantages in multiple links. Fidelity International noted that China has established a strong position in areas such as hardware, motion control, and manufacturing capabilities, while investment in robotics software, data collection, and large model base capabilities continues to accelerate. With the continuous expansion of scenarios such as robotics, smart manufacturing, and industrial automation, China's advantages in AI commercialization and industrial implementation are gradually emerging.

From a global investment perspective, the real competition in AI lies not only in algorithms but also in who can embed technology into real industries faster and generate sustainable revenue. China's vast manufacturing base, rich application scenarios, complete supply chain system, and relatively complete engineering capabilities provide unique soil for AI to move from "lab technology" to "scaled commercial application." This is also an important reason why international institutions continue to focus on Chinese AI assets.

Robots and Large Models: Two Key Themes in A-Share AI

If computing power, chips, and data centers represent the first half of AI, then robots, industrial intelligence, and industry-specific large models are more like the core tracks of the second half. Multiple institutions mentioned in their outlooks that China has strong competitiveness in the robotics industry chain, and this field is expected to become an important breakthrough for AI commercialization.

Dale Nichols, a fund manager at Fidelity International, said that China has established solid advantages in hardware, motion control, and manufacturing capabilities, while investment in robotics software, data collection, and brain-base models is accelerating. Combined with recent research findings, he believes robotics is becoming an increasingly important innovation area, and China has great potential to lead in this field.

This judgment is not baseless. Competition in the robotics industry is no longer just about mechanical components or execution precision but integrates AI algorithms, perception capabilities, decision systems, and scenario data. Chinese companies' strengths in supply chain collaboration, engineering transformation, and scale manufacturing make it easier for them to form a closed loop from technology to product, and from product to scenario in this industrial upgrade.

At the same time, Zhao Yaoting noted that there is still room for further valuation upside for Chinese AI-related companies. From a global perspective, China's AI models, systems, and language models are more user-friendly for local users, and this "localization advantage" is expected to improve commercialization efficiency and lead to higher conversion rates in finance, manufacturing, retail, education, and other fields. For investors, this means Chinese AI assets not only have theme elasticity but also real earnings extensibility.

Conclusion: The Key in the AI Era Is Not Whether to Participate, but How to Choose the Right Position

From BlackRock and Fidelity International to Invesco's mid-year outlooks, it is clear that global asset managers are converging on their judgment of AI: AI is not a short-term trading hotspot but a core variable affecting global capital markets and industrial structure in the long term. For investors, the real question is no longer "Will AI continue to rise?" but "Who can occupy a higher-quality position in the AI value chain?"

In this context, the value of Chinese AI assets is being rediscovered. Whether from the perspective of relatively low valuations or the broad space for industrial implementation, the A-share AI sector has become a direction that cannot be ignored in global capital allocation. Especially in sub-sectors such as robotics, computing infrastructure, large model applications, and industrial intelligence, the Chinese market is expected to form unique advantages.

It can be foreseen that as AI shifts from capital-expenditure-driven to application-profit-driven, global tech investment logic will further differentiate. Companies that possess both technological capabilities and real commercialization scenarios will stand out in the next round of competition. For the Chinese market, this is both a challenge and a rare revaluation opportunity.