The phased pressure on short-term profits did not hinder long-term logic. Jingtai Holdings (02228)'s endogenous business growth rate exceeded 65%

Recently, Jingtai Holdings (02228), a leader in AI science and intelligence in Hong Kong stocks, issued a mid-term profit warning for 2026, which predicts that the current period's results will change from profit to loss. Although I&G's disclosure has heated up short-term concerns in the market, Jingtai's underlying logic is still visible after the announcement was dismantled.

Investors can clearly see that Jingtai's profit fluctuation is not due to weak operations in the main business. The core is due to two major objective factors: first, a one-time large licensing transaction for the Dovetree project of 51 million US dollars in the same period last year raised the performance base, and the other is that the company actively increased investment in R&D.

In fact, after excluding the disruption of Dovetree's one-time licensing deal, Jingtai's main business had strong endogenous growth momentum, with a year-on-year increase of more than 65%; among them, the AI for Science sector grew more than 120% year over year.

Furthermore, as the company's global research open platform XtalPi Science is about to be launched and exclusive scientific data assets continue to build core barriers, Jingtai's long-term growth logic has not changed. Its R&D platform capabilities across multiple business segments continue to be verified and valued in the fields of small molecule drugs, peptides, antibodies, small nucleic acids, and new materials.

The short-term accounting base is disrupted, and it is difficult to shake the resilience of the main business infrastructure

On August 5 of last year, Jingtai and DoveTree reached a pipeline cooperation with a total order size of about 5.99 billion US dollars, setting a new record for order size in the field of artificial intelligence drug research and development (AIDD). DoveTree's initial down payment of $51 million was confirmed by Jingtai in mid-2025. This is also one of the core drivers for its revenue surged by more than 200% last year and achieved annual profit for the first time.

The Zhitong Finance App learned that according to the normal pace of cooperation between the two parties, further payments from DoveTree will be confirmed by Jingtai in batches. The second payment, which was received in May of this year and confirmed as the company's mid-term revenue, was 19 million US dollars. It was a mismatch between the timeline for confirming earnings from the cooperation and the timeline of Jingtai's own financial reporting cycle, which directly caused Jingtai's current book revenue to weaken year-on-year.

Simply put, the changes in Jingtai's current financial data actually only disrupted the short-term accounting base and could not truly reflect the company's ability to normalize operations.

After excluding all payments related to Dovetree's one-time license, Jingtai's endogenous revenue has increased by more than 65% year-on-year during the current period. Among them, the AI automated robotics laboratory and intelligent service business grew by more than 120% year-on-year.

Furthermore, during the period, Jingtai not only achieved stable repurchase of traditional small molecule drug discovery research and development services, maintained a steady pace of delivery of cooperative orders from top global pharmaceutical companies, but also continued to implement new projects for biotech and new materials companies at home and abroad.

The obvious acceleration and positive trend of core business indicators not only confirms the accelerated penetration and implementation of the AI for Science industry, but also verifies that Jingtai's main business infrastructure is resilient.

If the high growth of Jingtai's own business proves its hard power, then the rapid progress of AI model technology and the drastic reduction in costs have pressed the acceleration key for the entire industry.

At the technical level, AI's capabilities at the core of drug development have improved significantly. According to industry agency predictions, advanced protein structure prediction models have achieved an accuracy improvement of more than 50% compared to traditional methods, and this technology is moving from the laboratory to the stage where it can be applied in practice.

What is more noteworthy is the cost side. Over the past two years, while the capabilities of mainstream large models have improved markedly, computational costs have continued to decline. This means that AI research and development tools are being popularized at a lower cost to small and medium-sized biotech companies, new materials companies, and even academic institutions. The customer base has expanded from a “few heads” to a “long-tail majority”, and the market ceiling for multiplexing head platforms such as Jingtai has been raised markedly.

For investors, one key sign is that when the cost of using core technology enters a rapid decline channel, the industry penetration rate will often break through the tipping point soon and usher in a period of explosion. Jingtai's current high growth is not only supported by the company's own capabilities, but also the dividends brought about by technological changes in the entire industry as the underlying logic. Its abundant cash reserves and continuous investment in research and development have provided abundant ammunition and momentum for the next growth cycle.

Actively pay strategic costs and accelerate entry into the “technology compounding period”

Although Jingtai has taken the lead in breaking through a closed commercial loop in recent years, what is more profound than short-term profit figures is the core of Jingtai's “technology first” strategy. As a leader in the field of AI for Science, Jingtai chose to increase investment in R&D and transform it into sustainable competitiveness by expanding the multiplier effect of the “AI+ robot” platform.

According to financial reports, Jingtai's R&D expenses increased by about 50% year-on-year in the current period, and related investment focused on the medium- to long-term strategic layout of AI for Science. The company mainly focuses on the three major investment directions of independent laboratories, smart system construction, and promotion of new drug technology platforms and self-research pipelines, and continues to expand the company's innovative technological value.

Judging from the pace of industry evolution, AI for Science is moving from a “single point of tool assistance” to a stage of qualitative transformation where the “smart body drives the whole process in a closed loop”. The leap forward in large model capabilities makes AI no longer limited to a single stage of efficiency optimization, but can go through the entire chain of target discovery, molecular design, synthesis route planning, and experimental verification. Jingtai's forward-looking autonomous laboratory and intelligent system is essentially seizing the “big model+robot”, the high ground of next-generation scientific research infrastructure. As model call costs continue to decline, AI for Science's unit R&D output cost curve is rapidly declining, and commercialization inflection points have been reached.

As technology platforms shift from “proof of concept” to “large-scale revenue contributions,” the market is willing to give significant valuation premiums. Jingtai's current investment in R&D is essentially to reserve ammunition for the upcoming “technical compounding period”. Short-term profits are under pressure in exchange for space to restructure the medium- to long-term valuation system.

In fact, looking at the past financial performance of domestic and foreign peers, intense R&D investment and phased losses are the norm in the AI science and intelligence industry at this stage. As one of the few AI platforms on the AI application circuit that has achieved past profits, Jingtai's advantage is that it has sufficient cash reserves on its books, has a safety cushion for countercyclically increasing the technical layout, and can accelerate entry into the “technical compounding period” by actively paying strategic costs.

From a policy perspective, the current AI enabling scientific research has risen to the national strategic level of China and the US. The industry boom continues to rise sharply, the government and industry invest heavily in both directions, and the long-term development space for the racetrack is extremely uncertain; from an industrial perspective, AI has also broken out of the concept verification stage and has fully entered the large-scale commercial cycle.

Therefore, at a critical point in time for the global AI industry to move from early exploration to a high-speed penetration cycle, Jingtai's upfront investment is expected to seize market share at an accelerated pace. With the launch of the XtalPi Science platform on July 29 this year and subsequent implementation, Jingtai's medium- to long-term performance growth will blossom, and the high growth trend is expected to continue.

epilogue

In a period of deep transformation in the AI industry, Jingtai is accelerating the effective transformation from technology investment to global competitiveness. Looking ahead to the next 6-12 months, the company faces an intensive release window for multiple catalysts: commercialization of the XtalPi Science platform, milestone progress in more pipelines, and disclosure of potentially large cooperative orders may all trigger valuation revaluation. In 2026, when the vertical application of AI is moving from “theme hype” to “performance delivery,” Jingtai is currently at the inflection point of the expected gap between “short-term reporting pressure” and “long-term value transition”, which is a strategic window for laying out a scientific and intelligent circuit. As multiple benefits are realized in batches, the company's business growth is expected to be released at an accelerated pace. As a core configuration target for long-term layout of scientific and intelligent circuits, it has shown considerable upward flexibility to market investors.