The mixed results underscore a broader transition: Tencent’s legacy businesses still generate substantial profits, but growth expectations increasingly hinge on AI.
The main reason for the revenue shortfall was slower growth in gaming sales, a segment that remains one of Tencent’s largest businesses.
Domestic gaming revenue grew about 6% year over year, but that pace was much slower than the growth seen a year earlier. Analysts and company commentary pointed partly to timing effects from the Chinese Spring Festival holiday, which fell later in the calendar and shifted revenue recognition for some game activity.
While gaming remained a major contributor, other divisions helped offset the slowdown:
Advertising growth was particularly strong as Tencent used AI-driven recommendation systems to improve targeting on platforms such as WeChat.
At Tencent’s annual general meeting, CEO and founder Pony Ma Huateng offered an unusually frank assessment of the company’s position in the AI race.
He told shareholders that Tencent had initially believed it was already well positioned, only to realize its progress was slower than expected. Using a metaphor, Ma said the company once thought it had "boarded the ship" but later discovered it was leaking. Now, he said, Tencent feels it has regained its footing—but "we cannot sit down yet," suggesting the recovery is still in its early stages.
Ma described the company as seeing the “beginning of a turnaround” in AI but acknowledged there is still work to do to catch up with competitors.
Tencent’s approach to AI focuses less on a single breakthrough product and more on integrating models across its massive ecosystem.
According to the company’s earnings materials, Tencent has made “significant initial progress” in its Hunyuan large language models and in new productivity‑focused AI agents.
The company’s strategy includes two major pillars:
Tencent is embedding AI capabilities into its core platforms and revenue engines, including:
These improvements aim to increase engagement, ad efficiency, and platform monetization.
Tencent is also developing new products around Hunyuan AI models and productivity agents, designed to assist with tasks such as writing, coding, and workflow automation.
These tools are expected to integrate tightly with Tencent’s ecosystem—especially WeChat, enterprise tools, and cloud services—which could provide a large distribution advantage if adoption grows.
The company’s pivot toward AI is expensive. Large model training, computing infrastructure, and product development have increased costs, creating pressure on margins in the short term.
Nevertheless, Tencent—along with Chinese tech peers like Alibaba—has signaled it will continue aggressive investment in AI infrastructure and products, viewing the technology as the next major growth platform for the internet industry.
Tencent’s Q1 results highlight a company balancing two realities:
For now, the company is still delivering steady profits even as revenue growth slows. But as Pony Ma’s remarks suggest, the real test ahead is whether Tencent’s AI push can evolve from experimentation into a meaningful new business line.