Ad Spending, Chips, and the Rise of AI in Recruiting: What Tencent’s Results Tell Us

In a recent conversation on Bloomberg Technology, WPIC CEO Jacob Cooke joined hosts Caroline Hyde and Ed Ludlow to unpack Tencent’s latest earnings and broader trends in Chinese ecommerce, advertising, and AI infrastructure. That interview—published by Bloomberg Technology—offered a grounded, on-the-ground perspective about why advertising revenues are holding up, how Chinese tech companies are navigating chip constraints, and what this all means for global business relationships. It also raises an interesting, if less direct, question about talent: the growing role of AI in recruiting as companies scale and internationalize their digital operations.

Outline

• Introduction and context
• Why Tencent’s ad spending matters
• Chinese ecommerce and the international footprint
• Chips, generative AI models, and infrastructure realities
• Geopolitics versus on-the-ground business
• Talent implications and AI in recruiting
• Conclusion — what to watch next

Introduction: Why Tencent’s numbers deserve attention

Tencent’s most recent earnings grabbed attention not because of a single blockbuster number but because of what the results reveal about demand dynamics across China and Southeast Asia. Jacob Cooke pointed out that advertising revenue was up about five percent in the quarter—an indicator that stimulus measures and consumer reopening are beginning to translate into ad dollars. In other words, the macro talk about China’s slow recovery is meeting the micro reality of people buying online, advertisers spending, and platforms like Tencent and Alibaba getting a piece of that economic activity.

As companies rethink hiring and talent strategies in this environment, the role of AI in recruiting will only grow. The phrase AI in recruiting appears increasingly in strategy meetings because employers need faster, data-driven ways to find and screen candidates across borders and tech stacks.

Why Tencent’s ad spending matters

Tencent isn’t just a gaming company; it’s a digital ecosystem that earns materially from advertising tied to ecommerce activity. Jacob Cooke highlighted that Tencent has become a major recipient of ad dollars as ecommerce booms in China and Southeast Asia. Investments in companies like Shopee have helped Tencent gain exposure to regional e-commerce growth, but the company’s strength extends beyond equity stakes—it’s capturing advertising flows from a revived consumer market.

Two themes emerge from this dynamic. First, advertising receipts are a timely barometer of consumer activity: when people buy more, merchants bid harder for attention, and ad platforms win. Second, ad revenue can be surprisingly resilient even amid geopolitical uncertainty, provided the spending originates domestically and reflects genuine consumer demand.

Chinese e-commerce and international footholds

When we talk about Chinese tech going global, it’s not only about sending hardware across borders; it’s also the movement of software, platforms, and advertising clout. Cooke noted that while Alibaba is the obvious heavyweight in B2B software ecosystems, Tencent’s investments and ad moat make it a strong player in the regional digital economy. That’s especially relevant in Southeast Asia, where platforms like Shopee have captured massive market share and where advertisers are following shoppers.

This has implications for businesses and HR departments operating internationally. Platforms with regional footprints need talent that understands cross-border digital marketing, localization, and regulatory nuance. That creates demand for recruiters who can surface multilingual, culturally fluent candidates—hence the need for smarter screening tools and more reliance on AI in recruiting to scale hiring quickly and accurately.

Chips, generative AI models, and the infrastructure story

One of the most discussed topics in the interview was access to GPUs and other chip infrastructure—essential for training and running large language models (LLMs) and generative AI systems. Tencent publicly downplayed any immediate constraints, saying it has sufficient chips for inference workloads. However, the guests and hosts acknowledged the opacity around vendor-specific access, notably to NVIDIA hardware and software.

"If Tencent comes and says that they have all the chips they need, there's no reason not to believe that," Jacob Cooke said, while also noting it’s hard to see all the details from the outside.

Despite export controls and geopolitically driven restrictions, Chinese firms like Alibaba and others have continued to develop competitive models. The rollout of models from Alibaba and newer entrants such as DeepSeek (as mentioned in the discussion) shows that innovation can continue, even if the hardware supply path is constrained or opaque. Companies are finding workarounds, optimizing inference efficiency, or relying on domestically produced chips.

This technical evolution matters for recruiting too. Recruiting teams increasingly need to identify candidates with expertise in model optimization, inference engineering, and hybrid cloud deployments. AI in recruiting becomes a multiplier here—helping hiring teams quickly find specialized engineers who can wring more performance from limited chip budgets.

Geopolitics vs. on-the-ground reality

The interview emphasized a split between high-level diplomatic tensions and local business realities. While media headlines highlight strained relations and policy friction, Jacob Cooke pointed out that, on the ground, people-to-people connections and business relationships remain strong. Suppliers, advertisers, and partners that have cultivated relationships over decades often continue to transact.

Cooke made a helpful observation about stimulus timing: China’s significant stimulus shifted the momentum of consumer spending, and the trickle-down into advertising revenues is now apparent in recent quarters. This helps explain why Tencent and other advertising platforms are seeing healthier ad spends even amid broader macro headlines.

There was also discussion about different policy levers. For example, China has used mechanisms like export tax credits in the past to support certain exports—potentially the mirror image of tariffs or controls applied elsewhere. The net effect is that market access, pricing, and availability can vary across regions but don’t always translate into immediate, uniform headwinds for companies with strong domestic or regional positions.

Talent implications: why AI in recruiting becomes essential

As Chinese tech firms scale their software, advertising, and AI capabilities, demand for specialized talent surges. Whether it’s building recommendation engines, optimizing ad auctions, or engineering efficient inference pipelines, the skill sets needed are niche and often scarce. That’s where AI in recruiting can be transformational.

Here are the key talent pressures and how AI in recruiting helps address them:

• Speed and scale: Platforms racing to deploy new AI features need engineers fast. AI in recruiting automates candidate sourcing and preliminary screening, cutting time-to-hire.
• Specialized skill identification: Identifying expertise in model compression, quantization, or distributed training is time-consuming. AI-inferred skill maps can prioritize candidates who have relevant hands-on experience.
• Cross-border hiring: Companies hiring across China, Southeast Asia, and beyond must evaluate language and cultural fit quickly. AI in recruiting helps standardize assessments and surface candidates with demonstrable regional experience.
• Bias reduction: When properly designed, AI in recruiting can help remove subjective bias from early-stage screening—though it must be monitored closely to avoid encoding undesirable biases.
• Retention and internal mobility: AI tools can also identify internal candidates for new roles, improving retention by matching current employees to evolving opportunities.

These pressures are not hypothetical. As Tencent and Alibaba push new AI-enabled products and advertisers demand more measurement and targeting sophistication, hiring pipelines must be faster and more precise. Using AI in recruiting can help organizations keep pace without dramatically increasing headcount in HR operations.

Caveats and governance — using AI in recruiting responsibly

It’s important to acknowledge that AI in recruiting is not a silver bullet. The technology can amplify both useful signals and systemic biases. Good governance, explainability, and regular audits are necessary to ensure that AI-driven hiring tools are fair and compliant with local labor laws and privacy standards.

Moreover, geopolitical differences in data protection and employment law complicate a one-size-fits-all approach. Recruiting systems that work in one jurisdiction may need adjustments elsewhere—another reason to build local expertise into hiring strategies and to combine automated screening with human judgment.

What to watch next

Several indicators will be instructive in the coming quarters:

1. Advertising revenue trends across Tencent and Alibaba—continued strength will indicate consumer spending and ecommerce momentum.
2. Announcements about chip supply and partnerships—look for disclosures about proprietary chips, domestic supply chains, or agreements with global vendors.
3. New model releases and benchmark performance—whether Alibaba, Tencent, or other Chinese firms keep closing the gap with global LLMs despite export constraints.
4. Hiring patterns in AI and ML roles—whether companies start to rely more on remote talent, internal training, or automated sourcing through AI in recruiting.

Each of these will shape how companies allocate capital between R&D, infrastructure, and people. For recruiters and HR leaders, the immediate takeaway is clear: the pace of product development and market expansion demands faster, smarter hiring practices. AI in recruiting is one of the tools that can deliver that speed without sacrificing quality.

Conclusion

The Bloomberg Technology discussion with WPIC’s Jacob Cooke illuminated a couple of important truths: China’s advertising market is recovering and feeding revenue into dominant platforms; Chinese tech companies continue to develop advanced AI models even amid chip supply uncertainty; and on-the-ground business relationships remain resilient despite headline-level geopolitical noise. For organizations focused on growth, these trends underscore a parallel imperative—building hiring systems that can keep up.

That convergence—accelerated digital monetization and scarce technical talent—means AI in recruiting is no longer optional for companies that want to compete at scale. Used thoughtfully, it can help identify the engineers and product specialists who will turn ad spend and model research into customer-facing value—without bogging down HR in manual sifting. As the market evolves, the firms that align product strategy, infrastructure access, and talent acquisition will be best positioned to take advantage of the recovery and the next wave of AI-driven innovation.

Source: This analysis was informed by a conversation on Bloomberg Technology featuring Jacob Cooke of WPIC, Caroline Hyde, and Ed Ludlow.