Artificial intelligence is increasingly transforming the advertising landscape, offering faster campaign learning, improved targeting, and higher click-through rates. As businesses adapt to these intelligent systems, they experience enhanced performance while simplifying the complexities of campaign execution. With AI technology advancing rapidly, the advertising sector is witnessing a fundamental shift in how campaigns are launched and optimized.
Typically, advertisers start their campaigns with clear objectives and compelling products, but initial performance can be erratic. Advertisers often find themselves making adjustments, switching creatives, and waiting for the system to learn. This early phase is critical—it can shape outcomes based on how swiftly an advertising system comprehends user intent and adapts to various options. AI is redefining this stage, enhancing the efficacy of recommendation systems and delivering intelligent tools that benefit advertisers, especially small and medium enterprises (SMEs).
Traditionally, campaigns begin with a “cold start,” a period characterized by limited data and unpredictable performance. This often necessitated waiting for impressions and clicks to accumulate before campaigns stabilized, requiring manual adjustments. However, advancements in multimodal user behavior analysis and large language models (LLMs) are shortening this phase. According to Jiang Jie, Vice President of Tencent, using LLMs with embedded prior knowledge allows advertising systems to deduce intent and explore delivery strategies more quickly, enabling earlier momentum and reducing the need for resource-intensive course corrections.
Advertisers are increasingly seeking ways to enhance creative output, yet many face hurdles with complicated setups and slow, costly creative testing. Performance can vary significantly based on audience, context, and placement, creating unpredictability in outcomes. As campaigns scale, teams find themselves balancing adjustments with strategic improvements, often to their detriment.
To overcome these challenges, Tencent has launched its intelligent delivery suite, Tencent Ads AIM+. AIM+ automates critical processes such as targeting, bidding, placements, and creative optimization. With this system, advertisers define their objectives and preferences, allowing the platform to coordinate delivery and optimization throughout the campaign lifecycle. This not only reduces manual steps but also enhances consistency, allowing teams to focus on broader strategic goals.
The advantages of faster learning are evident in key performance metrics. With AI integration across ad recommendation, delivery, and creative optimization, certain advertising inventory has seen click-through rates increase to approximately three percent, compared to the historic average of one percent. In an industry where even marginal gains can have significant impacts, this improvement is substantial. Operational efficiency has also experienced a notable uptick; data indicates that for every $1,400 spent, the required platform operations decreased by around 80 percent, streamlining execution and minimizing repetitive tasks.
For businesses of all sizes, improved return on investment is a critical consideration. Traditionally, creative production has favored larger enterprises with significant resources, as testing new ideas can be time-consuming and costly for smaller teams. However, AI-supported creative tools are helping to level the playing field. By analyzing high-performing ads and generating fresh variations, teams can experiment with increased volume without needing to expand personnel or production budgets. One advertiser utilizing Weixin Store launched a campaign using solely AI-generated materials, effectively halving creative costs while significantly boosting return on investment.
The evolution of AI in advertising is not merely a trend; it represents a fundamental shift toward more sophisticated systems that utilize multimodal signals combining text, images, and video for better delivery. Automation is becoming a cornerstone of processes including planning, optimization, and execution. As AI costs decline, creative flexibility increases, allowing advertisers to tailor content for different audiences and contexts without scaling production efforts.
As Jiang noted, this shift emphasizes the value of originality, as human creativity and judgment become key differentiators in an increasingly automated landscape. The most significant impact of AI in advertising lies in the clarity it provides. Enhanced learning, reduced manual intervention, and lower creative barriers enable businesses to operate with greater confidence. As teams spend less time on adjustments, they can instead focus on shaping successful outcomes.
Continuing this trajectory, Tencent is fostering innovation through algorithm competitions, with the upcoming 2026 edition set to emphasize sequence modeling for large-scale recommendation systems. As advertising technologies evolve, the competitive advantage will increasingly belong to companies that can learn and adapt more swiftly, rather than simply those that invest more heavily.
