From faster campaign learning and better targeting to higher click-through rates and more stable performance, AI is reshaping how advertising works. Here’s how intelligent systems are helping businesses improve performance while simplifying execution.

You launch a campaign with a clear goal, a strong product, and creative based on solid foundations. Early indicators show, however, that performance is uneven. You make some adjustments, swap creatives, and wait for the system to learn.

This early phase is familiar to most advertisers. It’s also where outcomes are shaped – sometimes positively, sometimes not – by how quickly an advertising system can understand intent, test options, and adapt.

AI is changing that moment, improving the efficiency and effectiveness of recommendation systems, while also packaging these capabilities into intelligent tools for advertisers. This is especially helpful for SMEs, enabling them to streamline campaign management and boost creativity.

Faster learning, earlier momentum

Most campaigns begin with a cold start, the period when an advertising system has limited data and performance can be unpredictable. Traditionally, this meant waiting for impressions and clicks to accumulate before delivery stabilized, often requiring manual adjustments to compensate.

Multimodal User’s Behavior Sequences and Large Language Models (LLMs) shorten this phase. By using LLMs with embedded prior knowledge, advertising systems can infer intent, explore delivery strategies, and reach stability earlier. As Jiang Jie, Vice President of Tencent, notes, this allows systems to respond sooner rather than relying on long learning cycles.

For businesses, that means earlier momentum and fewer resources spent correcting course.

Complicated setups and low creative capacity: why advertising has been hard to scale

Advertisers want to boost creative output and increasingly turn to AI to improve efficiency.

Setup is often manual and complicated. Creative testing is slow and costly. Performance varies widely across different audiences, contexts, creative and placements, making outcomes hard to predict. As campaigns grow, teams spend more time adjusting settings and less time improving strategy.

These frictions compound with scale, and place smaller teams at a disadvantage.

An intelligent product for simpler campaign execution

To address these execution challenges, Tencent introduced its intelligent delivery suite, Tencent Ads AIM+.

AIM+ simplifies campaign execution by automating targeting, bidding, placements, and creative optimization. Advertisers define objectives and preferences. The system coordinates delivery and optimization across the campaign lifecycle, reducing manual steps and improving consistency.

Higher click throughs and better operational efficiency: performance gains that compound

The impact of faster learning shows up in the metrics that matter.

With AI applied across ad recommendation, delivery, and creative optimization, some advertising inventory has seen click-through rates rise to around three percent compared to historic rates of one percent. In an industry where incremental gains compound, it’s a meaningful lift.

Operational efficiency improves as well. Data shows that for every US$1,400 spent, required platform operations fell by around 80 percent – reducing repetitive work and speeding up execution.

Advertisers focus on direction. The system handles coordination.

Improved ROI for businesses of any size

Creative production has long favored businesses with large teams and budgets. Testing ideas requires time and capacity that smaller teams often lack.

AI-supported creative tools help narrow that gap. By analyzing high-performing ads and generating refreshed variations, teams can test more ideas without expanding headcount or production costs.

One Weixin Store advertiser ran a campaign using only AI-generated materials. By launching the ads without a dedicated creative team, the business cut creative costs by nearly half, and significantly improved return on investment.

For many SMEs, this lowers the barrier to experimentation and shifts the advantage from scale to clarity.

What is changing and what comes next

AI is reshaping how advertising systems work.

Data is evolving from structured inputs into multimodal signals that combine text, images, and video. Delivery processes are becoming more automated across planning, optimization, and execution.

Creative is also becoming more flexible: as AI costs fall, ads can increasingly adjust creative to different people and contexts automatically, expanding relevance without increasing production effort.

As Jiang has observed, this evolution raises the value of originality. As systems handle execution and optimization, human judgment and creative thinking become the differentiators.

A clearer way forward

The most meaningful impact of AI in advertising is not novelty. It is clarity.

Faster learning, fewer manual steps, and lower creative barriers help businesses operate with confidence. Teams spend less time correcting and more time shaping outcomes.

Notably, Tencent is driving continued innovation through its algorithm competitions. The 2026 edition will focus on sequence modeling for large-scale recommendation systems, helping foster talent development and technical exchange.

As advertising systems evolve, the advantage will belong to businesses that learn faster, not just those that spend more.