#e4mXplains:  Vibe coding gains ground in advertising; a shift from campaign execution to AI-led intent

A new term is beginning to define the next phase of advertising’s evolution. Vibe coding, an AI-led approach that replaces manual campaign building with intent-driven prompts, is rapidly gaining traction across marketing circles, pointing to a structural shift in how brands plan, create and optimise campaigns.

At a time when consumer attention is increasingly fragmented and cultural cycles move faster than traditional campaign timelines, marketers are being pushed to rethink execution. Vibe coding addresses this gap by allowing brands to define the mood, tone and context of a campaign in simple language, while artificial intelligence handles the heavy lifting across creative, media and optimisation layers.

The shift is not merely semantic. It represents a deeper transition from linear workflows to continuous, adaptive systems. Campaigns are no longer built in stages and evaluated after launch. Instead, they are designed to evolve in real time, responding to performance signals and audience behaviour as they unfold.

From process-heavy to prompt-led marketing

The early adoption of vibe coding is being driven by its ability to compress timelines and unlock scale. AI systems can generate multiple versions of ad creatives, test them simultaneously and refine outputs based on real-time feedback. This replaces traditional A/B testing models with dynamic experimentation at scale.

In India, platforms such as Vibelets.ai have demonstrated measurable gains, reporting campaign performance improvements between 20 and 30 per cent and decision-making cycles that are nearly a third faster, according to media reports. These efficiencies stem from the platform’s ability to detect creative fatigue and audience drop-offs instantly, enabling marketers to adjust campaigns without delay.

A notable example of this shift playing out in performance marketing comes from Cashify, the online marketplace for used electronics. The company tested Google’s AI-powered Performance Max through AI Max in India by feeding the system with product data and allowing it to identify additional relevant queries. 

According to reports, conversions increased by 15 per cent and cost per acquisition decreased by 12 per cent compared to standard campaign setups. The case underlines how AI-led, constraint-driven inputs can improve targeting efficiency without requiring manual intervention.

Global adtech platforms are also embedding similar capabilities. AI-powered advertising tools are enabling marketers to expand keyword discovery, automate bidding and generate creative assets directly within campaign interfaces. Early use cases have shown conversion improvements of around 15 percent alongside reductions in acquisition costs by approximately 12 percent, reinforcing the business case for automation-led workflows.

This shift is collapsing the traditional boundaries between strategy, creative and media. Instead of multiple teams working sequentially, unified systems increasingly manage campaigns by continuously aligning inputs and outputs.

India’s diversity becomes a catalyst

India’s complex linguistic and cultural landscape is accelerating the adoption of vibe coding. The ability of AI to generate content in multiple languages and adapt messaging to regional nuances is enabling brands to scale localisation in ways that were previously resource-intensive.

Campaigns built using AI-generated multilingual scripts and region-specific narratives have shown significantly higher engagement and recall. In several cases, brands have moved away from generic national messaging to hyper-local storytelling, creating content that resonates more deeply with diverse audiences.

This evolution is also redefining targeting strategies. Instead of relying solely on demographic filters, campaigns are increasingly shaped by cultural signals and contextual relevance. The creative itself becomes a driver of targeting, aligning content with audience interests in a more organic manner.

The result is a shift towards emotional and cultural alignment as key drivers of performance. Engagement is no longer measured only by clicks or impressions, but by how effectively a campaign connects with audiences across different contexts.

Metrics evolve alongside workflows

As vibe coding reshapes execution, it is also redefining how success is measured. Traditional metrics such as click-through rates and return on ad spend remain important, but they are being complemented by new indicators that capture speed, adaptability and engagement depth.

Creative velocity is emerging as a key metric, reflecting how quickly new assets can be generated and deployed. Real-time performance tracking is replacing periodic reporting, allowing marketers to respond instantly to changes in campaign effectiveness. Sentiment analysis and brand recall are gaining importance as indicators of emotional resonance, particularly in culturally driven campaigns.

The shift towards continuous optimisation is also reducing the lag between insight and action. Campaigns can now be adjusted within minutes based on performance data, significantly improving efficiency and reducing wasted spend.

At the same time, the increasing reliance on AI systems is placing greater emphasis on the quality of inputs. First-party data, audience signals and clearly defined objectives are becoming critical in guiding automated systems toward meaningful outcomes.

Rewriting the marketing playbook

The rise of vibe coding is prompting a broader rethink of marketing structures. Creative teams are transitioning from execution roles to direction and curation, focusing on defining the overall narrative rather than producing individual assets. Media planning is becoming more fluid, with budgets dynamically allocated based on real-time performance signals.

Automation is also reshaping the role of marketers, shifting the focus from operational tasks to strategic oversight. The ability to articulate clear intent and guide AI systems is emerging as a key capability, as opposed to managing granular campaign details.

However, the transition is not without its challenges. Concerns around brand safety, authenticity and regulatory compliance are becoming more prominent as AI-generated content scales. The risk of generic or culturally insensitive outputs underscores the need for human oversight and strong brand frameworks.

Regulatory frameworks around AI in advertising are still evolving, and marketers are expected to navigate issues related to transparency, intellectual property and data usage. As AI becomes more deeply embedded in marketing workflows, governance and accountability will play a critical role in ensuring responsible adoption.

A shift that extends beyond technology

Vibe coding signals more than just a technological upgrade. It reflects a broader shift in how marketing is conceptualised, moving from execution-led processes to intent-driven systems that prioritise speed, relevance and adaptability.

In a market like India, where digital consumption continues to grow and cultural diversity demands constant localisation, this approach offers a pathway to scale without compromising relevance. The ability to generate and optimise campaigns in real time aligns closely with the demands of a rapidly evolving consumer landscape.

As the industry continues to experiment with this model, the focus is likely to shift towards balancing automation with strategic clarity. The effectiveness of vibe coding will depend not just on the sophistication of AI tools, but on how well brands define the intent that drives them.

In that sense, the emergence of vibe coding marks a turning point. It places the emphasis back on the core of marketing, where clarity of thought and understanding of the audience become the primary drivers of impact, even as machines take over the mechanics of execution.