Fewer clicks, faster decisions: How Conversational AI is shaping Indian commerce

The language of commerce is quietly changing. For over two decades, the internet economy has been built on clicks, impressions and conversion funnels that stretch across multiple touchpoints. Today, that structure is beginning to fold in on itself. What emerges in its place is not simply a faster funnel but a fundamentally different way of making decisions, one where the consumer does not navigate the internet as much as they converse with it.

This shift is being driven by the rise of agentic AI, systems that do more than retrieve information. They interpret context, anticipate intent and guide outcomes. In this new environment, discovery is no longer a linear journey and evaluation is no longer manual. The process collapses into a single interaction where the user asks, refines and acts. The implication is clear. The future of commerce in India will not be driven by more choice but by better decisions.

The early signals are already visible. Data presented during industry discussions points to a 40 per cent reduction in touchpoints when conversational AI tools are used, alongside a 53 per cent higher likelihood of purchase within 30 minutes of exposure. At the same time, the rise of AI-powered customer engagement is showing tangible business outcomes, including a 236 per cent increase in AI-led customer service interactions, a 35 per cent reduction in churn and a 30 per cent increase in lifetime value.

These are not incremental gains. They point to a redefinition of how value is created and captured in digital commerce.

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The end of search as we know it

At the heart of this transformation lies a simple behavioural shift. Consumers are no longer searching in the traditional sense. They are asking.

Aditya Varadarajan, Director India and SEA at InMobi Advertising, frames this as a reset rather than an evolution. “Consumers are no longer searching in the traditional sense, they are asking. A query is no longer just to find me a dress but something far more layered and personal, with AI expected to interpret the situation and suggest what fits best,” he says.

This change alters the role of platforms and brands alike. Instead of presenting options, systems are expected to recommend outcomes. AI does not merely respond to keywords but builds context by drawing from past behaviour, signals and preferences. The result is a commerce experience that is assistive rather than transactional.

Varadarajan adds that the impact of this is most visible in how journeys are collapsing. “AI systems will not just respond to prompts but anticipate needs. The journey collapses from discovery to decision into a single guided interaction,” he says.

This collapse of the journey challenges one of the foundational assumptions of digital marketing. The idea that more exposure leads to higher conversion is being replaced by a more nuanced understanding that relevance and timing matter more than volume. In a world of infinite options, curation becomes the new currency.

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AI and search find a new equilibrium

While the rise of conversational interfaces has sparked debate around the future of search, industry data suggests a more balanced picture. AI and search are not replacing each other but evolving in tandem.

Nick Seckold, Regional Vice President-APAC at Microsoft Advertising, notes that while journeys are becoming shorter, traditional search behaviour continues to grow. “What’s true is that the journeys are collapsing. These conversational AI tools are helping consumers get to their destination faster. But it’s not mutually exclusive from traditional search. We are seeing our volume increase,” he says.

This duality reflects a transition phase where users move fluidly between Conversational AI and search engines depending on context. The distinction lies not in the platform but in the nature of the task. Complex, intent-driven queries are increasingly moving towards conversational formats, while broader exploration continues to rely on search.

Seckold also points to a critical shift in how advertising must adapt within this environment. “We need to rewire our thinking from ten blue links on a search page into advertising that is relevant and additive to the conversation stream,” he says.

The implication is that advertising can no longer exist as an interruption. It must integrate seamlessly into the decision-making process. In conversational environments, relevance is not a feature but a requirement. Any mismatch between context and messaging risks breaking the interaction altogether.

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From visibility to recommendation

If the mechanics of discovery are changing, so too are the metrics that define success. The long-standing reliance on last-click attribution is being challenged by a broader view of performance that includes visibility, relevance and recommendation.

Varadarajan highlights this shift as a key inflection point for marketers. “The industry’s reliance on last-click attribution is likely to give way to broader definitions of performance. The end goal remains the same, delivering returns, but how that return is understood and tracked will change,” he says.

This change is closely tied to the growing importance of recommendation within AI systems. In an environment where algorithms curate options, brands do not compete merely for attention but for inclusion. Being recommended by an AI system becomes as critical as being visible.

He also points to an emerging imbalance between demand capture and demand creation. “Brands that have relied heavily on organic traction may hit a ceiling if they do not invest in generating new demand. Visibility becomes as important as conversion,” he says.

This creates a new layer of complexity for marketers. It is no longer enough to optimise for search rankings or paid placements. Brands must ensure that their content is structured, credible and contextually relevant so that it can be surfaced by AI systems during decision-making moments.

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The rise of agent-led commerce

Beyond discovery and recommendation lies a more profound shift. The emergence of agents that act on behalf of users. These agents are designed to understand preferences, remember past interactions and make decisions with minimal input.

Seckold describes this as an extension of current capabilities. “If you have to do less work as a consumer and you get more relevant results, then you will probably convert quicker and more often. The theory is higher ROI because of shorter journeys and more relevance,” he says.

However, this shift also raises new challenges around trust and brand equity. If an AI system presents a shortlist of options, the consumer is more likely to choose a brand they recognise. This places renewed emphasis on brand building even within performance-driven environments.

Seckold adds that performance marketing alone may not be sufficient in this new landscape. “If a model is surfacing three or four brands and the consumer does not know one of them, are they likely to win that consumer. Probably not. Trust still matters,” he says.

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A new layer of control and caution

While the promise of agentic AI is significant, industry voices caution against assuming full automation. The role of human oversight remains critical, particularly when it comes to brand identity and decision-making.

Gopa Menon, Co-Founder and Chief Operating Officer at Theblurr, emphasises the need for balance. “Agents trying to run campaigns and making it autonomous will happen. But there has to be a human layer for oversight. You cannot leave it entirely to agents. There has to be a brand filter and an understanding of tonality that comes from humans,” he says.

This perspective reflects a broader industry sentiment that while AI can enhance efficiency, it cannot fully replace the nuanced judgment required in marketing. The challenge lies in finding the right balance between automation and control.

Menon also highlights the structural impact of this shift on the broader ecosystem. As discovery moves from linear browsing to conversational interfaces, publishers and platforms must adapt. “The linear discovery has gone. You need to be part of the AI journey. If you are not optimised for that, you will see a dip in relevance,” he says.

This has implications not only for brands but for the entire digital value chain. Content, distribution and monetisation models will need to evolve to align with AI-driven discovery.

Rethinking metrics and media

As attention shifts towards conversational interfaces, traditional metrics such as click-through rates are losing relevance. The focus is moving towards outcomes that reflect actual business impact.

Menon points to an emerging shift in how performance is evaluated. “People are talking about moving from click to confidence. It is not about CTR anymore. It is about whether the consumer trusts the recommendation enough to act,” he says.

This redefinition of metrics aligns with the broader theme of the article. Commerce in the age of agentic AI is not about driving traffic but about building confidence. The success of a brand will depend on its ability to be recommended, trusted and acted upon within AI-driven environments.

At the same time, media allocation is expected to evolve. While overall marketing budgets may not see exponential growth, their distribution across channels is likely to change. Early experimentation in AI-driven advertising is already showing promising results, with some brands attributing a significant share of incremental sales to these channels.

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The road ahead

The transition from clicks to conversations marks a pivotal moment for India’s digital economy. It signals a shift from an attention-driven model to a decision-driven one. In this new paradigm, the role of marketing is not to guide users through a funnel but to enable them to make better choices.

For brands, this requires a fundamental rethink of strategy. It means investing in credibility, structuring content for AI discovery and embracing new metrics that capture real business outcomes. It also means recognising that the audience is no longer just the consumer but also the algorithms that mediate their decisions.

As Varadarajan notes, the industry is still in its early stages. “We are closer to learning how to walk than run. But the pace of change will only accelerate from here,” he says.

That acceleration is likely to define the next phase of India’s commerce story. In a landscape where decisions are increasingly guided by intelligent systems, the brands that succeed will be those that understand not just how to be seen, but how to be chosen.