Mobavenue’s Tejas Rathod On Why AI Will Drive The Next Phase Of India’s Digital Advertising Growth

Marketing was once considered a game of darts in the dark. Earlier, brands used to cast their nets wide, hoping something would stick. But those days of ‘spray and pray’ are rapidly giving way to AI-powered solutions designed to engage targeted consumers and drive conversions for a genuine return on investment.

Market data also underlines this shift. Globally, the madtech market, which operates at the intersection of marketing technology (MarTech), advertising technology (AdTech), and data technology (DataTech), is undergoing a seismic change. Industry analysts estimate that by 2027, publishers, marketers, agencies, and those that enable them will invest $245 Bn annually in madtech, up from $100 Bn in 2020. 

It is more than a market projection; it is a signal flare. As consumer journeys become increasingly fragmented and ad platforms become more complex, brands can no longer afford to fly blind and rely on generic media buying. They need partners who can ensure hyper-personalisation, automation, and, above all, measurable outcomes. 

As in every other domain, artificial intelligence (AI) is quietly, yet fundamentally, rewriting the playbook of new-age marketing. From insight mining and predictive modelling to automated campaign execution, AI is transforming how decisions are made and delivered with minimal human intervention for maximum outcomes.

One of the leading changemakers in this domain is Mobavenue. This programmatic advertising company automates media buying and helps brands optimise ad spend, target audiences with precision, and scale customer engagement to enhance their marketing efforts.

Set up by Tejas Rathod, Kunal Kothari, and Ishank Joshi, the company has positioned itself as a new-age madtech agency, guiding brands through every stage of the customer funnel — from awareness, acquisition, to retention — while enabling them to grow beyond walled gardens or closed ecosystems. 

In an exclusive interaction with Inc42, Rathod, Mobavenue’s founder and COO, delved deep into the madtech platform’s AI bet as the foundation of its expanding product suite. He also shared his views on how brands should integrate AI in their marketing strategy and why India is poised to lead madtech innovations. Here are the edited excerpts. 

Inc42: How has Mobavenue’s approach to AI-led marketing evolved? What key trends have driven this change, and what adjustments have you made along the way?

Tejas Rathod: When Mobavenue was launched in 2017, our operations were largely manual as we were in the early stages of building our programmatic Demand-side Platform (DSP). Back then, we tailored our campaigns based on marketers’ input, but lacked deeper analytical insights and predictive intelligence. For example, if a client wanted to target specific users of a particular gaming app in Mumbai, our system would execute that request, but without adding much value beyond the basics. 

However, over the past 5 years, brands have shifted away from simply running ads or using broad targeting. Today, brands are laser-focused on outcomes — conversions, engagement and ultimately, ROI. This evolution in expectations has driven us to transition from manual, rules-based operations to a smarter, AI-driven model. Automation, self-learning systems, and decision-making powered by historical data are now at the core of our platform. Instead of relying on human interventions, our AI-powered platform now learns from customer behaviour and actively optimises campaigns to eliminate inefficiencies and improve results.

This adoption wasn’t random — it was a strategic response to the current market demands. Precision, personalisation, and adaptive intelligence are now essential to marketing success, and we’ve built our systems to deliver exactly that. As the bar for performance continues to rise, we remain focused on offering smarter, faster, and more efficient targeting solutions that help brands achieve measurable outcomes.

Inc42: How have you embedded AI in Mobavenue’s product suite? 

Tejas Rathod: At Mobavenue, we have not acquired any technology; we have built our own technology. Our proprietary AI-powered core engine serves as the backbone for our entire product suite: PrsmX omnichannel brand awareness platform), SurgeX (user acquisition platform), ResurgeX (retargeting and remarketing platform), and AudX (consumer intelligence platform). Each of these products leverages this core engine, which holds the decision-making power for all key functions.

The core engine features a set of advanced machine learning (ML) and AI capabilities that enable the identification of strategic and lookalike audiences for brands across multiple devices, including connected TVs, mobile phones, desktops, laptops, and digital out-of-home screens, all in under 100 milliseconds. It enables automated, real-time decisions that drive performance at scale.

All credit goes to the deep AI integration and AI-driven matchmaking capabilities for our hockey stick growth. Today, we serve around 50 crores ads a day — a scale at which manual decision-making for each ad is not practicable. Our AI-powered core engine leverages machine intelligence to analyse performance, track user conversions, and optimise targeting and conversion among these 50 cr ads for faster turnaround time (TAT) and better ROI.

Inc42: In your view, is AI in marketing still an efficiency tool, or is it becoming a growth lever?

Tejas Rathod: AI has eliminated the need for manual tasks, such as filtering through massive amounts of data in spreadsheets. For marketers managing multi-million-dollar budgets, it has become a significant growth driver — streamlining production, audience targeting and campaign execution at scale.

In a recent interview, Mark Zuckerberg also mentioned this shift. An advertiser will soon be able to input a website, budget and goals, and AI will generate everything else, including creatives, targeting and spending allocations. It is not just efficient — it makes sophisticated and precise advertising accessible to all.

Inc42: Is AI-driven marketing in India outpacing global growth? What is driving this momentum?

Tejas Rathod: India is definitely setting the pace in certain areas, mainly in the adoption of technology. In recent conferences, AI has been a topic of national discussion, with policymakers, industry leaders, and government research groups exploring its implementation and impact.

On the ground, businesses are actively experimenting with AI, especially in the marketing space. They are running pilots, integrating models into existing systems, and generating business value. In fact, AI is transforming the way creative assets are produced. Rather than relying on large design or video production teams, many brands are now leveraging Generative AI (GenAI) tools to automate creative workflows while respecting brand guidelines and brand parity.

From a media buying angle, brands are also putting data from Google and Facebook APIs into their LLM infrastructure to analyse campaign outcomes and make necessary changes across digital touchpoints. This has led to faster decision-making, more efficient ad spend, and a feedback loop that gets smarter with each cycle. 

Inc42: Do you think AI can help reduce customer acquisition costs in the next two or three years?

Tejas Rathod: AI is reducing the customer acquisition playbook on multiple fronts. First, there is smarter targeting. AI models can predict user behaviour through historical user data and user characteristics with remarkable precision. It means ads are more likely to reach high-intent target audiences, reduce waste and improve efficiency.

Second, artificial intelligence unlocks hyper-personalisation at scale. It can dynamically adapt content based on location, language, and user preferences, whether displaying ads in Kannada for users in Bengaluru or customising creatives for audiences in tier II and III cities. Again, all this happens in near-real time.

Then, there will be automation and predictive testing of creatives. AI can simulate campaign performance even before launch, forecasting outcomes of various metrics such as click-through and conversion rates. That reduces the guesswork — the cost and time associated with traditional A/B testing. Advertisers can iterate faster, personalise and optimise on the fly, and make more informed decisions, with the customer acquisition cost (CAC) dropping significantly. 

Given today’s scenario, this is not a projection for two or three years; it is already in motion. Many companies are actively using these AI tools. By next year, we will see broader adoption and more measurable impact across the industry.

Inc42: Can you walk us through a go-to-market use case where AI helped reduce CAC or significantly improved campaign ROI?

Tejas Rathod: Our gaming clients are compelling examples. Overall, the gaming industry is highly data-driven. When we worked for one such company, we integrated first-party user persona data [information that a company collects from users/target audiences via its channels] from its customer relationship management [CRM] system into our AI core engine. It primarily covered behavioural attributes and helped our system gain a clear understanding of the user types who had converted earlier.

When the campaign went live, our AI model didn’t have to start from scratch. It already knew high-conversion cohorts from Day 1 — the kind of users the brand wanted to reach, the geographies that converted better, the apps those users were on and the inventories they engaged with. This baseline understanding allowed us to optimise targeted reach and keep a lid on media spending from the beginning rather than going through the 30-day test-and-learn cycle.

With the AI model leveraging the marketers’ CRM data and learning from historical patterns, we were able to reduce customer acquisition cost (CAC) and scale the campaign within the first week. Otherwise, it would have taken several weeks to achieve that. 

Inc42: From planning to execution, how do you use AI for an entire campaign?

Tejas Rathod: Well, we haven’t yet embedded AI in every phase of the product lifecycle. But we have made significant headway, especially in campaign optimisation and automation of creatives, where AI is delivering measurable value.

Our AI models are trained on a rolling basis every three days to accommodate fresh performance data. After each [three-day] cycle, we feed the cumulative campaign outcomes back into the system. The models then analyse a wide range of variables, such as which inventories performed better, the best bidding strategies, bid accuracy, win-loss ratios on impressions, and the broader impact on cost and efficiency.

This round-the-clock feedback loop enables us to fine-tune campaigns with minimal manual input. Our media planners today spend a fraction of the time on manual adjustments compared to just 18 months ago, freeing them up to focus on strategy rather than mechanics. 

Campaign creation is still a manual process, but we are evolving it towards automation. While final approvals rest with the respective brands, we have partially automated the creation of creatives by generating multiple variants from existing assets. This allows us to test performance more efficiently and iterate quickly. Complete automation is a work in progress, but it is the next significant milestone on our road map.

Inc42: What are the most exciting AI innovations you plan to integrate in the next 18 months?

Tejas Rathod: We are doubling down on two core capabilities. The first is automated campaign creation. Although much of the industry still relies on manual or semi-manual workflows, we are building a large language model (LLM) API for content creation. When it is ready, a marketer can input a simple prompt, and the system will auto-generate a fully configured campaign to be deployed within our DSP. It is not just a time-saver. It will make every campaign more intuitive and scalable.

The second is LLM-powered analytics and reporting. Our MIS team spends nearly five hours a day extracting data from various sources and entering it into the spreadsheet. Next, our finance team reviews it, and our vendors are paid. Even now, these reports are quite drab, featuring rows and columns of static data, but we want to change that. 

We want marketers to delve deep into microdata, especially tiny modules, for a thorough understanding of what’s happening on the ground. In natural language reporting, users can delve deeper into their queries, and the system responds naturally, in real-time, with no dashboard navigation or SQL skills required. This lowers the barrier to data access and makes performance intelligence available to every stakeholder, not just data teams.

Apart from the above AI models, we are also working on new product launches like DiscvrX – Contextual & OEM DSP and EarnX – Monetisation Platform, which are going to drive enhanced digital growth for brands across the globe.

Inc42: With AI reshaping modern-day marketing, how can founders and CMOs embed it for effective impact?

Tejas Rathod: Start small and scale smart — that’s the strategic blueprint for companies just starting. Begin with pilots in specific funnels, build a proof of concept, test it rigorously and iterate before full-scale adoption. Once you have clarity on what a brand expects from AI, scale up from there.

One should also invest early in hiring and upskilling AI engineers, machine learning practitioners and data science professionals who can tailor models for specific business contexts. For brands, it is equally important to choose the right AI-native technology partner or solution providers that will drive growth, minimise operational friction, and help them avoid reinventing the wheel. 

To conclude, think of AI as a layered stack: Integrate the essentials, build on a robust foundation and allow the system to evolve. When aligned with the right Key Performance Indicators (KPIs), AI becomes less of a moonshot and more of a real-time growth engine.