Earlier this year, Madison Media launched MbrAIn, an AI-powered media planning agentic system designed to optimise decisions, among other things. MbrAIn acts as an always-on strategic intelligence layer, speeding up the planning cycle by synthesising inputs, structuring hypotheses and stress-testing assumptions. The agency says the next decade will be won by brands that treat planning as a continuous, intelligence-led operating system where strategy is structured, explainable and improves with every cycle.
A number of brands are also developing their own in-house AI tools for better returns on their media bucks. Take Godrej Consumer Products’ Media Allocation and Spends Harmonisation (MASH), a media planning tool that has been deployed to improve efficiency, speed, and precision of its marketing campaigns. It has allowed the company to move away from traditional, iterative agency planning toward a faster, data-driven approach.
“The traditional model—built on scale, layers and specialised silos—is being fundamentally challenged,” says Nandini Dias, strategic advisor, independent board director & former CEO of Lodestar UM. “As advertisers experiment with AI across various aspects of their businesses, they are also putting pressure on agencies to evolve, often switching agencies if they believe someone else is more AI-enabled and digitally savvy.”
Digital Takeover
Even until a few years ago, it was not uncommon to find media planners hunched over spreadsheets or negotiating for ad slots based on historical metrics like gross rating points, target rating points, and circulation numbers rather than real-time clicks or conversions. This legacy approach relied on direct human-to-human interaction between advertisers (or their agencies) and media vendors, such as TV networks, radio stations, and print publishers.
AI and programmatic tools have taken over a huge chunk of that task — bidding, targeting, optimisation and budget allocation — across media platforms. Experts say AI has become an intelligent layer of the media planning and marketing function enabling agencies to keep up with growing demand for outcomes from brands. “AI has materially transformed the execution layer of media buying in India, particularly across programmatic, search, social, and retail media environments,” says Meher Patel, founder of adtech platform Hector. “A clear signal of this shift is that programmatic now accounts for 42% of India’s digital advertising spend.”
Full automation of media planning and buying is still some way off. Tech tools have automated 15-25% of the task overall, aver experts, though on the digital side, AI deployment has been sharper. “It roughly covers 60-80% of digital biddable buying today across platforms,” says Rohan Chincholi, chief digital officer, Havas Media India.
Tranditional media still relies on human intervention for best results. Legacy media still relies on static data, primarily offered by, say, IRS and BARC. As a result, AI usage in offline media is largely restricted to automation and workflow efficiencies, not decision-making.
Structural shift
The growing uptake of AI tools has the potential to fundamentally alter the structure of advertising agencies, say experts. “What earlier required three separate teams — creative, media and analytics — can now be managed by a single, AI-enabled setup. This drives speed and efficiency, but also risks reducing the diversity of thinking and specialised craft,” says Havas’ Chincholi.
Manpower-intensive roles such as data processing, daily reporting and client interactions are now automated, leading to leaner teams. “At an organisational level, the traditional 7-8 layer hierarchical structure is flattening,” says Dias. While this might not lead to outright job cuts, there will be less demand for repetitive roles and organisations will seek people in more strategic, analytical and creative thinking roles, say experts. “The uncomfortable truth is that agencies are still figuring out their next avatar,” says Dias.
There are still some gaps in this transition. With media planning and buying being driven by algorithms, there is a convergence in campaign strategies, with multiple advertisers relying on similar optimisation frameworks. “While this standardisation improves operational efficiency, it risks limiting differentiation and weakening the development of distinctive, long-term media strategies,“ says Patel.
While AI is a powerful tool for detecting bot traffic and inappropriate ad placements, it also poses some risks — at least now. Some marketers have reported incidents such as AI hallucinations or off-brand material appearing side by side or within campaigns. Of course, it’s a matter of time before all that is ironed out.