Agents of the AI Era

Marketing is entering a new era—one where artificial intelligence does not just automate, it acts. Agentic AI, a new class of autonomous systems, is changing the way brands plan, execute and optimise campaigns. Unlike traditional marketing automation, which relies on predefined rules and workflows, Agentic AI can interpret goals, make decisions and take actions independently, almost like a digital strategist working around the clock.

In simple terms, it is the difference between following instructions and setting your own agenda. Traditional systems send emails or trigger campaigns when prompted; Agentic AI systems can analyse performance data, decide which channels to prioritise, adjust creative elements, and even negotiate media spends without waiting for human input. This shift from rule-based to goal-based intelligence is poised to redefine marketing efficiency, creativity and accountability.

For agencies and brands in India, the rise of Agentic AI signals a fundamental change in how marketing teams will operate. Instead of manually segmenting audiences or running A/B tests, marketers could soon supervise intelligent agents that autonomously manage entire campaign cycles from insight generation to optimisation.

For agencies, these capabilities are already beginning to move beyond theory and into everyday campaign workflows. Increasingly, agentic systems are being deployed to analyse performance signals across platforms, interpret competitive patterns, and generate insights that would previously take teams days to compile.

Rohan Chincholi, Chief Digital Officer, Havas Media India, says the technology is already helping agencies better understand market dynamics and optimise campaign performance. He says, “On the media side, Agentic AI is being deployed within a privacy-compliant environment to help us understand the competitive landscape for our clients. It leverages historical data across competition, creative assets, and traffic patterns to identify trends and opportunities in the market. Currently, one of the most practical applications is in consolidated reporting and insight generation. Agentic and generative AI capabilities are helping us aggregate campaign data across platforms and analyse performance to understand what is working, what isn’t, and where optimisation opportunities lie. The strength of this integrated reporting framework is that the platform continuously learns from campaign signals and impression-level data, improving the quality of insights over time.” This ability to synthesise signals across platforms is gradually shifting the role of AI from simple automation toward active decision support within marketing ecosystems.

Anindita Veluri, Director Marketing, Adobe India, shares that at Adobe, Agentic AI is not just a new capability but a new operating model. It represents the shift from ‘How do we get more done with the same team?’ to ‘What becomes possible if our teams can focus only on work that truly matters?’

She notes that this evolution became especially visible with the updates announced at Adobe MAX 2025, where Adobe expanded its collaboration with Google Cloud to bring models like Gemini, Veo and Imagen directly into Firefly, Photoshop and Premiere Pro.

“With Firefly Foundry, enterprises particularly in media and entertainment can train brand-specific AI models using proprietary content. This enables high-fidelity image, video and multimedia generation that preserves authorship, ownership and creative control across production workflows. For us, Agentic AI is not about replacing human thinking. It is about removing operational friction, accelerating decision-making while clearing the runway so our best ideas can actually take flight,” states Veluri.

Hyundai Motor India is also gearing up for the next phase of AI-driven customer engagement, building on the strong performance of its existing chatbot ecosystem. According to Virat Khullar, AVP and Vertical Head – Marketing, Hyundai Motor India, the company’s current AI-powered Hyundai Chatbot has already reshaped how customers interact with the brand.

“Our focus has always been on delivering customer-centric innovation,” he says, noting that the chatbot now handles “24x7, personalised, and seamless interactions” across platforms including the website and WhatsApp.

The scale of adoption is significant. “Every month, over one lakh customers engage with the chatbot, driving tangible results in sales and service,” Khullar explains. The automation of routine conversations has also delivered real savings, with Hyundai “saving over Rs 10 lakhs annually” through AI-led efficiencies.

As these intelligent agents take over functions once controlled by people, one key question remains: who takes accountability when AI drives the marketing wheel?

Rajesh Jain, Founder and Group Managing Director, Netcore Cloud, believes that while Agentic AI represents the future, the industry is still in a transitional phase – somewhere between automation and autonomy. “First there comes automation. Endgame is autonomous. But in the middle, you will have the human in the loop,” he says.

Explaining how Netcore envisions this evolution, Jain adds, “At every stage, the multi-agent system will basically ask you whether this is the right understanding and what everyone wants. Nothing gets executed without the human saying yes.”

He likens this process to how conversational AI platforms operate. “Because sometimes once you see what’s there, you may also want to give some clarifications on the understanding. It’s going to be very similar here. Of course, there will be guardrails. You’ll have brand guidelines, the brand kit, media kit, but there will be a human in the loop,” he explains.

Within agency environments, these systems are increasingly embedded into day-to-day campaign management, particularly in areas that previously required extensive manual reporting and analysis. According to Chincholi one of the most immediate benefits lies in how AI agents streamline campaign reporting and insight generation. He opines, “AI-driven reporting agents can also pull data from multiple platforms and generate automated dashboards and insights through natural language queries, significantly reducing the manual effort involved in campaign reporting while enabling teams to focus more on strategy, optimisation, and decision-making.”

Hareesh Tibrewala, CEO, Anhad Digital, points out that the rise of Agentic AI is being fuelled by both technological progress and market pressure. “On one hand, Large Language Models (LLMs) are becoming better, making Agentic AI a real possibility,” he says.

He states that more mature frameworks and better data infrastructure within enterprises, such as customer data platforms (CDPs), are providing agentic AI the raw material required to generate meaningful outcomes. But it is not just technology driving the shift; it is necessity. Marketing cycles that once operated in ‘batch mode’ are no longer viable in an era of real-time engagement.

“With the increased cost of customer acquisition and dramatic media fragmentation, brands cannot work anymore in batch mode, where you run a campaign and then spend time poring over the outcome and optimising it later,” Tibrewala explains.

According to Srinivasan Subramani, VP – Growth & AI, CleverTap, there are noticeable early wins in lifecycle marketing and retention because that is where the signal is strongest. He notes that first-party data and consistent behaviour patterns allow AI agents to learn effectively and deliver meaningful results.

“The biggest impact of agentic AI will be its ability to hyper-personalise customer communication in a way that simply isn’t humanly possible,” Subramani says.

Subramani envisions a future where “every customer could have their own dynamic engagement calendar — personalised to their motivations, shaped by their browsing and purchase habits, and continuously optimised based on how they respond.”

Experts believe that in India, the next wave of agentic AI adoption will be led by industries operating at massive scale and complexity – places where even marginal efficiency gains translate to significant business value. These sectors share a common thread: they have relatively mature digital cores with clearly defined process ecosystems, and they have already invested heavily in automation and data, making them primed to experiment with autonomous agents.

Bharat Khatri, Chief Digital Officer, Omnicom Media, Asia Pacific, notes, “AI will increasingly support areas such as budget optimisation, scenario modelling and investment allocation, simply because these decisions depend on analysing large volumes of signals in real time. In practice, this means working with clients to define where human authority is essential and where AI can operate with oversight. It is similar to how automated programmatic buying works today but extended across more parts of the marketing workflow. This model also enables the outcome-based approaches our clients increasingly want where budgets can flex dynamically, ROI can be forecast earlier & creative can be linked more directly to business results of our clients.”

Mayank Rausaria, Partner, Deloitte India, says these industries stand out because “they’ve already built the digital plumbing needed for autonomous agents to plug in and deliver value from day one.”

He notes that some operate on thin margins and high competition, making automation a strategic necessity rather than an optional upgrade. Others benefit from cloud-native systems, modern enterprise resource planning (ERP) tools, CDPs and AI-driven workflows that reduce integration barriers. But Rausaria cautions that readiness is not uniform. “Enterprises shouldn’t assume entire sectors will adopt at the same pace. The smarter approach is to assess readiness at a process level,” he says.

For Kedarswamy Ravangave, EVP – Marketing, Kotak Mahindra Bank, the real unlock will be trust – and that trust will come from clarity. “Trust will grow as AI stops behaving like a workflow engine and starts behaving like a reasoning engine,” he says.

Ravangave outlines three essentials: “clean, connected, consented data; clear goal-setting; and a culture comfortable with co-creation.” Agentic AI is beginning to take on tasks that traditionally sat within creative, media, and digital agencies – from drafting campaigns to managing optimisation workflows. While this shift is prompting questions about whether AI could cannibalise parts of agency work, its real impact remains uncertain.

Abhinay Bhasin, Senior Vice President – Product and Technology, Dentsu India, believes the fear is overstated. “Agentic AI won’t cannibalise the work — it will cannibalise the tasks, not the talent,” he says. Bhasin expects 40–60% of low-value tasks such as pacing checks, bid adjustments and reporting consolidation to disappear, pushing teams toward more strategic roles. “The value shifts from controlling the levers to designing the levers, the rules and the outcomes,” he adds.

Ahmed Aftab Naqvi, Global CEO and Co-Founder, Gozoop Group, shares a similar view. “Agentic AI isn’t here to cannibalise agency work, it’s here to supercharge it,” he says. He argues that the strongest agencies will combine talent with transparent AI systems, “building audit trails, decision logs and human override points to understand why an AI agent acted the way it did.”

Sarvesh Bagla, Founder and CEO, Techmagnate, believes this shift will realign industry roles. “Marketers will move from campaign execution to strategic supervision,” he says. “Agents will handle optimisation, reporting, and performance management in real time, allowing humans to focus on creativity and insight.”

For media planners, the day-to-day of buying and budgeting may soon look very different. “Media planners will set strategy and quality parameters while AI manages budgets and learns from outcomes,” Bagla explains.

Agentic systems are also increasingly being used to simulate planning scenarios before budgets are deployed, allowing marketers to test different strategies before committing investments. According to Das, these systems can dramatically accelerate the speed and quality of decision-making in media planning. “Agentic AI will certainly evolve to play a much bigger role in managing complex media functions, including scenario modelling, forecasting outcomes, and recommending budget allocations across channels. All, with a string of prompts & a click. It can dramatically increase decision speed, improve investment efficiency, and unlock deeper insights from campaign data. Instead of waiting days or weeks for analysis, marketers can explore multiple planning scenarios almost instantly and make more informed decisions about where their budgets will deliver the strongest impact.” However, Das emphasises that human oversight will remain critical in major investment decisions, particularly as brands navigate increasingly complex media ecosystems.

As agentic AI moves from concept to deployment, brands are confronting a new question: what will it take to adopt autonomous marketing workflows?

Shashishekhar Mukherjee, Head – Digital Marketing & D2C, Dabur India Ltd., says the starting point is discipline. “Brands will need a much stronger data and governance cadence — clean, unified customer and campaign data, and policy guardrails that define what agents can and cannot touch,” he says. “Marketers need to evolve from managing agencies to managing AI agents,” Mukherjee adds.

Vikas Nair, VP and Head of Marketing and Communications, Century Real Estate, states that Agentic AI will disrupt slow marketing routines. “By the time campaigns are executed, analysed and insights acted upon, it is often too late for meaningful impact,” he says. “Clean, consistently updated data is the bedrock, especially for offline-heavy sectors like real estate,” Nair notes.

Vibhor Gulati, Co-founder, Defodio Digital, says agentic AI will relieve teams of repetitive, manual work. “This means marketers can finally focus more on strategy, creativity, and big-picture thinking,” Gulati says. He adds that GPT agents are used to simplify workflows, optimise campaigns and support planning, while other AI tools assist with research and design. “Instead of being stuck in routine tasks, our team can now focus on insights, creative problem-solving, and ensuring every AI-driven output moves the brand in the right direction,” Gulati says.

Khatri, shares, “Agentic capabilities accelerate ideation, generate content variations and adapt assets across platforms and formats. A campaign that previously required a production team to manually resize and localise assets for eight platforms can now be handled in a fraction of the time. The real value, though, comes from connecting these two streams: creative performance data feeds directly into media optimisation and media signals inform the next round of creative. It becomes a continuous improvement loop rather than a series of disconnected handoffs. The intent is not to replace craft. It is to remove the repetitive production tax so that our teams spend more time on the ideas and fewer hours resizing the same banner 20 times.”

Varun Seth, Managing Partner, AdGlobal360, believes the shift will elevate human roles. “Agentic AI is not replacing marketers but upgrading them,” he says. According to Seth, marketers will evolve from operating tools to designing outcomes. Their value will lie in orchestration, brand thinking and creativity at scale rather than manual execution.

Agencies and brands are set for a structural pivot.While automation will inevitably reshape workflows, many industry leaders believe the real transformation will lie in how agency teams evolve. Das argues that agentic systems will shift the composition of teams rather than eliminate the need for them. “Roles will inevitably evolve, with teams becoming AI-enabled partners supporting client growth. We will see a greater emphasis on strategists, data specialists, technologists, and creative thinkers, while roles focused primarily on manual optimisation, reporting, and repetitive operational tasks will gradually diminish as these functions become increasingly automated.” In this environment, the agencies that succeed will likely be those that combine technological capability with strategic expertise — using agentic systems not simply to reduce costs but to elevate the value of human decision-making. Execution-heavy models will give way to new identities: martech transformation partners, AI governance advisors and customer lifecycle strategists. In this emerging landscape, the agencies that thrive will be those that help brands navigate both the technology and the transformation it enables.