Mondelez India’s Cadbury brand made waves when it used AI to customize more than 130,000 hyper-local video ads featuring Shah Rukh Khan, each addressing a neighborhood store by name. Around the same time, food delivery giant Swiggy auto-generated over 1,000 unique promotional videos for restaurant partners using generative AI. These high-visibility campaigns spotlight a quieter but far more structural shift underway inside Indian marketing teams. A new, unnamed middle layer of AI-focused specialists is emerging behind the scenes. They are not traditional creatives or core IT engineers, but a hybrid group working as AI prompt engineers, automation orchestrators, MarTech stack integrators, and data translators. These roles rarely appear on organization charts, come without formal KPIs, and often lack clear reporting lines. Yet they are fast becoming indispensable as enterprises deploy AI across creativity, campaign execution, targeting, and customer engagement.
Across Indian enterprises, AI adoption in marketing has accelerated sharply. Nearly all large companies now report using some form of generative AI, and close to half say AI is already embedded in everyday workflows. At the same time, a large share of marketing teams admit they are still experimenting rather than operating mature AI-led systems. This gap between ambition and execution is where the new middle layer has taken root. While boards and leadership teams push for AI-led efficiency and personalization, most marketing departments lack people who can translate strategy into machine-driven execution. Skill gaps remain the biggest bottleneck. A majority of Indian marketing leaders say they do not yet have the talent required to use AI tools effectively, and only a small fraction of CMOs believe their teams are fully prepared to integrate advanced AI into marketing operations.
One of the most visible roles in this emerging layer is that of the AI prompt engineer. As generative AI tools are increasingly used to produce ad copy, social posts, emails, and visuals, companies are discovering that results depend heavily on how the AI is instructed. Prompt engineering has become a creative discipline of its own, requiring an understanding of language, tone, visual cues, and brand context, alongside knowledge of how AI models respond to inputs. Deepak Oram, Head of MarTech at HDFC Bank, has publicly described prompt engineering as sitting at the intersection of art and machine-guided production. According to him, writing prompts today is not about typing a command, but about understanding narrative intent, pacing, visual grammar, and brand consistency. In practice, this means content strategists and creative managers now spend hours refining prompts, reference material, and data inputs so that AI-generated outputs align with brand standards.
These prompt specialists are rarely hired under that title. Most still carry legacy labels such as content strategist, brand manager, or digital lead. Yet job descriptions increasingly demand experience with generative AI tools, experimentation frameworks, and rapid iteration. The rise of these roles reflects a broader truth: creativity in marketing is no longer purely human-driven. It is now co-created with machines, and someone must sit in the middle to guide that collaboration.
Alongside prompt engineers, another critical role has emerged: the automation orchestrator. Modern marketing campaigns are no longer linear or manual. Emails, WhatsApp messages, push notifications, ads, and website experiences are increasingly triggered by AI-driven decision engines that respond to customer behavior in real time. Someone has to design these flows, define the rules, monitor outcomes, and step in when automation goes wrong. That responsibility is often carried by marketing operations leaders or digital strategists who have become de facto AI conductors.
As marketing automation deepens, human roles are shifting upward. A growing share of companies report reallocating human effort away from execution and toward oversight, strategy, and quality control as AI agents handle routine tasks. This transition has created both opportunity and anxiety inside marketing teams. Creative professionals worry about relevance, while leaders grapple with accountability. When an AI system chooses which customer to target, what message to send, and how much budget to allocate, the question of responsibility becomes unavoidable. Orchestrators sit at the center of this tension, balancing speed with control and innovation with risk.
The complexity of modern MarTech stacks has further fueled the rise of integrator roles. Large enterprises today use dozens of marketing tools across CRM, analytics, media buying, content management, personalization, and customer data platforms. Studies suggest that marketers use an average of more than 70 tools, yet only a third of available capabilities are fully utilized. This underutilization is rarely due to lack of software, but rather lack of integration and expertise. MarTech stack integrators, often embedded within marketing or operating as bridges to IT teams, work to connect platforms, streamline workflows, and ensure that AI tools can function across fragmented systems.
HDFC Bank offers a clear example of this challenge. Its marketing infrastructure spans legacy banking systems and newer digital platforms, requiring continuous restructuring to accommodate AI-led personalization and analytics. Similar challenges exist at companies like Flipkart, which has invested heavily in generative AI to enhance e-commerce experiences, and Unilever, which operates across multiple brands and markets. In such environments, integrators ensure that data flows correctly between systems, AI insights reach the right teams, and automation does not collapse under technical complexity.
Perhaps the least visible but most crucial role in this middle layer is that of the data translator. As AI systems generate increasingly complex outputs, marketing teams need people who can interpret these insights and convert them into actionable decisions. Ravi Santhanam, CMO of HDFC Bank, has stated publicly that the use of data science and AI in marketing is no longer optional, as customers now expect personalization and relevance at scale. Yet many marketers struggle to understand model outputs, probability scores, and algorithmic recommendations. Data translators bridge this gap by explaining what the AI is saying in business terms and advising teams on how to act.
In many organizations, CMOs themselves are forced into this translator role, sitting between data scientists and creative teams. But as AI adoption deepens, the responsibility is increasingly pushed down the hierarchy. Insight managers, analytics leads, and performance marketers are now expected to understand both data and storytelling. They validate AI outputs, question anomalies, and ensure decisions align with brand strategy and regulatory expectations. Without this layer, AI-driven marketing risks becoming either blindly automated or completely ignored.
Indian and India-facing companies are already reshaping their marketing teams around these emerging roles, even if unofficially. Swiggy has reportedly set up internal groups focused on generative AI experimentation, drawing talent from content, design, and engineering. Flipkart’s acquisition of an AI startup was as much about acquiring specialized talent as technology. Unilever continues to experiment with AI-generated creatives globally, with Indian teams adapting these systems locally. Traditional conglomerates such as Tata Motors and TVS Motor have appointed senior AI leadership to drive adoption across functions, including marketing.
Despite their growing importance, these middle-layer roles remain largely informal. Career paths are unclear, success metrics are undefined, and compensation structures have yet to catch up. Yet history suggests formalization will follow adoption. Just as social media management evolved from an ad hoc responsibility into a recognized profession, AI-centric marketing roles are likely to crystallize over the next few years. Titles will stabilize, training programs will expand, and performance frameworks will emerge.
What is already clear is that marketing is no longer just about big ideas or clever slogans. It is increasingly about orchestrating intelligent systems, managing automation responsibly, and translating machine intelligence into human insight. The new middle layer of AI specialists is quietly becoming the backbone of this transformation. They may not yet have a name, but they are already reshaping how Indian marketing works, one prompt, workflow, and data insight at a time.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.